Computer Science | UCD Research.

Book

Assoc Professor Pavel Gladyshev
Gladyshev, P., Goel, S., James, J., Markowsky, G., & Johnson, D. (2022). Preface (Vol. 441 LNICST).
Dr Punit Gupta
Gupta, P., Goyal, M. K., Chakraborty, S., & Elngar, A. A. (2022). Machine Learning and Optimization Models for Optimization in Cloud. doi:10.1201/9781003185376
Assoc Professor Georgiana Ifrim
Lemaire, V., Malinowski, S., Bagnall, A., Guyet, T., Tavenard, R., & Ifrim, G. (2022). Advanced Analytics and Learning on Temporal Data 6th ECML PKDD Workshop, AALTD 2021, Bilbao, Spain, September 13, 2021, Revised Selected Papers. Springer.
Dr Nhien An Le Khac
Le-Khac, N. -A., & Choo, K. -K. R. (2022). A Practical Hands-on Approach to Database Forensics. Springer International Publishing. doi:10.1007/978-3-031-16127-8
Dr Madhusanka Liyanage
Ding, A. Y., & Liyanage, M. (2022). Mobile Edge Computing and Communications Driving Forces, Technology Foundation, and Application Areas. Wiley-IEEE Press.

Chapter

Dr Nima Afraz
Afraz, N., Ruffini, M., & Ahmadi, H. (2021). Hyperledger Blockchain-Based Distributed Marketplaces for 5G Networks. In Unknown Book (pp. 117-136). Wiley. doi:10.1002/9781119790839.ch5
Dr Oisin Boydell
Ariappampalayam Krishnamoorthi, P., Shahid, S., & Boydell, O. (2022). Preserving Privacy in Private Blockchain Networks. In Unknown Book (Vol. 12991 LNCS, pp. 118-128). doi:10.1007/978-3-030-96527-3_8
Dr Rob Brennan
Vining, R., McDonald, N., McKenna, L., Ward, M. E., Doyle, B., Liang, J., et al. (2022). Developing a Framework for Trustworthy AI-Supported Knowledge Management in the Governance of Risk and Change. In HCI International 2022 - Late Breaking Papers. Design, User Experience and Interaction (pp. 318-333). Springer International Publishing. doi:10.1007/978-3-031-17615-9_22
Hernandez, J., McKenna, L., & Brennan, R. (2022). TIKD: A Trusted Integrated Knowledge Dataspace for Sensitive Data Sharing and Collaboration. In Data Spaces (pp. 265-291). Springer International Publishing. doi:10.1007/978-3-030-98636-0_13
Professor Joe Carthy
Monaghan, M., Carthy, J., O'Boyle, K., Sokell, E., Wilson, W., & Naidoo, G. (2022). Designing buildings for student-centered learning: The Science Centre at University College Dublin. In Leading Change in Healthcare: Transforming Organizations Using Complexity, Positive Psychology and Relationship-Centered Care (pp. 211-235). doi:10.1201/9780429084119-13
Assoc Professor Fred Cummins
Cummins, F. (2022). Distinctions and common ground in collective epistemology.. In L. H. Kaufmann, F. Cummins, R. Dible, L. Conrad, G. Ellsbury, A. Crompton, & F. Grote (Eds.), Laws of Form: A Fiftieth Anniversary. Singapore: World Scientific Publishing.
Professor Pádraig Cunningham
Kathirgamanathan, B., Buckley, C., Caulfield, B., & Cunningham, P. (2022). Feature Subset Selection for Detecting Fatigue in Runners Using Time Series Sensor Data. In Unknown Book (Vol. 13363 LNCS, pp. 541-552). doi:10.1007/978-3-031-09037-0_44
Kathirgamanathan, B., Davenport, J., Caulfield, B., & Cunningham, P. (2022). Using Barycenters as Aggregate Representations of Repetition-Based Time-Series Exercise Data. In Unknown Book (Vol. 1571 CCIS, pp. 178-188). doi:10.1007/978-3-031-02044-5_15
Blanzeisky, W., Smyth, B., & Cunningham, P. (2022). Algorithmic Bias and Fairness in Case-Based Reasoning. In Unknown Book (Vol. 13405 LNAI, pp. 48-62). doi:10.1007/978-3-031-14923-8_4
Dr Ruihai Dong
Wang, Q., Muhammad, K., O'Reilly-Morgan, D., Smyth, B., Tragos, E., Lawlor, A., et al. (2022). MARF: User-Item Mutual Aware Representation with Feedback. In Unknown Book (Vol. 13362 LNCS, pp. 3-15). doi:10.1007/978-3-031-09917-5_1
Dr Punit Gupta
Bhardwaj, S., Tomar, B. S., Ankur, A., & Gupta, P. (2022). Machination of Human Carpus. In Unknown Book (Vol. 238, pp. 353-359). doi:10.1007/978-981-16-2641-8_34
Bhardwaj, S., & Sharma, N. (2022). Novel Algorithm for Detection and Analysis of Irremediable diseases—Progeria. In Smart Systems: Innovations in Computing (pp. 101-112). Springer Singapore. doi:10.1007/978-981-16-2877-1_10
Bhagat, S., & Gupta, P. (2022). A Survey on Scalable Resource Allocation in Cloud Computing. In Unknown Book (Vol. 832, pp. 401-414). doi:10.1007/978-981-16-8248-3_33
Malhotra, M., Gupta, P., Dhaka, V. S., & Singh, A. (2022). Model to Predict the Crop Cost Using Machine Learning and Read Dataset. In Unknown Book (Vol. 832, pp. 415-426). doi:10.1007/978-981-16-8248-3_34
Rawat, P. S., Bhadoria, R. S., & Gupta, P. (2022). Comparative Study of the Virtual Machine Scheduling Approaches in Cloud Environment. In Unknown Book (Vol. 235, pp. 411-418). doi:10.1007/978-981-16-2877-1_37
Bhardwaj, S., Kaushik, T., Bisht, M., Gupta, P., & Mundra, S. (2022). Detection of Alzheimer Disease Using Machine Learning. In Unknown Book (Vol. 235, pp. 443-450). doi:10.1007/978-981-16-2877-1_40
Mundra, S., Mundra, A., Saigal, A., Gupta, P., Agarwal, J., & Goyal, M. K. (2022). Machine Learning Approaches for the Classification of Spammed Text in Messages. In Unknown Book (Vol. 235, pp. 601-617). doi:10.1007/978-981-16-2877-1_56
Verma, R., & Gupta, P. (2022). Neural Network-Based Resource Allocation Model in Multilayered Cloud. In Machine Learning and Optimization Models for Optimization in Cloud (pp. 33-54). doi:10.1201/9781003185376-3
Malik, Y., Goyal, D., Sachdeva, A., & Gupta, P. (2022). Cost-Efficient BAT Algorithm for Task Scheduling in Cloud. In Unknown Book (Vol. 855, pp. 637-644). doi:10.1007/978-981-16-8892-8_48
Agarwal, D., Agrawal, S., & Gupta, P. (2022). Fault-Aware Machine Learning and Deep Learning-Based Algorithm for Cloud Architecture. In Machine Learning and Optimization Models for Optimization in Cloud (pp. 119-136). doi:10.1201/9781003185376-7
Sharma, F., & Gupta, P. (2022). Machine Learning-Based Predictive Model to Improve Cloud Application Performance in Cloud SaaS. In Machine Learning and Optimization Models for Optimization in Cloud (pp. 95-118). doi:10.1201/9781003185376-6
Bhagat, S., & Gupta, P. (2022). Neural Network and Deep Learning-Based Resource Allocation Model for Multilayered Cloud. In Machine Learning and Optimization Models for Optimization in Cloud (pp. 73-94). doi:10.1201/9781003185376-5
Rane, D., Chourey, V., Verma, R., & Gupta, P. (2022). Consideration of Availability and Reliability in Cloud Computing. In Machine Learning and Optimization Models for Optimization in Cloud (pp. 55-72). doi:10.1201/9781003185376-4
Gupta, P., & Goyal, M. K. (2022). Machine Learning, Deep Learning-Based Optimization in Multilayered Cloud. In Machine Learning and Optimization Models for Optimization in Cloud (pp. 15-32). doi:10.1201/9781003185376-2
Singh, A., Gupta, P., Sharma, V. K., Jain, T., & Chauhan, S. (2022). Intelligent Scalable Algorithm for Resource Efficiency in Cloud. In Machine Learning and Optimization Models for Optimization in Cloud (pp. 185-200). doi:10.1201/9781003185376-10
Assoc Professor Neil Hurley
Wang, Q., Muhammad, K., O'Reilly-Morgan, D., Smyth, B., Tragos, E., Lawlor, A., et al. (2022). MARF: User-Item Mutual Aware Representation with Feedback. In Unknown Book (Vol. 13362 LNCS, pp. 3-15). doi:10.1007/978-3-031-09917-5_1
Assoc Professor Georgiana Ifrim
Singh, A., Le, B. T., Nguyen, T. L., Whelan, D., O’Reilly, M., Caulfield, B., & Ifrim, G. (2022). Interpretable Classification of Human Exercise Videos Through Pose Estimation and Multivariate Time Series Analysis. In Unknown Book (Vol. 1013, pp. 181-199). doi:10.1007/978-3-030-93080-6_14
Professor Mark Keane
Warren, G., Smyth, B., & Keane, M. T. (2022). “Better” Counterfactuals, Ones People Can Understand: Psychologically-Plausible Case-Based Counterfactuals Using Categorical Features for Explainable AI (XAI). In Unknown Book (Vol. 13405 LNAI, pp. 63-78). doi:10.1007/978-3-031-14923-8_5
Smyth, B., & Keane, M. T. (2022). A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations. In Unknown Book (Vol. 13405 LNAI, pp. 18-32). doi:10.1007/978-3-031-14923-8_2
Assoc Professor Alexey Lastovetsky
Khaleghzadeh, H., Manumachu, R. R., & Lastovetsky, A. (2022). A Novel Algorithm for Bi-objective Performance-Energy Optimization of Applications with Continuous Performance and Linear Energy Profiles on Heterogeneous HPC Platforms. In Unknown Book (Vol. 13098 LNCS, pp. 166-178). doi:10.1007/978-3-031-06156-1_14
Dr Aonghus Lawlor
Wang, Q., Muhammad, K., O'Reilly-Morgan, D., Smyth, B., Tragos, E., Lawlor, A., et al. (2022). MARF: User-Item Mutual Aware Representation with Feedback. In Unknown Book (Vol. 13362 LNCS, pp. 3-15). doi:10.1007/978-3-031-09917-5_1
Feely, C., Caulfield, B., Lawlor, A., & Smyth, B. (2022). An Extended Case-Based Approach to Race-Time Prediction for Recreational Marathon Runners. In Unknown Book (Vol. 13405 LNAI, pp. 335-349). doi:10.1007/978-3-031-14923-8_22
Dr Nhien An Le Khac
Buurke, R., & Le-Khac, N. A. (2022). Accessing Secure Data on Android Through Application Analysis. In Unknown Book (Vol. 441 LNICST, pp. 93-108). doi:10.1007/978-3-031-06365-7_6
Dr David Lillis
Zhang, G., Nulty, P., & Lillis, D. (2022). A Decade of Legal Argumentation Mining: Datasets and Approaches. In Unknown Book (Vol. 13286 LNCS, pp. 240-252). doi:10.1007/978-3-031-08473-7_22
Wang, C., Nulty, P., & Lillis, D. (2022). Using Pseudo-Labelled Data for Zero-Shot Text Classification. In Unknown Book (Vol. 13286 LNCS, pp. 35-46). doi:10.1007/978-3-031-08473-7_4
Dr Madhusanka Liyanage
Maksymyuk, T., Gazda, J., Liyanage, M., Han, L., Shubyn, B., Strykhaliuk, B., et al. (2022). AI-Enabled Blockchain Framework for Dynamic Spectrum Management in Multi-operator 6G Networks. In Lecture Notes in Electrical Engineering (Vol. 831, pp. 322-338). doi:10.1007/978-3-030-92435-5_19
Assoc Professor Brian Mac Namee
Hagos, M. T., Curran, K. M., & Mac Namee, B. (2022). Impact of Feedback Type on Explanatory Interactive Learning. In Unknown Book (Vol. 13515 LNAI, pp. 127-137). doi:10.1007/978-3-031-16564-1_13
Professor Eleni Mangina
Mangina, E., McGirl, T., Ryan, G., Murphy, J., & McAuliffe, F. (2022). Experience API (xAPI) for Virtual Reality (VR) Education in Medicine. In Lecture Notes in Networks and Systems (Vol. 456, pp. 335-359). doi:10.1007/978-3-031-04286-7_16
Mangina, E., Burke, E., Matson, R., O’Briain, R., Caffrey, J. M., & Saffari, M. (2022). Plant Species Detection Using Image Processing and Deep Learning: A Mobile-Based Application. In Springer Optimization and Its Applications (Vol. 183, pp. 103-130). doi:10.1007/978-3-030-84148-5_5
Farella, M., Arrigo, M., Tosto, C., Taibi, D., Seta, L., Chifari, A., et al. (2022). An Augmented Reality Solution for the Positive Behaviour Intervention and Support. In Unknown Book (Vol. 13484 LNCS, pp. 206-212). doi:10.1007/978-3-031-16234-3_12
Mangina, E., Psyrra, G., Phelan, T., & Schwaiger, M. (2022). Data Analytics on eXtended Reality (XR) for Pedagogy Education: Educators’ Awareness for the Future of Education in Smart Cities. In Advances in Intelligent Systems and Computing (pp. 490-493). Springer International Publishing. doi:10.1007/978-3-031-14054-9_45
Dr Ravi Manumachu
Khaleghzadeh, H., Manumachu, R. R., & Lastovetsky, A. (2022). A Novel Algorithm for Bi-objective Performance-Energy Optimization of Applications with Continuous Performance and Linear Energy Profiles on Heterogeneous HPC Platforms. In Unknown Book (Vol. 13098 LNCS, pp. 166-178). doi:10.1007/978-3-031-06156-1_14
Assoc Professor Mark Scanlon
Kanta, A., Coisel, I., & Scanlon, M. (2022). PCWQ: A Framework for Evaluating Password Cracking Wordlist Quality. In Unknown Book (Vol. 441 LNICST, pp. 159-175). doi:10.1007/978-3-031-06365-7_10
Dr Arsalan Shahid
Treacy, C., Regan, G., Shahid, A., & Maguire, B. (2022). Legal, Privacy, Social and Ethical Requirements and Impact Assessment for an Artificial Intelligence Based Medical Imaging Project. In Unknown Book (Vol. 1646 CCIS, pp. 29-44). doi:10.1007/978-3-031-15559-8_3
Professor Barry Smyth
Feely, C., Caulfield, B., Lawlor, A., & Smyth, B. (2022). An Extended Case-Based Approach to Race-Time Prediction for Recreational Marathon Runners. In Unknown Book (Vol. 13405 LNAI, pp. 335-349). doi:10.1007/978-3-031-14923-8_22
Warren, G., Smyth, B., & Keane, M. T. (2022). “Better” Counterfactuals, Ones People Can Understand: Psychologically-Plausible Case-Based Counterfactuals Using Categorical Features for Explainable AI (XAI). In Unknown Book (Vol. 13405 LNAI, pp. 63-78). doi:10.1007/978-3-031-14923-8_5
Blanzeisky, W., Smyth, B., & Cunningham, P. (2022). Algorithmic Bias and Fairness in Case-Based Reasoning. In Unknown Book (Vol. 13405 LNAI, pp. 48-62). doi:10.1007/978-3-031-14923-8_4
Smyth, B., & Keane, M. T. (2022). A Few Good Counterfactuals: Generating Interpretable, Plausible and Diverse Counterfactual Explanations. In Unknown Book (Vol. 13405 LNAI, pp. 18-32). doi:10.1007/978-3-031-14923-8_2
Wang, Q., Muhammad, K., O'Reilly-Morgan, D., Smyth, B., Tragos, E., Lawlor, A., et al. (2022). MARF: User-Item Mutual Aware Representation with Feedback. In Unknown Book (Vol. 13362 LNCS, pp. 3-15). doi:10.1007/978-3-031-09917-5_1

Conference Paper

Dr Deepak Ajwani
Tayebi, D., Ray, S., & Ajwani, D. (2022). Learning to Prune Instances of k-median and Related Problems. In Proceedings of the Workshop on Algorithm Engineering and Experiments Vol. 2022-January (pp. 184-194).
Dr Brett Becker
Becker, B. (2021). The Roles and Challenges of Computing Terminology in Non-Computing Disciplines. In ACM International Conference Proceeding Series. doi:10.1145/3481282.3481284
Brown, N., Kyfonidis, C., Weill-Tessier, P., Becker, B., Dillane, J., & Kölling, M. (2021). A Frame of Mind: Frame-based vs. Text-based Editing. In ACM International Conference Proceeding Series. doi:10.1145/3481282.3481286
Dillane, J., Karvelas, I., & Becker, B. A. (2021). Portraits of Programmer Behavior in a Frame-Based Language. In ACM International Conference Proceeding Series (pp. 49-56). doi:10.1145/3507923.3507933
Finnie-Ansley, J., Denny, P., Becker, B. A., Luxton-Reilly, A., & Prather, J. (2022). The robots are coming: Exploring the implications of OpenAI codex on introductory programming. In ACM International Conference Proceeding Series (pp. 10-19). doi:10.1145/3511861.3511863
Caton, S., Russell, S., & Becker, B. A. (2022). What Fails Once, Fails Again: Common Repeated Errors in Introductory Programming Automated Assessments. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education Vol. 1 (pp. 955-961). doi:10.1145/3478431.3499419
Becker, B. A., Gallagher, D., Denny, P., Prather, J., Gostomski, C., Norris, K., & Powell, G. (2022). From the Horse's Mouth: TheWordsWe Use to Teach Diverse Student Groups Across Three Continents. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education Vol. 1 (pp. 71-77). doi:10.1145/3478431.3499392
Groeneveld, W., Becker, B. A., & Vennekens, J. (2022). How Creatively AreWe Teaching and Assessing Creativity in Computing Education: A Systematic Literature Review. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education Vol. 1 (pp. 934-940). doi:10.1145/3478431.3499360
DIckson, P. E., Richards, T., & Becker, B. A. (2022). Experiences Implementing and Utilizing a Notional Machine in the Classroom. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education Vol. 1 (pp. 850-856). doi:10.1145/3478431.3499320
Karvelas, I., & Becker, B. A. (2022). Sympathy for the (Novice) Developer: Programming Activity When Compilation Mechanism Varies. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education Vol. 1 (pp. 962-968). doi:10.1145/3478431.3499347
Denny, P., Becker, B. A., Bosch, N., Prather, J., Reeves, B., & Whalley, J. (2022). Novice Reflections during the Transition to a New Programming Language. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education Vol. 1 (pp. 948-954). doi:10.1145/3478431.3499314
Decker, A., Weiss, M. A., Becker, B. A., Dougherty, J. P., Edwards, S. H., Goode, J., et al. (2022). Piecing Together the Next 15 Years of Computing Education Research Workshop Report. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2 (pp. 1051-1052). doi:10.1145/3478432.3499037
Quille, K., Faherty, R., & Becker, B. A. (2022). Building K-12 Teacher Capacity to Expand Uptake in a National CS Curriculum. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2 (pp. 1086). doi:10.1145/3478432.3499063
Nolan, K., Quille, K., & Becker, B. A. (2022). CSLINC a Nationwide CS MOOC for Second-level Students. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2 (pp. 1100). doi:10.1145/3478432.3499069
Mahon, J., Quille, K., Mac Namee, B., & Becker, B. A. (2022). A Novel Machine Learning and Artificial Intelligence Course for Secondary School Students. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2 (pp. 1155). doi:10.1145/3478432.3499073
Faherty, R., Quille, K., & Becker, B. A. (2022). Comparing the Programming Self-Efficacy of Teachers Using CSLINC to Those Teaching the Formal National Curriculum. In Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE Vol. 2 (pp. 619). doi:10.1145/3502717.3532130
Becker, B. A., Quille, K., Laakso, M. J., Barendsen, E., & Simon. (2022). ITiCSE 2022 Chairs' Welcome. In Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE Vol. 1 (pp. III-IV).
Prather, J., Margulieux, L., Whalley, J., Denny, P., Reeves, B. N., Becker, B. A., et al. (2022). Getting By With Help From My Friends: Group Study in Introductory Programming Understood as Socially Shared Regulation. In ICER 2022 - Proceedings of the 2022 ACM Conference on International Computing Education Research Vol. 1 (pp. 164-176). doi:10.1145/3501385.3543970
Professor Michela Bertolotto
Vo, A. V., Lokugam Hewage, C. N., Le Khac, N. A., Bertolotto, M., & Laefer, D. (2021). A PARALLEL ALGORITHM FOR LOCAL POINT DENSITY INDEX COMPUTATION OF LARGE POINT CLOUDS. In 3D GeoInfo 2021 Vol. VIII-4/W2-2021 (pp. 75-82). New York: ISPRS Annals. doi:10.5194/isprs-annals-VIII-4-W2-2021-75-2021
Burse, R., Bertolotto, M., & Mcardle, G. (2022). A Novel Atomic Annotator for Quality Assurance of Biomedical Ontologies. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies. SCITEPRESS - Science and Technology Publications. doi:10.5220/0010782500003123
Mattos, A., Bertolotto, M., & McArdle, G. (2022). Mapping Slums with Deep Learning Feature Extraction. In CEUR Workshop Proceedings Vol. 3207 (pp. 27-32).
Dr Rob Brennan
Hickey, D., & Brennan, R. (2021). A GDPR International Transfer Compliance Framework Based on an Extended Data Privacy Vocabulary (DPV). In Frontiers in Artificial Intelligence and Applications Vol. 346 (pp. 161-170). doi:10.3233/FAIA210332
Czarnik, A., Darragh, A., Hurley, M., O’Connell, D., Quagliata, M., & Brennan, R. (2022). Best Practice in Multi-organisation Sensitive Health Data Sharing: A Comparative Analysis of Ireland’s Data Governance Approach for the Covid–19 Data Research Hub. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies. SCITEPRESS - Science and Technology Publications. doi:10.5220/0010802100003123
Trestian, R., Celeste, E., Xie, G., Lohar, P., Bendechache, M., Brennan, R., & Ta, I. (2022). The Privacy Paradox-Investigating People's Attitude Towards Privacy in a Time of COVID-19. In 14th International Conference on Communications, COMM 2022 - Proceedings. doi:10.1109/COMM54429.2022.9817170
Kumar, T., Turab, M., Talpur, S., Brennan, R., & Bendechache, M. (2022). Detection Datasets: Forged Characters for Passport and Driving Licence. In Artificial Intelligence, Soft Computing and Applications. Academy and Industry Research Collaboration Center (AIRCC). doi:10.5121/csit.2022.120204
Kumar, T., Brennan, R., & Bendechache, M. (2022). Stride Random Erasing Augmentation. In Artificial Intelligence, Soft Computing and Applications. Academy and Industry Research Collaboration Center (AIRCC). doi:10.5121/csit.2022.120201
Aleem, S., Kumar, T., Little, S., Bendechache, M., Brennan, R., & McGuinness, K. (2022). Random Data Augmentation based Enhancement: A Generalized Enhancement Approach for Medical Datasets. In 24th Irish Machine Vision and Image Processing Conference. Irish Pattern Recognition and Classification Society. doi:10.56541/fumf3414
Dr Abey Campbell
Pan, X., Xu, X., Dev, S., & Campbell, A. (2021). 3D Displays: Their Evolution, Inherent Challenges & Future Perspectives. In Future Technologies Conference (FTC).
Xu, Z., Liang, Y., Campbell, A. G., & Dev, S. (2022). An Explore of Virtual Reality for Awareness of the Climate Change Crisis: A Simulation of Sea Level Rise. In Proceedings of 2022 8th International Conference of the Immersive Learning Research Network, iLRN 2022. doi:10.23919/iLRN55037.2022.9815983
Banjar, A., & Campbell, A. G. (2022). Work-in-Progress - Design of Mixed Reality Educational Applications Using Enhanced ARCS+G Model for Motivation. In Proceedings of 2022 8th International Conference of the Immersive Learning Research Network, iLRN 2022. doi:10.23919/iLRN55037.2022.9815916
Banjar, A., & Campbell, A. G. (2022). Doctoral Colloquium - The Potential of Mixed-Reality Technology for Motivating Dentistry Students in Higher Education. In Proceedings of 2022 8th International Conference of the Immersive Learning Research Network, iLRN 2022. doi:10.23919/iLRN55037.2022.9815939
Zheng, M., Pan, X., Bermeo, N. V., Thomas, R. J., Coyle, D., O'Hare, G. M. P., & Campbell, A. G. (2022). STARE: Semantic Augmented Reality Decision Support in Smart Environments. In Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022 (pp. 630-631). doi:10.1109/VRW55335.2022.00166
Sayarh, J. H., & Campbell, A. G. (2022). Digital Preservation of Experiences in Virtual Worlds: Extending Digital Rights to Include Right to Replay. In Lecture Notes in Networks and Systems Vol. 360 LNNS (pp. 432-442). doi:10.1007/978-3-030-89912-7_33
Pan, X., Xu, X., Dev, S., & Campbell, A. G. (2022). 3D Displays: Their Evolution, Inherent Challenges and Future Perspectives. In Lecture Notes in Networks and Systems Vol. 360 LNNS (pp. 397-415). doi:10.1007/978-3-030-89912-7_31
Zheng, M., Bermeo, N. V., & Campbell, A. G. (2022). Augmented Reality In-Field Observation Creation and Visualization in Underperforming Areas. In Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022 (pp. 852-853). doi:10.1109/VRW55335.2022.00277
Dr Simon Caton
Caton, S., Russell, S., & Becker, B. A. (2022). What Fails Once, Fails Again: Common Repeated Errors in Introductory Programming Automated Assessments. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education Vol. 1 (pp. 955-961). doi:10.1145/3478431.3499419
Dr Dimitris Chatzopoulos
Kumar, A., Khimani, V., Chatzopoulos, D., & Hui, P. (2022). FEDCLEAN: A DEFENSE MECHANISM AGAINST PARAMETER POISONING ATTACKS IN FEDERATED LEARNING. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings Vol. 2022-May (pp. 4333-4337). doi:10.1109/ICASSP43922.2022.9747497
Tirana, J., Pappas, C., Chatzopoulos, D., Lalis, S., & Vavalis, M. (2022). The role of compute nodes in privacy-aware decentralized AI. In EMDL 2022 - Proceedings of the 6th International Workshop on Embedded and Mobile Deep Learning, Part of MobiSys 2022 (pp. 19-24). doi:10.1145/3539491.3539594
Assoc Professor David Coyle
Zheng, M., Pan, X., Bermeo, N. V., Thomas, R. J., Coyle, D., O'Hare, G. M. P., & Campbell, A. G. (2022). STARE: Semantic Augmented Reality Decision Support in Smart Environments. In Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022 (pp. 630-631). doi:10.1109/VRW55335.2022.00166
Nunes Vilaza, G., Doherty, K., McCashin, D., Coyle, D., Bardram, J., & Barry, M. (2022). A Scoping Review of Ethics Across SIGCHI. In DIS 2022 - Proceedings of the 2022 ACM Designing Interactive Systems Conference: Digital Wellbeing (pp. 137-154). doi:10.1145/3532106.3533511
Professor Pádraig Cunningham
Mullen, J., Celikin, M., Cunningham, P., & Browne, D. (2022). Research acceleration via Machine Learning for characterization of growing dendritic crystals from in situ X-ray videos of alloy solidification. In First World Congress on Artificial Intelligence in Materials and Manufacturing (AIM 2022). Pittsburgh, Pennsylvania, USA: TMS.
Dr Soumyabrata Dev
Wu, J., Orlandi, F., Alskaif, T., O'Sullivan, D., & Dev, S. (2021). Ontology modeling for decentralized household energy systems. In SEST 2021 - 4th International Conference on Smart Energy Systems and Technologies. doi:10.1109/SEST50973.2021.9543327
Jain, M., Jain, M., Alskaif, T., & Dev, S. (2021). Impact of load demand dataset characteristics on clustering validation indices. In SEST 2021 - 4th International Conference on Smart Energy Systems and Technologies. doi:10.1109/SEST50973.2021.9543285
Pan, X., Xu, X., Dev, S., & Campbell, A. (2021). 3D Displays: Their Evolution, Inherent Challenges & Future Perspectives. In Future Technologies Conference (FTC).
Fathima, T. A., Nedumpozhimana, V., Lee, Y. H., & Dev, S. (2021). Embedding Cyclical Information in Solar Irradiance Forecasting. In Proc. IEEE AP-S Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting.
Wu, J., Chen, H., Orlandi, F., Lee, Y. H., O'Sullivan, D., & Dev, S. (2021). Automated Climate Analyses Using Knowledge Graph. In Proc. IEEE AP-S Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting.
Pathan, M. S., Wu, J., Lee, Y. H., Yan, J., & Dev, S. (2021). Analyzing the Impact of Meteorological Parameters on Rainfall Prediction. In Proc. IEEE AP-S Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting.
Wang, H., Pathan, M. S., Lee, Y. H., & Dev, S. (2021). Day-ahead Forecasts of Air Temperature. In Proc. IEEE AP-S Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting.
Wu, J., Chen, H., Orlandi, F., Lee, Y. H., O'Sullivan, D., & Dev, S. (2021). An Interoperable Open Data Portal for Climate Analysis. In Proc. IEEE AP-S Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting.
Jain, M., Jain, N., Lee, Y. H., Winkler, S., & Dev, S. (2021). Detecting Blurred Ground-based Sky/Cloud Images. In Proc. IEEE AP-S Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting.
Pan, X., Xu, X., Dev, S., & Campbell, A. G. (2022). 3D Displays: Their Evolution, Inherent Challenges and Future Perspectives. In Lecture Notes in Networks and Systems Vol. 360 LNNS (pp. 397-415). doi:10.1007/978-3-030-89912-7_31
Berjon, P., Sharma, R., Nag, A., & Dev, S. (2022). Frequency-Centroid Features Forword Recognition of Non-Native English Speakers. In 2022 33rd Irish Signals and Systems Conference, ISSC 2022. doi:10.1109/ISSC55427.2022.9826202
Xu, Z., Liang, Y., Campbell, A. G., & Dev, S. (2022). An Explore of Virtual Reality for Awareness of the Climate Change Crisis: A Simulation of Sea Level Rise. In Proceedings of 2022 8th International Conference of the Immersive Learning Research Network, iLRN 2022. doi:10.23919/iLRN55037.2022.9815983
Larchen Costuchen, A., & Dev, S. (2022). Confronting challenges of non-formal education: A shift from book-based EFL to tailor-made, experimental syllabi. In ACM International Conference Proceeding Series (pp. 248-254). doi:10.1145/3524383.3524450
Jain, M., Kumari, C., & Dev, S. (2022). Identifying The Best Clear Sky Model For The Delhi-NCR Region. In IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
Wu, J., Orlandi, F., O'Sullivan, D., & Dev, S. (2022). Publishing Climate Data As Linked Data Via Virtual Knowledge Graphs. In IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
Wu, J., Orlandi, F., O'Sullivan, D., & Dev, S. (2022). A Workflow To Convert Live Atmospheric Sensor Data Into Linked Data. In IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
Pathan, M. S., Nag, A., & Dev, S. (2022). Efficient Rainfall Prediction Using a Dimensionality Reduction Method. In IGARSS 2022 - 2022 IEEE International Geoscience and Remote Sensing Symposium. IEEE. doi:10.1109/igarss46834.2022.9884849
Jain, M., Yericherla, D., & Dev, S. (2022). On the Relationship Between Ground- and Satellite-Based Global Horizontal Irradiance. In IEEE International Geoscience and Remote Sensing Symposium (IGARSS).
Wu, J., Orlandi, F., Pathan, M. S., O'Sullivan, D., & Dev, S. (2022). Augmenting Weather Sensor Data With Remote Knowledge Graphs. In IEEE International Geoscience and Remote Sensing Symposium (IGARSS).

Dr Ruihai Dong
Li, I., Feng, A., Wu, H., Li, T., Suzumura, T., & Dong, R. (2022). LiGCN: Label-interpretable Graph Convolutional Networks for Multi-label Text Classification. In DLG4NLP 2022 - 2nd Workshop on Deep Learning on Graphs for Natural Language Processing, Proceedings of the Workshop (pp. 60-70).
Liu, D., Greene, D., & Dong, R. (2022). A Novel Perspective to Look At Attention: Bi-level Attention-based Explainable Topic Modeling for News Classification. In Findings of the Association for Computational Linguistics: ACL 2022. Association for Computational Linguistics. doi:10.18653/v1/2022.findings-acl.178
Yang, L., Dong, R., Smyth, B., Jiazheng, L., & Zhang, Y. (2022). NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-Task Financial Forecasting. In https://aaai-2022.virtualchair.net/papers.html?filter=keywords. Virtual: AAAI Press.
Wang, Q., Tragos, E., Hurley, N., Smyth, B., Lawlor, A., & Dong, R. (2022). Entity-Enhanced Graph Convolutional Network for Accurate and Explainable Recommendation. In UMAP2022 - Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 79-88). doi:10.1145/3503252.3531316
Dr Ray Genoe
Guemimi, M., Camara, D., & Genoe, R. (2022). Iterative Learning for Semi-automatic Annotation Using User Feedback. In Communications in Computer and Information Science Vol. 1616 CCIS (pp. 31-44). doi:10.1007/978-3-031-10525-8_3
Dr Daniel Gibert
Palacín, I., Gibert, D., Planes, J., Arena, S., Orrù, P. F., Melis, M., & Annis, M. (2021). Anomaly Detection for Diagnosing Failures in a Centrifugal Compressor Train. In Frontiers in Artificial Intelligence and Applications Vol. 339 (pp. 217-220). doi:10.3233/FAIA210137
Alsinet, T., Argelich, J., Béjar, R., Gibert, D., Planes, J., & Torrent, N. (2021). Argumentation Reasoning with Graph Neural Networks for Reddit Conversation Analysis. In Frontiers in Artificial Intelligence and Applications Vol. 339 (pp. 123-131). doi:10.3233/FAIA210124
Assoc Professor Pavel Gladyshev
Simioni, M., Gladyshev, P., Habibnia, B., & Nunes de Souza, P. R. (2021). Monitoring an anonymity network: Toward the deanonymization of hidden services. In Forensic Science International: Digital Investigation Vol. 38. doi:10.1016/j.fsidi.2021.301135
Gladyshev, S. P., Gladyshev, P. S., Okrainskaya, I. S., & Gladychev, N. P. (2022). Two-Phase Power Frequency Converter for A.C. Wireless Rotor Machines. In International Conference on Electrical, Computer, and Energy Technologies, ICECET 2022. doi:10.1109/ICECET55527.2022.9872794
Dr Fatemeh Golpayegani
Golpayegani, F., Ghanadbashi, S., & Riad, M. (2021). Urban Emergency Management using Intelligent Traffic Systems: Challenges and Future Directions. In 2021 IEEE International Smart Cities Conference, ISC2 2021. doi:10.1109/ISC253183.2021.9562937
Ghanadbashi, S., & Golpayegani, F. (2021). An Ontology-Based Intelligent Traffic Signal Control Model. In IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC Vol. 2021-September (pp. 2554-2561). doi:10.1109/ITSC48978.2021.9564962
Riad, M., & Golpayegani, F. (2022). A Normative Multi-objective Based Intersection Collision Avoidance System. In Smart Innovation, Systems and Technologies Vol. 306 (pp. 289-300). doi:10.1007/978-981-19-3359-2_25
Dr Derek Greene
Datta, S., Ganguly, D., Roy, D., & Greene, D. (2021). Overview of the Causality-driven Adhoc Information Retrieval (CAIR) task at FIRE-2021. In ACM International Conference Proceeding Series (pp. 25-27). doi:10.1145/3503162.3505648
Sadler, S., Greene, D., & Archambault, D. (2022). Selecting Informative Features for Post-hoc Community Explanation. In Studies in Computational Intelligence Vol. 1015 (pp. 297-308). doi:10.1007/978-3-030-93409-5_25
Cunningham, E., Smyth, B., & Greene, D. (2022). Navigating Multidisciplinary Research Using Field of Study Networks. In Studies in Computational Intelligence Vol. 1015 (pp. 104-115). doi:10.1007/978-3-030-93409-5_10
Ganguly, D., Datta, S., Mitra, M., & Greene, D. (2022). An Analysis of Variations in the Effectiveness of Query Performance Prediction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13185 LNCS (pp. 215-229). doi:10.1007/978-3-030-99736-6_15
Datta, S., Ganguly, D., Mitra, M., & Greene, D. (2022). On the Reproduciblity and Robustness of Query Performance Prediction Experiments - An Extended Abstract. In CEUR Workshop Proceedings Vol. 3178.
Liu, D., Greene, D., & Dong, R. (2022). A Novel Perspective to Look At Attention: Bi-level Attention-based Explainable Topic Modeling for News Classification. In Findings of the Association for Computational Linguistics: ACL 2022. Association for Computational Linguistics. doi:10.18653/v1/2022.findings-acl.178
Delaney, E., Greene, D., Shalloo, L., Lynch, M., & Keane, M. T. (2022). Forecasting for Sustainable Dairy Produce: Enhanced Long-Term, Milk-Supply Forecasting Using k-NN for Data Augmentation, with Prefactual Explanations for XAI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13405 LNAI (pp. 365-379). doi:10.1007/978-3-031-14923-8_24
Datta, S., Ganguly, D., Greene, D., & Mitra, M. (2022). Deep-QPP: A pairwise interaction-based deep learning model for supervised query performance prediction. In WSDM 2022 - Proceedings of the 15th ACM International Conference on Web Search and Data Mining (pp. 201-209). doi:10.1145/3488560.3498491
Cunningham, E., & Greene, D. (2022). Assessing Network Representations for Identifying Interdisciplinarity. In WWW 2022 - Companion Proceedings of the Web Conference 2022 (pp. 758-762). doi:10.1145/3487553.3524653
Datta, S., MacAvaney, S., Ganguly, D., & Greene, D. (2022). A 'Pointwise-Query, Listwise-Document' based Query Performance Prediction Approach. In SIGIR 2022 - Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval (pp. 2148-2153). doi:10.1145/3477495.3531821
Cunningham, E., & Greene, D. (2022). The Structure of Interdisciplinary Science: Uncovering and Explaining Roles in Citation Graphs. In Proc. 11th International Conference on Complex Networks and Their Applications. Palermo, Italy: Springer.
Dr Babak Habibnia
Simioni, M., Gladyshev, P., Habibnia, B., & Nunes de Souza, P. R. (2021). Monitoring an anonymity network: Toward the deanonymization of hidden services. In Forensic Science International: Digital Investigation Vol. 38. doi:10.1016/j.fsidi.2021.301135
Dr Andrew Hines
Becerra, H., Ragano, A., & Hines, A. (2022). Exploring the influence of fine-tuning data on wav2vec 2.0 model for blind speech quality prediction. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH Vol. 2022-September (pp. 4088-4092). doi:10.21437/Interspeech.2022-10766
Chinen, M., Skoglund, J., Reddy, C. K. A., Ragano, A., & Hines, A. (2022). Using Rater and System Metadata to Explain Variance in the VoiceMOS Challenge 2022 Dataset. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH Vol. 2022-September (pp. 4531-4535). doi:10.21437/Interspeech.2022-799
Geraghty, J., Li, J., Ragano, A., & Hines, A. (2022). AQP: An Open Modular Python Platform for Objective Speech and Audio Quality Metrics. In MMSys 2022 - Proceedings of the 13th ACM Multimedia Systems Conference (pp. 191-196). doi:10.1145/3524273.3532885
Assoc Professor Neil Hurley
Ghaffar, F., & Hurley, N. (2021). Modelling social capital: The structural hole connections game. In Proceedings of the 2021 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2021 (pp. 9-13). doi:10.1145/3487351.3488365
Wang, Q., Tragos, E., Hurley, N., Smyth, B., Lawlor, A., & Dong, R. (2022). Entity-Enhanced Graph Convolutional Network for Accurate and Explainable Recommendation. In UMAP2022 - Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 79-88). doi:10.1145/3503252.3531316
Assoc Professor Georgiana Ifrim
Ghalandari, D., Hokamp, C., & Ifrim, G. (2022). Efficient Unsupervised Sentence Compression by Fine-tuning Transformers with Reinforcement Learning. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers). Association for Computational Linguistics. doi:10.18653/v1/2022.acl-long.90
Professor Mark Keane
Delaney, E., Greene, D., Shalloo, L., Lynch, M., & Keane, M. T. (2022). Forecasting for Sustainable Dairy Produce: Enhanced Long-Term, Milk-Supply Forecasting Using k-NN for Data Augmentation, with Prefactual Explanations for XAI. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13405 LNAI (pp. 365-379). doi:10.1007/978-3-031-14923-8_24
Dai, X., Keane, M. T., Shalloo, L., Ruelle, E., & Byrne, R. M. J. (2022). Counterfactual Explanations for Prediction and Diagnosis in XAI. In AIES 2022 - Proceedings of the 2022 AAAI/ACM Conference on AI, Ethics, and Society (pp. 215-226). doi:10.1145/3514094.3534144
Professor Mohand Tahar Kechadi
Akilal, A., & Kechadi, M. T. (2022). A Forensic-Ready Intelligent Transportation System. In Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST Vol. 442 LNICST (pp. 617-630). doi:10.1007/978-3-031-06371-8_39
Assoc Professor Alexey Lastovetsky
Manumachu, R. R., & Lastovetsky, A. (2022). On Energy Nonproportionality of CPUs and GPUs. In Proceedings - 2022 IEEE 36th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2022 (pp. 34-44). doi:10.1109/IPDPSW55747.2022.00015
Dr Aonghus Lawlor
Wang, Q., Tragos, E., Hurley, N., Smyth, B., Lawlor, A., & Dong, R. (2022). Entity-Enhanced Graph Convolutional Network for Accurate and Explainable Recommendation. In UMAP2022 - Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 79-88). doi:10.1145/3503252.3531316
Dr Nhien An Le Khac
Vo, A. V., Lokugam Hewage, C. N., Le Khac, N. A., Bertolotto, M., & Laefer, D. (2021). A PARALLEL ALGORITHM FOR LOCAL POINT DENSITY INDEX COMPUTATION OF LARGE POINT CLOUDS. In 3D GeoInfo 2021 Vol. VIII-4/W2-2021 (pp. 75-82). New York: ISPRS Annals. doi:10.5194/isprs-annals-VIII-4-W2-2021-75-2021
Nguyen, V. Q., Nguyen, V. H., Cao, V. L., Khac, N. -A. L., & Shone, N. (2021). A Robust PCA Feature Selection To Assist Deep Clustering Autoencoder-Based Network Anomaly Detection. In 2021 8th NAFOSTED Conference on Information and Computer Science (NICS). IEEE. doi:10.1109/nics54270.2021.9701456
Dr David Lillis
Wang, C., & Lillis, D. (2022). UCD-CS at TREC 2021 Incident Streams Track. In Thirtieth Text REtreival Conference (TREC 2021). Gaithersburg, MD, USA.
Dr Madhusanka Liyanage
Hewa, T., Kalla, A., Porambage, P., Liyanage, M., & Ylianttila, M. (2021). How DoS attacks can be mounted on Network Slice Broker and can they be mitigated using blockchain?. In IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC Vol. 2021-September (pp. 1525-1531). doi:10.1109/PIMRC50174.2021.9569375
Maksymyuk, T., Volosin, M., Gazda, J., & Liyanage, M. (2021). Blockchain-based Decentralized Service Provisioning in Local 6G Mobile Networks. In SenSys 2021 - Proceedings of the 2021 19th ACM Conference on Embedded Networked Sensor Systems (pp. 516-519). doi:10.1145/3485730.3493821
Dilanka, G., Viranga, L., Pamudith, R., Gamage, T. D., Ranaweera, P., Balapuwaduge, I. A. M., & Liyanage, M. (2022). MEC-RHA: Demonstration of Novel Service Request Handling Algorithm for MEC. In Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022. doi:10.1109/NOMS54207.2022.9789915
Hewa, T., Weerasinghe, N., Porambage, P., Liyanage, M., & Ylianttila, M. (2022). Demo: Blockchain-based Secured and Federated Slice Broker (SFSBroker). In Proceedings of the IEEE/IFIP Network Operations and Management Symposium 2022: Network and Service Management in the Era of Cloudification, Softwarization and Artificial Intelligence, NOMS 2022. doi:10.1109/NOMS54207.2022.9789764
Yadav, A. K., Misra, M., Pandey, P. K., Kaur, K., Garg, S., & Liyanage, M. (2022). LEMAP: A Lightweight EAP based Mutual Authentication Protocol for IEEE 802.11 WLAN. In IEEE International Conference on Communications Vol. 2022-May (pp. 692-697). doi:10.1109/ICC45855.2022.9839094
Wijethilaka, S., Porambage, P., De Alwis, C., & Liyanage, M. (2022). A Comprehensive Analysis on Network Slicing for Smart Hospital Applications. In Proceedings - IEEE Consumer Communications and Networking Conference, CCNC (pp. 276-279). doi:10.1109/CCNC49033.2022.9700535
Dilanka, G., Viranga, L., Pamudith, R., Gamage, T. D., Ranaweera, P., Balapuwaduge, I. A. M., & Liyanage, M. (2022). A Novel Request Handler Algorithm for Multi-access Edge Computing Platforms in 5G. In Proceedings - IEEE Consumer Communications and Networking Conference, CCNC (pp. 126-131). doi:10.1109/CCNC49033.2022.9700585
Siriwardhana, Y., Porambage, P., Liyanage, M., & Ylianttila, M. (2022). Robust and Resilient Federated Learning for Securing Future Networks. In 2022 Joint European Conference on Networks and Communications and 6G Summit, EuCNC/6G Summit 2022 (pp. 351-356). doi:10.1109/EuCNC/6GSummit54941.2022.9815812
Jayasinghe, S., Siriwardhana, Y., Porambage, P., Liyanage, M., & Ylianttila, M. (2022). Federated Learning based Anomaly Detection as an Enabler for Securing Network and Service Management Automation in Beyond 5G Networks. In 2022 Joint European Conference on Networks and Communications and 6G Summit, EuCNC/6G Summit 2022 (pp. 345-350). doi:10.1109/EuCNC/6GSummit54941.2022.9815754
De Silva, R., Siriwardhana, Y., Samarasinghe, T., Liyanage, M., & Ylianttila, M. (2022). Deployment Options of 5G Network Slicing for Smart Healthcare. In Proceedings - IEEE Consumer Communications and Networking Conference, CCNC (pp. 749-750). doi:10.1109/CCNC49033.2022.9700516
Assoc Professor Brian Mac Namee
Mahon, J., Quille, K., Mac Namee, B., & Becker, B. A. (2022). A Novel Machine Learning and Artificial Intelligence Course for Secondary School Students. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education V.2 (pp. 1155). doi:10.1145/3478432.3499073
Hagos, M. T., Killeen, R. P., Curran, K. M., & Mac Namee, B. (2022). Interpretable Identification of Mild Cognitive Impairment Progression Using Stereotactic Surface Projections. In Frontiers in Artificial Intelligence and Applications Vol. 351 (pp. 153-156). doi:10.3233/FAIA220074
Professor Eleni Mangina
Bampoulas, A., Pallonetto, F., Mangina, E., & P. Finn, D. (2021). A machine learning-based methodology for harnessing the energy flexibility potential of residential buildings. In Building Simulation Conference Proceedings. KU Leuven. doi:10.26868/25222708.2021.30420
Kathirgamanathan, A., Mangina, E., & P. Finn, D. (2021). Comparison of data-driven model-based and model-free control approaches for unlocking building energy flexibility. In Building Simulation Conference Proceedings. KU Leuven. doi:10.26868/25222708.2021.30740
Shamsi, M. H., Ali, U., Mangina, E., & O'Donnell, J. (2021). Assessing the effect of network order on epistemic uncertainty quantification for reduced-order grey-box energy models. In Building Simulation Conference Proceedings. KU Leuven. doi:10.26868/25222708.2021.30178
Tiede, J., Grafe, S., & Mangina, E. (2022). Teachers' Attitudes and Technology Acceptance Towards AR Apps for Teaching and Learning. In Proceedings of 2022 8th International Conference of the Immersive Learning Research Network, iLRN 2022. doi:10.23919/iLRN55037.2022.9815918
Thanyadit, S., Heintz, M., L Law, E., & Mangina, E. (2022). How easy is it to eXtend Reality? A Usability Study of Authoring Toolkits. In Human Interaction and Emerging Technologies (IHIET 2022): Artificial Intelligence and Future Applications. AHFE International. doi:10.54941/ahfe1002707
Dr Ravi Manumachu
Manumachu, R. R., & Lastovetsky, A. (2022). On Energy Nonproportionality of CPUs and GPUs. In Proceedings - 2022 IEEE 36th International Parallel and Distributed Processing Symposium Workshops, IPDPSW 2022 (pp. 34-44). doi:10.1109/IPDPSW55747.2022.00015
Dr Gavin McArdle
Hafeez, T., & McArdle, G. (2021). Using Dynamic Perceptually Important Points for Data Reduction in IoT. In ACM International Conference Proceeding Series (pp. 33-39). doi:10.1145/3494322.3494327
Mattos, A., Bertolotto, M., & McArdle, G. (2022). Mapping Slums with Deep Learning Feature Extraction. In CEUR Workshop Proceedings Vol. 3207 (pp. 27-32).
Burse, R., Bertolotto, M., & Mcardle, G. (2022). A Novel Atomic Annotator for Quality Assurance of Biomedical Ontologies. In Proceedings of the 15th International Joint Conference on Biomedical Engineering Systems and Technologies. SCITEPRESS - Science and Technology Publications. doi:10.5220/0010782500003123
Rabiei-Dastjerdi, H., McArdle, G., & Aghajani, M. A. (2022). User-generated data in cultural mapping: Analyzing google point of interest reviews in dublin. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. 5 (pp. 107-112). doi:10.5194/isprs-Annals-V-4-2022-107-2022
Dr Vivek Nallur
Nallur, V., & Ramanayake, R. (2021). A Computational Architecture for a Pro-Social Rule Bending Agent. In International Workshop on Computational Machine Ethics. Online. doi:10.5281/zenodo.6470437
Assoc Professor Mel Ó Cinnéide
Bree, D. C., & Cinneide, M. O. (2022). Removing Decorator to Improve Energy Efficiency. In Proceedings - 2022 IEEE International Conference on Software Analysis, Evolution and Reengineering, SANER 2022 (pp. 902-912). doi:10.1109/SANER53432.2022.00108
Dr Michael O'Grady
Xu, J., Bermeo, N. V., O'Grady, M., & O'Hare, G. M. P. (2022). Autonomous Sensing at the Edge. In 2022 IEEE 19th International Conference on Software Architecture Companion, ICSA-C 2022 (pp. 49-54). doi:10.1109/ICSA-C54293.2022.00018
Professor Gregory O'Hare
Xu, J., Bermeo, N. V., O'Grady, M., & O'Hare, G. M. P. (2022). Autonomous Sensing at the Edge. In 2022 IEEE 19th International Conference on Software Architecture Companion, ICSA-C 2022 (pp. 49-54). doi:10.1109/ICSA-C54293.2022.00018
Zheng, M., Pan, X., Bermeo, N. V., Thomas, R. J., Coyle, D., O'Hare, G. M. P., & Campbell, A. G. (2022). STARE: Semantic Augmented Reality Decision Support in Smart Environments. In Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022 (pp. 630-631). doi:10.1109/VRW55335.2022.00166
Dr Liliana Pasquale
Pasquale, L., & Treude, C. (2022). Message from the NIER Chairs of ICSE 2022. In Proceedings - International Conference on Software Engineering (pp. x). doi:10.1109/ICSE-NIER55298.2022.9793512
Ntafloukas, K., McCrum, D., & Pasquale, L. (2022). An overview of threat sources, vulnerabilities and physical impact assessment of an IoT enabled transportation infrastructure. In Civil Engineering Research Association of Ireland Conference. Dublin, Ireland.
Ntafloukas, K., McCrum, D., & Pasquale, L. (2022). A risk assessment approach for IoT enabled transportation infrastructure subjected to cyber-physical attacks. In The 32nd European Safety and Reliability Conference (ESREL 2022). Dublin, Ireland.
Dr Muhammad Salman Pathan
Pathan, M. S., Wu, J., Lee, Y. H., Yan, J., & Dev, S. (2021). Analyzing the Impact of Meteorological Parameters on Rainfall Prediction. In Proc. IEEE AP-S Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting.
Wang, H., Pathan, M. S., Lee, Y. H., & Dev, S. (2021). Day-ahead Forecasts of Air Temperature. In Proc. IEEE AP-S Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting.
Dr Seán Russell
Russell, S. (2022). Automated Code Tracing Exercises for CS1. In ACM International Conference Proceeding Series (pp. 13-16). doi:10.1145/3498343.3498347
Alaofi, S., & Russell, S. (2022). A Validated Computer Terminology Test for Predicting Non-native English-speaking CS1 Students’ Academic Performance. In ACM International Conference Proceeding Series (pp. 133-142). doi:10.1145/3511861.3511876
Caton, S., Russell, S., & Becker, B. A. (2022). What Fails Once, Fails Again: Common Repeated Errors in Introductory Programming Automated Assessments. In SIGCSE 2022 - Proceedings of the 53rd ACM Technical Symposium on Computer Science Education Vol. 1 (pp. 955-961). doi:10.1145/3478431.3499419
Blanchard, J., Hott, J. R., Berry, V., Carroll, R., Edmison, B., Glassey, R., et al. (2022). Leveraging Community Software in CS Education to Avoid Reinventing the Wheel. In Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE Vol. 2 (pp. 580-581). doi:10.1145/3502717.3532169
Dr Mohamed Saadeldin
Albert, P., Saadeldin, M., Narayanan, B., Namee, B. M., Hennessy, D., O'Connor, N. E., & McGuinness, K. (2022). Unsupervised domain adaptation and super resolution on drone images for autonomous dry herbage biomass estimation. In IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops Vol. 2022-June (pp. 1635-1645). doi:10.1109/CVPRW56347.2022.00170
Dr Takfarinas Saber
Tao, N., Ventresque, A., & Saber, T. (2022). Multi-objective Grammar-guided Genetic Programming with Code Similarity Measurement for Program Synthesis. In 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. doi:10.1109/CEC55065.2022.9870312
Professor Barry Smyth
Cunningham, E., Smyth, B., & Greene, D. (2022). Navigating Multidisciplinary Research Using Field of Study Networks. In Studies in Computational Intelligence Vol. 1015 (pp. 104-115). doi:10.1007/978-3-030-93409-5_10
Yang, L., Dong, R., Smyth, B., Jiazheng, L., & Zhang, Y. (2022). NumHTML: Numeric-Oriented Hierarchical Transformer Model for Multi-Task Financial Forecasting. In https://aaai-2022.virtualchair.net/papers.html?filter=keywords. Virtual: AAAI Press.
Wang, Q., Tragos, E., Hurley, N., Smyth, B., Lawlor, A., & Dong, R. (2022). Entity-Enhanced Graph Convolutional Network for Accurate and Explainable Recommendation. In UMAP2022 - Proceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization (pp. 79-88). doi:10.1145/3503252.3531316
Dr Nestor Velasco Bermeo
Zheng, M., Bermeo, N. V., & Campbell, A. G. (2022). Augmented Reality In-Field Observation Creation and Visualization in Underperforming Areas. In Proceedings - 2022 IEEE Conference on Virtual Reality and 3D User Interfaces Abstracts and Workshops, VRW 2022 (pp. 852-853). doi:10.1109/VRW55335.2022.00277
Xu, J., Bermeo, N. V., O'Grady, M., & O'Hare, G. M. P. (2022). Autonomous Sensing at the Edge. In 2022 IEEE 19th International Conference on Software Architecture Companion, ICSA-C 2022 (pp. 49-54). doi:10.1109/ICSA-C54293.2022.00018
Dr Anthony Ventresque
Laurent, T., Gaffney, S., & Ventresque, A. (2022). Re-visiting the coupling between mutants and real faults with Defects4J 2.0. In Proceedings - 2022 IEEE 14th International Conference on Software Testing, Verification and Validation Workshops, ICSTW 2022 (pp. 189-198). doi:10.1109/ICSTW55395.2022.00042
Tao, N., Ventresque, A., & Saber, T. (2022). Multi-objective Grammar-guided Genetic Programming with Code Similarity Measurement for Program Synthesis. In 2022 IEEE Congress on Evolutionary Computation, CEC 2022 - Conference Proceedings. doi:10.1109/CEC55065.2022.9870312
Birhane, A., Ruane, E., Laurent, T., S. Brown, M., Flowers, J., Ventresque, A., & L. Dancy, C. (2022). The Forgotten Margins of AI Ethics. In ACM International Conference Proceeding Series (pp. 948-958). doi:10.1145/3531146.3533157
Ventresque, A., Rushe, E., Holmes, R., & Fowley, F. (2022). Improving Signer Independent Sign Language Recognition for Low Resource Languages. In International Workshop on Sign Language Translation and Avatar Technology. Marseille, France. Retrieved from http://www.lrec-conf.org/
Murphy, A., Laurent, T., & Ventresque, A. (2022). The case for grammatical evolution in test generation. In GECCO 2022 Companion - Proceedings of the 2022 Genetic and Evolutionary Computation Conference (pp. 1946-1947). doi:10.1145/3520304.3534042
Dr Anh Vu Vo
Truong-Hong, L., Jia, F., Che, E., Emamgholian, S., Laefer, D., & Vo, A. V. (2021). Preface: 3D GeoInfo 2021. In International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives Vol. 46 (pp. 1-4). doi:10.5194/isprs-archives-XLVI-4-W4-2021-1-2021
Vo, A. V., Lokugam Hewage, C. N., Le Khac, N. A., Bertolotto, M., & Laefer, D. (2021). A PARALLEL ALGORITHM FOR LOCAL POINT DENSITY INDEX COMPUTATION OF LARGE POINT CLOUDS. In 3D GeoInfo 2021 Vol. VIII-4/W2-2021 (pp. 75-82). New York: ISPRS Annals. doi:10.5194/isprs-annals-VIII-4-W2-2021-75-2021

Edited Book

Assoc Professor Fred Cummins
Kauffman, L. H., Cummins, F., Dible, R., Conrad, L., Elisbury, G., Crompton, A., & Grote, F. (2022). Laws of Form: A Fiftieth Anniversary.
Dr Madhusanka Liyanage
Tafazolli, R., Wang, C. -L., Chatzimisios, P., & Liyanage, M. (Eds.) (2021). The Wiley 5G REF: Security. United Kingdom: Wiley.

Journal article

Dr Nima Afraz
Afraz, N. (2021). Techno-economics of Optical Access Network Sharing. doi:10.31237/osf.io/gqhrc
Afraz, N., & Ruffini, M. (2022). Trusted distributed marketplace for virtual passive optical network sharing. Journal of Optical Communications and Networking, 14(5), B22-B29. doi:10.1364/JOCN.449363
Dr Helard Becerra
Garcia-Rudolph, A., Opisso, E., Tormos, J. M., Madai, V. I., Frey, D., Becerra, H., et al. (2021). Toward personalized web-based cognitive rehabilitation for patients with ischemic stroke: Elo rating approach. JMIR Medical Informatics, 9(11). doi:10.2196/28090
Professor Michela Bertolotto
Vo, A. V., Lokugam Hewage, C. N., Le Khac, N. A., Bertolotto, M., & Laefer, D. (2021). A PARALLEL ALGORITHM for LOCAL POINT DENSITY INDEX COMPUTATION of LARGE POINT CLOUDS. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 8(4/W2-2021), 75-82. doi:10.5194/isprs-annals-VIII-4-W2-2021-75-2021
Mubarak, M., Tahir, A., Waqar, F., Haneef, I., McArdle, G., Bertolotto, M., & Saeed, M. T. (2022). A Map-Based Recommendation System and House Price Prediction Model for Real Estate. ISPRS International Journal of Geo-Information, 11(3). doi:10.3390/ijgi11030178
Assoc Professor Chris Bleakley
Rasti, S., Bleakley, C. J., Holden, N. M., Whetton, R., Langton, D., & O'Hare, G. (2022). A survey of high resolution image processing techniques for cereal crop growth monitoring. Information Processing in Agriculture, 9(2), 300-315. doi:10.1016/j.inpa.2021.02.005
Dr Oisin Boydell
Pérez-Carabaza, S., Boydell, O., & O'Connell, J. (2021). Habitat classification using convolutional neural networks and multitemporal multispectral aerial imagery. Journal of Applied Remote Sensing, 15(4). doi:10.1117/1.JRS.15.042406

Dr Rob Brennan
Trestian, R., Xie, G., Lohar, P., Celeste, E., Bendechache, M., Brennan, R., et al. (2021). Privacy in a Time of COVID-19: How Concerned Are You?. IEEE Security and Privacy, 19(5), 26-35. doi:10.1109/MSEC.2021.3092607
McDonald, N., McKenna, L., Vining, R., Doyle, B., Liang, J., Ward, M. E., et al. (2021). Evaluation of an access-risk-knowledge (Ark) platform for governance of risk and change in complex socio-technical systems. International Journal of Environmental Research and Public Health, 18(23). doi:10.3390/ijerph182312572
Basereh, M., Caputo, A., & Brennan, R. (2022). AccTEF: A Transparency and Accountability Evaluation Framework for Ontology-Based Systems. International Journal of Semantic Computing, 16(1), 5-27. doi:10.1142/S1793351X22400013
Kumar, T., Turab, M., Talpur, S., Brennan, R., & Bendechache, M. (2022). Forged Character Detection Datasets: Passports, Driving Licences and Visa Stickers. International Journal of Artificial Intelligence & Applications, 13(02), 21-35. doi:10.5121/ijaia.2022.13202
Ryan, P., & Brennan, R. (2022). Support for Enhanced GDPR Accountability with the Common Semantic Model for ROPA (CSM-ROPA). SN Computer Science, 3(3). doi:10.1007/s42979-022-01099-9
Ryan, P., Brennan, R., & Pandit, H. J. (2022). DPCat: Specification for an Interoperable and Machine-Readable Data Processing Catalogue Based on GDPR. Information (Switzerland), 13(5). doi:10.3390/info13050244
Dr Igor Brigadir
Diaz-Aviles, E., Orellana-Rodriguez, C., Brigadir, I., & Narayanan Kutty, R. (2021). NU:BRIEF-A privacy-aware newsleter personalization engine for publishers. RecSys 2021 - 15th ACM Conference on Recommender Systems, 764-767. doi:10.1145/3460231.3478884
Dr Abey Campbell
Iqbal, M. Z., & Campbell, A. G. (2021). From luxury to necessity: Progress of touchless interaction technology. Technology in Society, 67. doi:10.1016/j.techsoc.2021.101796
McNicholl, B., Lee, Y. H., Campbell, A. G., & Dev, S. (2022). Evaluating the Reliability of Air Temperature from ERA5 Reanalysis Data. IEEE Geoscience and Remote Sensing Letters, 19. doi:10.1109/LGRS.2021.3137643
Zheng, M., Pan, X., Bermeo, N. V., Thomas, R. J., Coyle, D., O'Hare, G. M. P., & Campbell, A. G. (2022). STARE: Augmented Reality Data Visualization for Explainable Decision Support in Smart Environments. IEEE Access, 10, 29543-29557. doi:10.1109/ACCESS.2022.3156697
Dr Simon Caton
Caton, S., Malisetty, S., & Haas, C. (2022). Impact of Imputation Strategies on Fairness in Machine Learning. Journal of Artificial Intelligence Research, 74, 1011-1035. doi:10.1613/jair.1.13197
Hall, M., Afzali, M. F., Krause, M., & Caton, S. (2022). What Quality Control Mechanisms do We Need for High-Quality Crowd Work?. IEEE Access, 10, 99709-99723. doi:10.1109/ACCESS.2022.3207292
Kilroy, D., Healy, G., & Caton, S. (2022). Using Machine Learning to Improve Lead Times in the Identification of Emerging Customer Needs. IEEE Access, 10, 37774-37795. doi:10.1109/ACCESS.2022.3165043
Dr Dimitris Chatzopoulos
Bermejo Fernandez, C., Chatzopoulos, D., Papadopoulos, D., & Hui, P. (2021). This Website Uses Nudging: MTurk Workers' Behaviour on Cookie Consent Notices. Proceedings of the ACM on Human-Computer Interaction, 5(CSCW2). doi:10.1145/3476087
Shatilov, K., Kwon, Y. D., Lee, L. H., Chatzopoulos, D., & Hui, P. (2022). MyoKey: Inertial Motion Sensing and Gesture-based QWERTY Keyboard for Extended Realities. IEEE Transactions on Mobile Computing. doi:10.1109/TMC.2022.3156939
Chatzopoulos, D., Jain, A., Gujar, S., Faltings, B., & Hui, P. (2022). Toward Mobile Distributed Ledgers. IEEE Internet of Things Journal, 9(11), 7891-7903. doi:10.1109/JIOT.2021.3113730
Assoc Professor Rem Collier
Kalyani, Y., & Collier, R. (2021). A systematic survey on the role of cloud, fog, and edge computing combination in smart agriculture. Sensors, 21(17). doi:10.3390/s21175922
Assoc Professor Fintan Costello
Costello, F., & Watts, P. (2022). Seeing Evidence for Rationality: Commentary on Fiedler et al. (2022). Decision, 9(3), 215-217. doi:10.1037/dec0000175
Assoc Professor David Coyle
Vilaza, G. N., Coyle, D., & Bardram, J. E. (2021). Public attitudes to digital health research repositories: Cross-sectional international survey. Journal of Medical Internet Research, 23(10). doi:10.2196/31294
Khan, M. A., Smyth, B., & Coyle, D. (2021). Addressing the complexity of personalized, context-aware and health-aware food recommendations: an ensemble topic modelling based approach. Journal of Intelligent Information Systems, 57(2), 229-269. doi:10.1007/s10844-021-00639-8
Pretorius, C., & Coyle, D. (2021). Young People's Use of Digital Tools to Support Their Mental Health During Covid-19 Restrictions. Frontiers in Digital Health, 3. doi:10.3389/fdgth.2021.763876
Zheng, M., Pan, X., Bermeo, N. V., Thomas, R. J., Coyle, D., O'Hare, G. M. P., & Campbell, A. G. (2022). STARE: Augmented Reality Data Visualization for Explainable Decision Support in Smart Environments. IEEE Access, 10, 29543-29557. doi:10.1109/ACCESS.2022.3156697
Pretorius, C., McCashin, D., & Coyle, D. (2022). Supporting personal preferences and different levels of need in online help-seeking: a comparative study of help-seeking technologies for mental health. Human-Computer Interaction. doi:10.1080/07370024.2022.2077733
McCashin, D., Coyle, D., & O'Reilly, G. (2022). Pesky gNATs for children experiencing low mood and anxiety – A pragmatic randomised controlled trial of technology-assisted CBT in primary care. Internet Interventions, 27. doi:10.1016/j.invent.2021.100489
Ivanof, B. E., Terhune, D. B., Coyle, D., Gottero, M., & Moore, J. W. (2022). Examining the effect of Libet clock stimulus parameters on temporal binding. Psychological Research, 86(3), 937-951. doi:10.1007/s00426-021-01546-x
Assoc Professor Fred Cummins
Cummins, F. (2021). Language as a problem. Language Sciences, 88. doi:10.1016/j.langsci.2021.101433
Professor Pádraig Cunningham
Mahato, V., Obeidi, M. A., Brabazon, D., & Cunningham, P. (2022). Detecting voids in 3D printing using melt pool time series data. Journal of Intelligent Manufacturing, 33(3), 845-852. doi:10.1007/s10845-020-01694-8
Badiane, M., & Cunningham, P. (2022). An empirical evaluation of kernels for time series. Artificial Intelligence Review, 55(3), 1803-1820. doi:10.1007/s10462-021-10050-y
Blanzeisky, W., & Cunningham, P. (2022). Using Pareto simulated annealing to address algorithmic bias in machine learning. Knowledge Engineering Review, 37. doi:10.1017/S0269888922000029
Dr Soumyabrata Dev
Berjon, P., Nag, A., & Dev, S. (2021). Analysis of French phonetic idiosyncrasies for accent recognition. Soft Computing Letters, 3, 100018. doi:10.1016/j.socl.2021.100018
McNicholl, B., Lee, Y. H., Campbell, A. G., & Dev, S. (2022). Evaluating the Reliability of Air Temperature from ERA5 Reanalysis Data. IEEE Geoscience and Remote Sensing Letters, 19. doi:10.1109/LGRS.2021.3137643
Wu, J., Orlandi, F., O'Sullivan, D., Pisoni, E., & Dev, S. (2022). Boosting Climate Analysis with Semantically Uplifted Knowledge Graphs. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 15, 4708-4718. doi:10.1109/JSTARS.2022.3177463
Sivapalan, G., Nundy, K. K., Dev, S., Cardiff, B., & John, D. (2022). ANNet: A Lightweight Neural Network for ECG Anomaly Detection in IoT Edge Sensors. IEEE Transactions on Biomedical Circuits and Systems, 16(1), 24-35. doi:10.1109/TBCAS.2021.3137646
Akrami, N., Ziarati, K., & Dev, S. (2022). Graph-based local climate classification in Iran. International Journal of Climatology, 42(3), 1337-1353. doi:10.1002/joc.7306
Walsh, J., Othmani, A., Jain, M., & Dev, S. (2022). Using U-Net Network for Efficient Brain Tumor Segmentation in MRI Images. Healthcare Analytics.
Dr Sahraoui Dhelim
Aung, N., Zhang, W., Sultan, K., Dhelim, S., & Ai, Y. (2021). Dynamic traffic congestion pricing and electric vehicle charging management system for the internet of vehicles in smart cities. Digital Communications and Networks, 7(4), 492-504. doi:10.1016/j.dcan.2021.01.002
Cai, X., Ning, H., Dhelim, S., Zhou, R., Zhang, T., Xu, Y., & Wan, Y. (2021). Robot and its living space: A roadmap for robot development based on the view of living space. Digital Communications and Networks, 7(4), 505-517. doi:10.1016/j.dcan.2020.12.001
Dhelim, S., Ning, H., Farha, F., Chen, L., Atzori, L., & Daneshmand, M. (2021). IoT-Enabled Social Relationships Meet Artificial Social Intelligence. IEEE Internet of Things Journal, 8(24), 17817-17828. doi:10.1109/JIOT.2021.3081556
Dhelim, S., Chen, L., Aung, N., Zhang, W., & Ning, H. (2022). A hybrid personality-aware recommendation system based on personality traits and types models. Journal of Ambient Intelligence and Humanized Computing. doi:10.1007/s12652-022-04200-5
Dhelim, S., Aung, N., Kechadi, T., Ning, H., Chen, L., & Lakas, A. (2022). Trust2Vec: Large-Scale IoT Trust Management System based on Signed Network Embeddings. IEEE Internet of Things Journal. doi:10.1109/JIOT.2022.3201772
Dhelim, S., Aung, N., Bouras, M. A., Ning, H., & Cambria, E. (2022). A survey on personality-aware recommendation systems. Artificial Intelligence Review, 55(3), 2409-2454. doi:10.1007/s10462-021-10063-7
Wang, W., Ning, H., Shi, F., Dhelim, S., Zhang, W., & Chen, L. (2022). A Survey of Hybrid Human-Artificial Intelligence for Social Computing. IEEE Transactions on Human-Machine Systems, 52(3), 468-480. doi:10.1109/THMS.2021.3131683
Dr Ernesto Diaz-Aviles
Diaz-Aviles, E., Orellana-Rodriguez, C., Brigadir, I., & Narayanan Kutty, R. (2021). NU:BRIEF-A privacy-aware newsleter personalization engine for publishers. RecSys 2021 - 15th ACM Conference on Recommender Systems, 764-767. doi:10.1145/3460231.3478884
Dr Ruihai Dong
Liu, L., He, J., Ren, K., Lungu, J., Hou, Y., & Dong, R. (2021). An information gain-based model and an attention-based RNN for wearable human activity recognition. Entropy, 23(12). doi:10.3390/e23121635
Wang, Q., Oreilly-Morgan, D., Tragos, E. Z., Hurley, N., Smyth, B., Lawlor, A., & Dong, R. (2022). Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems. IEEE Access, 10, 71961-71972. doi:10.1109/ACCESS.2022.3188709
Dr Diego Garaialde
Garaialde, D., Cox, A. L., & Cowan, B. R. (2021). Designing gamified rewards to encourage repeated app selection: Effect of reward placement. International Journal of Human Computer Studies, 153. doi:10.1016/j.ijhcs.2021.102661
Dr Daniel Gibert
Gibert, D., Fredrikson, M., Mateu, C., Planes, J., & Le, Q. (2022). Enhancing the insertion of NOP instructions to obfuscate malware via deep reinforcement learning. Computers and Security, 113. doi:10.1016/j.cose.2021.102543
Gibert, D., Fredrikson, M., Mateu, C., Planes, J., & Le, Q. (2022). Enhancing the insertion of NOP instructions to obfuscate malware via deep reinforcement learning. Computers & Security, 113, 102543. doi:10.1016/j.cose.2021.102543
Gibert, D. (2022). PE Parser: A Python package for Portable Executable files processing[Formula presented]. Software Impacts, 13. doi:10.1016/j.simpa.2022.100365
Dr Fatemeh Golpayegani
Ghanadbashi, S., & Golpayegani, F. (2022). Using ontology to guide reinforcement learning agents in unseen situations: A traffic signal control system case study. Applied Intelligence, 52(2), 1808-1824. doi:10.1007/s10489-021-02449-5
Golpayegani, F., Gueriau, M., Laharotte, P. A., Ghanadbashi, S., Guo, J., Geraghty, J., & Wang, S. (2022). Intelligent Shared Mobility Systems: A Survey on Whole System Design Requirements, Challenges and Future Direction. IEEE Access, 10, 35302-35320. doi:10.1109/ACCESS.2022.3162848
de Carvalho, V. R., & Golpayegani, F. (2022). Satisfying user preferences in optimised ridesharing services:: A multi-agent multi-objective optimisation approach. Applied Intelligence, 52(10), 11257-11272. doi:10.1007/s10489-021-02887-1
Dr Derek Greene
Cunningham, E., Smyth, B., & Greene, D. (2021). Collaboration in the time of COVID: a scientometric analysis of multidisciplinary SARS-CoV-2 research. Humanities and Social Sciences Communications, 8(1). doi:10.1057/s41599-021-00922-7
Datta, S., Ganguly, D., Mitra, M., & Greene, D. (2022). A Relative Information Gain-based Query Performance Prediction Framework with Generated Query Variants. ACM Transactions on Information Systems.
Dr Punit Gupta
Arulprakash, A., Baalamurugan, K. M., Dhanaraj, R. K., Sampath Kumar, K., Gupta, P., & Rehman, S. (2022). Aggregation Technique Using Dynamic Cross-Propagation Clustering Algorithm in Wireless Body Sensor Networks. Wireless Communications and Mobile Computing, 2022. doi:10.1155/2022/6102584
Saini, D. K., Kumar, K., & Gupta, P. (2022). Security Issues in IoT and Cloud Computing Service Models with Suggested Solutions. Security and Communication Networks, 2022. doi:10.1155/2022/4943225
Gupta, P., Bhagat, S., Saini, D. K., Kumar, A., Alahmadi, M., & Sharma, P. C. (2022). Hybrid Whale Optimization Algorithm for Resource Optimization in Cloud E-Healthcare Applications. Computers, Materials and Continua, 71(2), 5659-5676. doi:10.32604/cmc.2022.023056
Gupta, P., Kaikini, R. R., Saini, D. K., & Rahman, S. (2022). Cost-Aware Resource Optimization for Efficient Cloud Application in Smart Cities. Journal of Sensors, 2022. doi:10.1155/2022/4406809
Saini, J. S., Saini, D. K., Gupta, P., Lamba, C. S., & Rao, G. M. (2022). Cloud Computing: Legal Issues and Provision. Security and Communication Networks, 2022. doi:10.1155/2022/2288961
Mishra, D., Vajire, S. L., Saxena, S., Gupta, P., Saini, D. K., Srivastava, A. K., & Rao, G. M. (2022). GRUBin: Time-Series Forecasting-Based Efficient Garbage Monitoring and Management System for Smart Cities. Computational Intelligence and Neuroscience, 2022. doi:10.1155/2022/2538807
Nishi, F. K., Shams-E-Mofiz, M., Khan, M. M., Alsufyani, A., Bourouis, S., Gupta, P., & Saini, D. K. (2022). Electronic Healthcare Data Record Security Using Blockchain and Smart Contract. Journal of Sensors, 2022. doi:10.1155/2022/7299185
Sharma, S., Gupta, S., Gupta, D., Juneja, S., Gupta, P., Dhiman, G., & Kautish, S. (2022). Deep Learning Model for the Automatic Classification of White Blood Cells. Computational Intelligence and Neuroscience, 2022. doi:10.1155/2022/7384131
Gupta, P., Bhagat, S., & Rawat, P. (2022). Fault aware hybrid harmony search technique for optimal resource allocation in cloud. Journal of Intelligent and Fuzzy Systems, 42(4), 3677-3689. doi:10.3233/JIFS-211846
Gupta, P., Saini, D. K., Rawat, P. S., & Bhagat, S. (2022). Hybrid Big Bang-Big Crunch based resource scheduling to improve QoS in cloud infrastructure. Journal of Intelligent and Fuzzy Systems, 43(2), 1887-1895. doi:10.3233/JIFS-219290
Mundra, S., Vijay, S., Mundra, A., Gupta, P., Goyal, M. K., Kaur, M., et al. (2022). Classification of imbalanced medical data: An empirical study of machine learning approaches. Journal of Intelligent and Fuzzy Systems, 43(2), 1933-1946. doi:10.3233/JIFS-219294
Gupta, P., Mundra, S., Goyal, M. K., Khaitan, S., Dewan, R., Mundra, A., & Rajpoot, A. K. (2022). Fault aware intelligent resource allocation using Big Bang-Big Crunch trained neural network for cloud infrastructure. Journal of Intelligent and Fuzzy Systems, 43(2), 1947-1957. doi:10.3233/JIFS-219295
Gupta, P., Rawat, P., Tripathi, R. P., Mundra, A., Mundra, S., Goyal, M. K., et al. (2022). Nature inspired fault tolerant task allocation in cloud computing using neural network model. Journal of Intelligent and Fuzzy Systems, 43(2), 1959-1968. doi:10.3233/JIFS-219296
Yadav, A. K., Pateriya, R. K., Gupta, N. K., Gupta, P., Saini, D. K., & Alahmadi, M. (2022). Hybrid Machine Learning Model for Face Recognition Using SVM. Computers, Materials and Continua, 72(2), 2697-2712. doi:10.32604/cmc.2022.023052
Kumar T, S., H S, M., Mustapha, S. M. F. D. S., Gupta, P., & Tripathi, R. P. (2022). Intelligent Fault-Tolerant Mechanism for Data Centers of Cloud Infrastructure. Mathematical Problems in Engineering, 2022. doi:10.1155/2022/2379643
Kumar Saini, D., Saini, H., Gupta, P., & Mabrouk, A. B. (2022). Prediction of malicious objects using prey-predator model in Internet of Things (IoT) for smart cities. Computers and Industrial Engineering, 168. doi:10.1016/j.cie.2022.108061
Dr Alzubair Hassan
Mokhtar, H., Di, X., Zhou, Y., Hassan, A., Ma, Z., & Musa, S. (2021). Multiple-level threshold load balancing in distributed SDN controllers. Computer Networks, 198. doi:10.1016/j.comnet.2021.108369
Hassan, A., Hamza, R., Li, F., Ali, A., Bashir, M. B., Alqhtani, S. M., et al. (2022). A Secure User Authentication Protocol for Heterogeneous Mobile Environments. IEEE Access, 10, 69757-69770. doi:10.1109/ACCESS.2022.3186683
Tawfeeg, T. M., Yousif, A., Hassan, A., Alqhtani, S. M., Hamza, R., Bashir, M. B., & Ali, A. (2022). Cloud Dynamic Load Balancing and Reactive Fault Tolerance Techniques: A Systematic Literature Review (SLR). IEEE Access, 10, 71853-71873. doi:10.1109/ACCESS.2022.3188645
Yousif, A., Alqhtani, S. M., Bashir, M. B., Ali, A., Hamza, R., Hassan, A., & Tawfeeg, T. M. (2022). Greedy Firefly Algorithm for Optimizing Job Scheduling in IoT Grid Computing. Sensors, 22(3). doi:10.3390/s22030850
Ali, A., Bashir, M. B., Hassan, A., Hamza, R., Alqhtani, S. M., Tawfeeg, T. M., & Yousif, A. (2022). Design-Time Reliability Prediction Model for Component-Based Software Systems. Sensors, 22(7). doi:10.3390/s22072812
Hamza, R., Hassan, A., Ali, A., Bashir, M. B., Alqhtani, S. M., Tawfeeg, T. M., & Yousif, A. (2022). Towards Secure Big Data Analysis via Fully Homomorphic Encryption Algorithms. Entropy, 24(4). doi:10.3390/e24040519
Dr Andrew Hines
Ahmad, A., Mansoor, A. B., Barakabitze, A. A., Hines, A., Atzori, L., & Walshe, R. (2021). Supervised-learning-Based QoE Prediction of Video Streaming in Future Networks: A Tutorial with Comparative Study. IEEE Communications Magazine, 59(11), 88-94. doi:10.1109/MCOM.001.2100109
Jassim, W. A., Skoglund, J., Chinen, M., & Hines, A. (2022). Speech quality assessment with WARP-Q: From similarity to subsequence dynamic time warp cost. IET Signal Processing. doi:10.1049/sil2.12151
Ragano, A., Benetos, E., & Hines, A. (2022). Automatic Quality Assessment of Digitized and Restored Sound Archives. AES: Journal of the Audio Engineering Society, 70(4), 252-270. doi:10.17743/jaes.2022.0002
Sun, P. W., & Hines, A. (2022). Listening Effort Informed Quality of Experience Evaluation. Frontiers in Psychology, 12. doi:10.3389/fpsyg.2021.767840
Bajpai, V., Hohlfeld, O., Crowcroft, J., Keshav, S., Schulzrinne, H., Ott, J., et al. (2022). Recommendations for designing hybrid conferences. Computer Communication Review, 52(2), 63-69. doi:10.1145/3544912.3544920
Shariat Panah, D., Hines, A., McKeever, J. A., & McKeever, S. (2022). An audio processing pipeline for acquiring diagnostic quality heart sounds via mobile phone. Computers in Biology and Medicine, 145. doi:10.1016/j.compbiomed.2022.105415
Martinez, H. B., Cisek, K., García-Rudolph, A., Kelleher, J. D., & Hines, A. (2022). Understanding and Predicting Cognitive Improvement of Young Adults in Ischemic Stroke Rehabilitation Therapy. Frontiers in Neurology, 13. doi:10.3389/fneur.2022.886477
Assoc Professor Neil Hurley
Wang, Q., Oreilly-Morgan, D., Tragos, E. Z., Hurley, N., Smyth, B., Lawlor, A., & Dong, R. (2022). Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems. IEEE Access, 10, 71961-71972. doi:10.1109/ACCESS.2022.3188709
Assoc Professor Georgiana Ifrim
Frizzarin, M., Bevilacqua, A., Dhariyal, B., Domijan, K., Ferraccioli, F., Hayes, E., et al. (2021). Mid infrared spectroscopy and milk quality traits: A data analysis competition at the “International Workshop on Spectroscopy and Chemometrics 2021”. Chemometrics and Intelligent Laboratory Systems, 219. doi:10.1016/j.chemolab.2021.104442
Le Nguyen, T., & Ifrim, G. (2022). A short tutorial for time series classification and explanation with MrSQM[Formula presented]. Software Impacts, 11. doi:10.1016/j.simpa.2021.100197
Dr Anca Delia Jurcut
Zafar, S., Nazir, M., Sabah, A., & Jurcut, A. D. (2021). Securing Bio-Cyber Interface for the Internet of Bio-Nano Things using Particle Swarm Optimization and Artificial Neural Networks based parameter profiling. Computers in Biology and Medicine, 136. doi:10.1016/j.compbiomed.2021.104707
ElSayed, M. S., Le-Khac, N. A., Albahar, M. A., & Jurcut, A. (2021). A novel hybrid model for intrusion detection systems in SDNs based on CNN and a new regularization technique. Journal of Network and Computer Applications, 191. doi:10.1016/j.jnca.2021.103160
Khaloufi, H., Abouelmehdi, K., Beni-Hssane, A., Rustam, F., Jurcut, A. D., Lee, E., & Ashraf, I. (2021). Deep learning based early detection framework for preliminary diagnosis of covid-19 via onboard smartphone sensors. Sensors, 21(20). doi:10.3390/s21206853
Ali, A., Pasha, M. F., Ali, J., Fang, O. H., Masud, M., Jurcut, A. D., & Alzain, M. A. (2022). Deep Learning Based Homomorphic Secure Search-Able Encryption for Keyword Search in Blockchain Healthcare System: A Novel Approach to Cryptography. Sensors, 22(2). doi:10.3390/s22020528
Albahar, M. A., Elsayed, M. S., & Jurcut, A. (2022). A Modified ResNeXt for Android Malware Identification and Classification. Computational Intelligence and Neuroscience, 2022. doi:10.1155/2022/8634784
Gyamfi, E., Ansere, J. A., Kamal, M., Tariq, M., & Jurcut, A. (2022). An Adaptive Network Security System for IoT-Enabled Maritime Transportation. IEEE Transactions on Intelligent Transportation Systems. doi:10.1109/TITS.2022.3159450
Ranaweera, P., de Alwis, C., Jurcut, A. D., & Liyanage, M. (2022). Realizing contact-less applications with Multi-Access Edge Computing. ICT Express. doi:10.1016/j.icte.2022.03.001
Cvitic, I., Perakovic, D., Periša, M., & Jurcut, A. D. (2022). Methodology Proposal for Proactive Detection of Network Anomalies in e-Learning System During the COVID-19 Scenario. EAI/Springer Innovations in Communication and Computing, 143-151. doi:10.1007/978-3-030-67241-6_12
Hairab, B. I., Said Elsayed, M., Jurcut, A. D., & Azer, M. A. (2022). Anomaly Detection Based on CNN and Regularization Techniques Against Zero-Day Attacks in IoT Networks. IEEE Access, 10, 98427-98440. doi:10.1109/ACCESS.2022.3206367
Gyamfi, E., & Jurcut, A. D. (2022). Novel Online Network Intrusion Detection System for Industrial IoT based on OI-SVDD and AS-ELM. IEEE Internet of Things Journal. doi:10.1109/JIOT.2022.3172393
Sayed, M. S. E., Le-Khac, N. A., Azer, M. A., & Jurcut, A. D. (2022). A Flow Based Anomaly Detection Approach with Feature Selection Method Against DDoS Attacks in SDNs. IEEE Transactions on Cognitive Communications and Networking. doi:10.1109/TCCN.2022.3186331
Shahraki, A., Abbasi, M., Taherkordi, A., & Jurcut, A. D. (2022). Active Learning for Network Traffic Classification: A Technical Study. IEEE Transactions on Cognitive Communications and Networking, 8(1), 422-439. doi:10.1109/TCCN.2021.3119062
Lohrasbinasab, I., Shahraki, A., Taherkordi, A., & Delia Jurcut, A. (2022). From statistical- to machine learning-based network traffic prediction. Transactions on Emerging Telecommunications Technologies, 33(4). doi:10.1002/ett.4394
Shahraki, A., Abbasi, M., Taherkordi, A., & Jurcut, A. D. (2022). A comparative study on online machine learning techniques for network traffic streams analysis. Computer Networks, 207. doi:10.1016/j.comnet.2022.108836
Gyamfi, E., & Jurcut, A. (2022). Intrusion Detection in Internet of Things Systems: A Review on Design Approaches Leveraging Multi-Access Edge Computing, Machine Learning, and Datasets. Sensors, 22(10). doi:10.3390/s22103744
Mokhtar, B. I., Jurcut, A. D., ElSayed, M. S., & Azer, M. A. (2022). Active Directory Attacks—Steps, Types, and Signatures. Electronics (Switzerland), 11(16). doi:10.3390/electronics11162629
Professor Mark Keane
Kenny, E. M., & Keane, M. T. (2021). Explaining Deep Learning using examples: Optimal feature weighting methods for twin systems using post-hoc, explanation-by-example in XAI. Knowledge-Based Systems, 233. doi:10.1016/j.knosys.2021.107530
Riaboff, L., Shalloo, L., Smeaton, A. F., Couvreur, S., Madouasse, A., & Keane, M. T. (2022). Predicting livestock behaviour using accelerometers: A systematic review of processing techniques for ruminant behaviour prediction from raw accelerometer data. Computers and Electronics in Agriculture, 192. doi:10.1016/j.compag.2021.106610
Quinn, M. S., & Keane, M. T. (2022). Factors affecting “expectations of the unexpected”: The impact of controllability & valence on unexpected outcomes. Cognition, 225. doi:10.1016/j.cognition.2022.105142
Professor Mohand Tahar Kechadi
Jennings, M. R., Turner, C., Bond, R. R., Kennedy, A., Thantilage, R., Kechadi, M. T., et al. (2021). Code-free cloud computing service to facilitate rapid biomedical digital signal processing and algorithm development. Computer Methods and Programs in Biomedicine, 211. doi:10.1016/j.cmpb.2021.106398
Fehis, S., Nouali, O., & Kechadi, T. (2021). Secure encryption key management as a SecaaS based on Chinese wall security policy. Journal of Information Security and Applications, 63. doi:10.1016/j.jisa.2021.102975
Dhelim, S., Aung, N., Kechadi, T., Ning, H., Chen, L., & Lakas, A. (2022). Trust2Vec: Large-Scale IoT Trust Management System based on Signed Network Embeddings. IEEE Internet of Things Journal. doi:10.1109/JIOT.2022.3201772
Akilal, A., & Kechadi, M. T. (2022). An improved forensic-by-design framework for cloud computing with systems engineering standard compliance. Forensic Science International: Digital Investigation, 40. doi:10.1016/j.fsidi.2021.301315
Shahid, A., Bazargani, M. H., Banahan, P., Namee, B. M., Kechadi, T., Treacy, C., et al. (2022). A Two-Stage De-Identification Process for Privacy-Preserving Medical Image Analysis. Healthcare (Switzerland), 10(5). doi:10.3390/healthcare10050755
Ngo, Q. H., Kechadi, T., & Le-Khac, N. A. (2022). Knowledge representation in digital agriculture: A step towards standardised model. Computers and Electronics in Agriculture, 199. doi:10.1016/j.compag.2022.107127
Assoc Professor Alexey Lastovetsky
Khaleghzadeh, H., Reddy Manumachu, R., & Lastovetsky, A. (2022). Efficient exact algorithms for continuous bi-objective performance-energy optimization of applications with linear energy and monotonically increasing performance profiles on heterogeneous high performance computing platforms. Concurrency and Computation: Practice and Experience. doi:10.1002/cpe.7285
Nuriyev, E., Rico-Gallego, J. A., & Lastovetsky, A. (2022). Model-based selection of optimal MPI broadcast algorithms for multi-core clusters. Journal of Parallel and Distributed Computing, 165, 1-16. doi:10.1016/j.jpdc.2022.03.012
Dr Aonghus Lawlor
Smyth, B., & Lawlor, A. (2021). Longer Disciplined Tapers Improve Marathon Performance for Recreational Runners. Frontiers in Sports and Active Living, 3. doi:10.3389/fspor.2021.735220
Kelly, B. S., Judge, C., Bollard, S. M., Clifford, S. M., Healy, G. M., Aziz, A., et al. (2022). Correction to: Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE) (European Radiology, (2022), 10.1007/s00330-022-08784-6). European Radiology. doi:10.1007/s00330-022-08832-1
Kelly, B. S., Judge, C., Bollard, S. M., Clifford, S. M., Healy, G. M., Aziz, A., et al. (2022). Radiology artificial intelligence: a systematic review and evaluation of methods (RAISE). European Radiology. doi:10.1007/s00330-022-08784-6
Wang, Q., Oreilly-Morgan, D., Tragos, E. Z., Hurley, N., Smyth, B., Lawlor, A., & Dong, R. (2022). Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems. IEEE Access, 10, 71961-71972. doi:10.1109/ACCESS.2022.3188709
Dr Quan Le
Le, Q., Miralles-Pechuán, L., Sayakkara, A., Le-Khac, N. A., & Scanlon, M. (2021). Identifying Internet of Things software activities using deep learning-based electromagnetic side-channel analysis. Forensic Science International: Digital Investigation, 39. doi:10.1016/j.fsidi.2021.301308
Gibert, D., Fredrikson, M., Mateu, C., Planes, J., & Le, Q. (2022). Enhancing the insertion of NOP instructions to obfuscate malware via deep reinforcement learning. Computers and Security, 113. doi:10.1016/j.cose.2021.102543
Dr Nhien An Le Khac
Wijnberg, D., & Le-Khac, N. A. (2021). Identifying interception possibilities for WhatsApp communication. Forensic Science International: Digital Investigation, 38. doi:10.1016/j.fsidi.2021.301132
ElSayed, M. S., Le-Khac, N. A., Albahar, M. A., & Jurcut, A. (2021). A novel hybrid model for intrusion detection systems in SDNs based on CNN and a new regularization technique. Journal of Network and Computer Applications, 191. doi:10.1016/j.jnca.2021.103160
Vo, A. V., Lokugam Hewage, C. N., Le Khac, N. A., Bertolotto, M., & Laefer, D. (2021). A PARALLEL ALGORITHM for LOCAL POINT DENSITY INDEX COMPUTATION of LARGE POINT CLOUDS. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 8(4/W2-2021), 75-82. doi:10.5194/isprs-annals-VIII-4-W2-2021-75-2021
Jennings, M. R., Turner, C., Bond, R. R., Kennedy, A., Thantilage, R., Kechadi, M. T., et al. (2021). Code-free cloud computing service to facilitate rapid biomedical digital signal processing and algorithm development. Computer Methods and Programs in Biomedicine, 211. doi:10.1016/j.cmpb.2021.106398
Le, Q., Miralles-Pechuán, L., Sayakkara, A., Le-Khac, N. A., & Scanlon, M. (2021). Identifying Internet of Things software activities using deep learning-based electromagnetic side-channel analysis. Forensic Science International: Digital Investigation, 39. doi:10.1016/j.fsidi.2021.301308
Sayed, M. S. E., Le-Khac, N. A., Azer, M. A., & Jurcut, A. D. (2022). A Flow Based Anomaly Detection Approach with Feature Selection Method Against DDoS Attacks in SDNs. IEEE Transactions on Cognitive Communications and Networking. doi:10.1109/TCCN.2022.3186331
Khalid Alabdulsalam, S., Duong, T. Q., Raymond Choo, K. -K., & Le-Khac, N. -A. (2022). An efficient IoT forensic approach for the evidence acquisition and analysis based on network link. Logic Journal of the IGPL. doi:10.1093/jigpal/jzac012
Ngo, Q. H., Kechadi, T., & Le-Khac, N. A. (2022). Knowledge representation in digital agriculture: A step towards standardised model. Computers and Electronics in Agriculture, 199. doi:10.1016/j.compag.2022.107127
Dr David Lillis
Zhang, G., Nulty, P., & Lillis, D. (2022). Enhancing Legal Argument Mining with Domain Pre-training and Neural Networks. Journal of Data Mining & Digital Humanities, NLP4DH. doi:10.46298/jdmdh.9147

Dr Madhusanka Liyanage
Gaur, K., Kalla, A., Grover, J., Borhani, M., Gurtov, A., & Liyanage, M. (2021). A Survey of Virtual Private LAN Services (VPLS): Past, Present and Future. Computer Networks, 196. doi:10.1016/j.comnet.2021.108245
Moremada, C., Sandeepa, C., Dissanayaka, N., Gamage, T., & Liyanage, M. (2021). Energy efficient contact tracing and social interaction based patient prediction system for COVID-19 pandemic. Journal of Communications and Networks, 23(5), 390-407. doi:10.23919/jcn.2021.000037
Yapa, C., de Alwis, C., Liyanage, M., & Ekanayake, J. (2021). Survey on blockchain for future smart grids: Technical aspects, applications, integration challenges and future research. Energy Reports, 7, 6530-6564. doi:10.1016/j.egyr.2021.09.112
Hewa, T. M., Kovacevic, I., Porambage, P., Weerasinghe, N., Liyanage, M., Harjula, E., & Ylianttila, M. (2022). Blockchain-based Network Slice Broker to Facilitate Factory-as-a-Service. IEEE Transactions on Industrial Informatics. doi:10.1109/TII.2022.3173928
Yadav, A. K., Misra, M., Pandey, P. K., & Liyanage, M. (2022). An EAP-Based Mutual Authentication Protocol for WLAN connected IoT devices. IEEE Transactions on Industrial Informatics. doi:10.1109/TII.2022.3194956
Kalla, A., De Alwis, C., Gur, G., Gochhayat, S. P., Liyanage, M., & Porambage, P. (2022). Emerging Directions for Blockchainized 6G. IEEE Consumer Electronics Magazine. doi:10.1109/MCE.2022.3164530
Ding, A. Y., Peltonen, E., Meuser, T., Aral, A., Becker, C., Dustdar, S., et al. (2022). Roadmap for edge AI: A Dagstuhl Perspective. Computer Communication Review, 52(1), 28-33. doi:10.1145/3523230.3523235
Gur, G., Kalla, A., De Alwis, C., Pham, Q. V., Ngo, K. H., Liyanage, M., & Porambage, P. (2022). Integration of ICN and MEC in 5G and Beyond Networks: Mutual Benefits, Use Cases, Challenges, Standardization, and Future Research. IEEE Open Journal of the Communications Society, 3, 1382-1412. doi:10.1109/OJCOMS.2022.3195125
Saputhanthri, A., De Alwis, C., & Liyanage, M. (2022). Survey on Blockchain-based IoT Payment and Marketplaces. IEEE Access. doi:10.1109/ACCESS.2022.3208688
Maksymyuk, T., Gazda, J., Bugar, G., Gazda, V., Liyanage, M., & Dohler, M. (2022). Blockchain-Empowered Service Management for the Decentralized Metaverse of Things. IEEE Access, 10, 99025-99037. doi:10.1109/ACCESS.2022.3205739
Ranaweera, P., de Alwis, C., Jurcut, A. D., & Liyanage, M. (2022). Realizing contact-less applications with Multi-Access Edge Computing. ICT Express. doi:10.1016/j.icte.2022.03.001
Ding, A. Y., Peltonen, E., Meuser, T., Aral, A., Becker, C., Dustdar, S., et al. (2022). Roadmap for Edge AI: A Dagstuhl Perspective. ACM SIGCOMM COMPUTER COMMUNICATION REVIEW, 52(1), 28-33.
Maddikunta, P. K. R., Pham, Q. V., B, P., Deepa, N., Dev, K., Gadekallu, T. R., et al. (2022). Industry 5.0: A survey on enabling technologies and potential applications. Journal of Industrial Information Integration, 26. doi:10.1016/j.jii.2021.100257
Gaba, G. S., Hedabou, M., Kumar, P., Braeken, A., Liyanage, M., & Alazab, M. (2022). Zero knowledge proofs based authenticated key agreement protocol for sustainable healthcare. Sustainable Cities and Society, 80. doi:10.1016/j.scs.2022.103766
Gadekallu, T. R., Srivastava, G., Liyanage, M., M., I., Chowdhary, C. L., Koppu, S., & Maddikunta, P. K. R. (2022). Hand gesture recognition based on a Harris Hawks optimized Convolution Neural Network. Computers and Electrical Engineering, 100. doi:10.1016/j.compeleceng.2022.107836
Liyanage, M., Pham, Q. V., Dev, K., Bhattacharya, S., Maddikunta, P. K. R., Gadekallu, T. R., & Yenduri, G. (2022). A survey on Zero touch network and Service Management (ZSM) for 5G and beyond networks. Journal of Network and Computer Applications, 203. doi:10.1016/j.jnca.2022.103362
Assoc Professor Brian Mac Namee
Jing, M., Ng, K. Y., Namee, B. M., Biglarbeigi, P., Brisk, R., Bond, R., et al. (2021). COVID-19 modelling by time-varying transmission rate associated with mobility trend of driving via Apple Maps. Journal of Biomedical Informatics, 122. doi:10.1016/j.jbi.2021.103905
Pakrashi, A., & Mac Namee, B. (2021). A multi-label cascaded neural network classification algorithm for automatic training and evolution of deep cascaded architecture. Expert Systems, 38(7). doi:10.1111/exsy.12671
Miralles-Pechuán, L., Qureshi, M. A., & Namee, B. M. (2022). Real-time bidding campaigns optimization using user profile settings. Electronic Commerce Research. doi:10.1007/s10660-021-09513-9
Hossein Zadeh Bazargani, M., Pakrashi, A., & Namee, B. M. (2022). The Deep Radial Basis Function Data Descriptor (D-RBFDD) Network: A One-Class Neural Network for Anomaly Detection. IEEE Access, 10, 70645-70661. doi:10.1109/ACCESS.2022.3187961
Saadeldin, M., O'Hara, R., Zimmermann, J., Mac Namee, B., & Green, S. (2022). Using deep learning to classify grassland management intensity in ground-level photographs for more automated production of satellite land use maps. Remote Sensing Applications: Society and Environment, 26. doi:10.1016/j.rsase.2022.100741
Shahid, A., Bazargani, M. H., Banahan, P., Namee, B. M., Kechadi, T., Treacy, C., et al. (2022). A Two-Stage De-Identification Process for Privacy-Preserving Medical Image Analysis. Healthcare (Switzerland), 10(5). doi:10.3390/healthcare10050755
Professor Eleni Mangina
Tosto, C., Hasegawa, T., Mangina, E., Chifari, A., Treacy, R., Merlo, G., & Chiazzese, G. (2021). Exploring the effect of an augmented reality literacy programme for reading and spelling difficulties for children diagnosed with ADHD. Virtual Reality, 25(3), 879-894. doi:10.1007/s10055-020-00485-z
Ali, U., Shamsi, M. H., Hoare, C., Mangina, E., & O'Donnell, J. (2021). Review of urban building energy modeling (UBEM) approaches, methods and tools using qualitative and quantitative analysis. Energy and Buildings, 246. doi:10.1016/j.enbuild.2021.111073
Kathirgamanathan, A., Mangina, E., & Finn, D. P. (2021). Development of a Soft Actor Critic deep reinforcement learning approach for harnessing energy flexibility in a Large Office building. Energy and AI, 5. doi:10.1016/j.egyai.2021.100101
Shamsi, M. H., Ali, U., Mangina, E., & O'Donnell, J. (2021). Feature assessment frameworks to evaluate reduced-order grey-box building energy models. Applied Energy, 298. doi:10.1016/j.apenergy.2021.117174
Scaradozzi, D., Cesaretti, L., Screpanti, L., & Mangina, E. (2021). Identification and Assessment of Educational Experiences: Utilizing Data Mining with Robotics. IEEE Robotics and Automation Magazine, 28(4), 103-113. doi:10.1109/MRA.2021.3108942
Pallonetto, F., Jin, C., & Mangina, E. (2022). Forecast electricity demand in commercial building with machine learning models to enable demand response programs. Energy and AI, 7. doi:10.1016/j.egyai.2021.100121
Ryan, G. V., Callaghan, S., Rafferty, A., Higgins, M. F., Mangina, E., & McAuliffe, F. (2022). Learning Outcomes of Immersive Technologies in Health Care Student Education: Systematic Review of the Literature. Journal of Medical Internet Research, 24(2). doi:10.2196/30082
Ryan, G., Callaghan, S., Rafferty, A., Murphy, J., Mangina, E., Carroll, L., & McAuliffe, F. (2022). 381 Virtual reality in midwifery education: A prospective cohort study to assess learning and understanding. European Journal of Obstetrics & Gynecology and Reproductive Biology, 270, e102. doi:10.1016/j.ejogrb.2021.11.332
Ryan, G., Rafferty, A., Murphy, J., Higgins, M., Mangina, E., & McAuliffe, F. (2022). 379. Virtual reality learning: a randomised control trial assessing medical student knowledge of fetal development. European Journal of Obstetrics & Gynecology and Reproductive Biology, 270, e43-e44. doi:10.1016/j.ejogrb.2021.11.163
Pinto, G., Kathirgamanathan, A., Mangina, E., Finn, D. P., & Capozzoli, A. (2022). Enhancing energy management in grid-interactive buildings: A comparison among cooperative and coordinated architectures. Applied Energy, 310. doi:10.1016/j.apenergy.2021.118497
Dengel, A., Iqbal, M. Z., Grafe, S., & Mangina, E. (2022). A Review on Augmented Reality Authoring Toolkits for Education. Frontiers in Virtual Reality, 3. doi:10.3389/frvir.2022.798032
Tosto, C., Matin, F., Seta, L., Chiazzese, G., Chifari, A., Arrigo, M., et al. (2022). The Potential of AR Solutions for Behavioral Learning: A Scoping Review. Computers, 11(6). doi:10.3390/computers11060087
Al-Tamimi, N., Langan, P., Bernád, V., Walsh, J., Mangina, E., & Negrão, S. (2022). Capturing crop adaptation to abiotic stress using image-based technologies. Open biology, 12(6), 210353. doi:10.1098/rsob.210353
O’Grady, M., & Mangina, E. (2022). Adoption of Responsible Research and Innovation in Citizen Observatories. Sustainability (Switzerland), 14(12). doi:10.3390/su14127379
Neale, J., Shamsi, M. H., Mangina, E., Finn, D., & O'Donnell, J. (2022). Accurate identification of influential building parameters through an integration of global sensitivity and feature selection techniques. Applied Energy, 315. doi:10.1016/j.apenergy.2022.118956
Bampoulas, A., Pallonetto, F., Mangina, E., & Finn, D. P. (2022). An ensemble learning-based framework for assessing the energy flexibility of residential buildings with multicomponent energy systems. Applied Energy, 315. doi:10.1016/j.apenergy.2022.118947
Dr Ravi Manumachu
Khaleghzadeh, H., Reddy Manumachu, R., & Lastovetsky, A. (2022). Efficient exact algorithms for continuous bi-objective performance-energy optimization of applications with linear energy and monotonically increasing performance profiles on heterogeneous high performance computing platforms. Concurrency and Computation: Practice and Experience. doi:10.1002/cpe.7285
Dr Gavin McArdle
Zarbakhsh, N., Misaghian, M. S., & McArdle, G. (2022). Human Mobility-Based Features to Analyse the Impact of COVID-19 on Power System Operation of Ireland. IEEE Open Access Journal of Power and Energy, 9, 213-225. doi:10.1109/OAJPE.2022.3155960
Rabiei-Dastjerdi, H., Amini, S., McArdle, G., & Homayouni, S. (2022). City-region or city? That is the question: modelling sprawl in Isfahan using geospatial data and technology. GeoJournal. doi:10.1007/s10708-021-10554-8
Mubarak, M., Tahir, A., Waqar, F., Haneef, I., McArdle, G., Bertolotto, M., & Saeed, M. T. (2022). A Map-Based Recommendation System and House Price Prediction Model for Real Estate. ISPRS International Journal of Geo-Information, 11(3). doi:10.3390/ijgi11030178
Rabiei-Dastjerdi, H., Mohammadi, S., Saber, M., Amini, S., & McArdle, G. (2022). Spatiotemporal Analysis of NO<inf>2</inf> Production Using TROPOMI Time-Series Images and Google Earth Engine in a Middle Eastern Country. Remote Sensing, 14(7). doi:10.3390/rs14071725
Rabiei-Dastjerdi, H., McArdle, G., & Hynes, W. (2022). Which came first, the gentrification or the Airbnb? Identifying spatial patterns of neighbourhood change using Airbnb data. Habitat International, 125. doi:10.1016/j.habitatint.2022.102582
Crisci, M., Benassi, F., Rabiei-Dastjerdi, H., & McArdle, G. (2022). Spatio-temporal variations and contextual factors of the supply of Airbnb in Rome. An initial investigation. Letters in Spatial and Resource Sciences, 15(2), 237-253. doi:10.1007/s12076-022-00302-y
Khosravi Kazazi, A., Rabiei-Dastjerdi, H., & McArdle, G. (2022). Emerging paradigm shift in urban indicators: Integration of the vertical dimension. Journal of Environmental Management, 316. doi:10.1016/j.jenvman.2022.115234
Assoc Professor Catherine Mooney
Kaleel, M., Ellinger, L., Lalor, C., Pollastri, G., & Mooney, C. (2021). SCLpred-MEM: Subcellular localization prediction of membrane proteins by deep N-to-1 convolutional neural networks. Proteins: Structure, Function and Bioinformatics, 89(10), 1233-1239. doi:10.1002/prot.26144
Wei, L., Boutouil, H., R. Gerbatin, R., Mamad, O., Heiland, M., Reschke, C. R., et al. (2021). Detection of spontaneous seizures in EEGs in multiple experimental mouse models of epilepsy. Journal of Neural Engineering, 18(5). doi:10.1088/1741-2552/ac2ca0
Antoniadi, A. M., Galvin, M., Heverin, M., Hardiman, O., & Mooney, C. (2021). Prediction of caregiver quality of life in amyotrophic lateral sclerosis using explainable machine learning. Scientific Reports, 11(1). doi:10.1038/s41598-021-91632-2
Wei, L., Ventura, S., Mathieson, S., Boylan, G., Lowery, M., & Mooney, C. (2022). Spindle-AI: Sleep Spindle Number and Duration Estimation in Infant EEG. IEEE Transactions on Biomedical Engineering, 69(1), 465-474. doi:10.1109/TBME.2021.3097815
Antoniadi, A. M., Galvin, M., Heverin, M., Wei, L., Hardiman, O., & Mooney, C. (2022). A Clinical Decision Support System for the Prediction of Quality of Life in ALS. Journal of Personalized Medicine, 12(3). doi:10.3390/jpm12030435
Professor Liam Murphy
Konjaang, J. K., Murphy, J., & Murphy, L. (2022). Energy-efficient virtual-machine mapping algorithm (EViMA) for workflow tasks with deadlines in a cloud environment. Journal of Network and Computer Applications, 203. doi:10.1016/j.jnca.2022.103400
Dr Vivek Nallur
Nallur, V., & Finlay, G. (2022). Empathetic AI for ethics-in-the-small. AI and Society. doi:10.1007/s00146-022-01466-3
Ramanayake, R., Wicke, P., & Nallur, V. (2022). Immune moral models? Pro-social rule breaking as a moral enhancement approach for ethical AI. AI and Society. doi:10.1007/s00146-022-01478-z
Ramanayake, R., Wicke, P., & Nallur, V. (2022). Immune moral models? Pro-social rule breaking as a moral enhancement approach for ethical AI. AI & SOCIETY. doi:10.1007/s00146-022-01478-z
Ramanayake, R., & Nallur, V. (2022). Pro-Social Rule Breaking as a Benchmark of Ethical Intelligence in Socio-Technical Systems. Digital Society, 1(1). doi:10.1007/s44206-022-00001-7
Duboc, L., Bahsoon, R., Alrebeish, F., Mera-Gómez, C., Nallur, V., Kazman, R., et al. (2022). Systematic Scalability Modeling of QoS-Aware Dynamic Service Composition. ACM Transactions on Autonomous and Adaptive Systems. doi:10.1145/3529162
Assoc Professor Mel Ó Cinnéide
Hamdi, O., Ouni, A., Cinnéide, M., & Mkaouer, M. W. (2021). A longitudinal study of the impact of refactoring in android applications. Information and Software Technology, 140. doi:10.1016/j.infsof.2021.106699
Dr Michael O'Grady
Torresan, C., Benito Garzón, M., O’Grady, M., Robson, T. M., Picchi, G., Panzacchi, P., et al. (2021). A new generation of sensors and monitoring tools to support climate-smart forestry practices. Canadian Journal of Forest Research, 51(12), 1751-1765. doi:10.1139/cjfr-2020-0295
O'Grady, M., O'Hare, G., Ties, S., & Williams, J. (2021). The Citizen Observatory: Enabling Next Generation Citizen Science. Business Systems Research, 12(2), 221-235. doi:10.2478/bsrj-2021-0029
O’Grady, M., & Mangina, E. (2022). Adoption of Responsible Research and Innovation in Citizen Observatories. Sustainability (Switzerland), 14(12). doi:10.3390/su14127379
Woulfe, F., Fadahunsi, K. P., O'Grady, M., Chirambo, G. B., Mawkin, M., Majeed, A., et al. (2022). Modification and Validation of an mHealth App Quality Assessment Methodology for International Use: Cross-sectional and eDelphi Studies. JMIR Formative Research, 6(8). doi:10.2196/36912
Professor Gregory O'Hare
Sala-Comorera, L., Reynolds, L. J., Martin, N. A., Pascual-Benito, M., Stephens, J. H., Nolan, T. M., et al. (2021). crAssphage as a human molecular marker to evaluate temporal and spatial variability in faecal contamination of urban marine bathing waters. Science of the Total Environment, 789. doi:10.1016/j.scitotenv.2021.147828
Gillespie, G. D., McDonnell, K. P., & O'Hare, G. M. P. (2021). Can machine learning classification methods improve the prediction of leaf wetness in North-Western Europe compared to established empirical methods?. Expert Systems with Applications, 182. doi:10.1016/j.eswa.2021.115255
O'Grady, M., O'Hare, G., Ties, S., & Williams, J. (2021). The Citizen Observatory: Enabling Next Generation Citizen Science. Business Systems Research, 12(2), 221-235. doi:10.2478/bsrj-2021-0029
Zhang, T., Cheng, Y., Peng, C., Ma, F., Zeng, D., & O'Hare, G. M. P. (2022). Optimal Scheduling Strategy for Regional Microgrid considering Large-Scale Access of Electric Vehicles. International Transactions on Electrical Energy Systems, 2022. doi:10.1155/2022/7244304
Zhang, T., Ma, F., Peng, C., Yu, Y., Yue, D., Dou, C., & O'Hare, G. M. P. (2022). A Very-Short-Term Online PV Power Prediction Model Based on RAN with Secondary Dynamic Adjustment. IEEE Transactions on Artificial Intelligence, 1. doi:10.1109/tai.2022.3179353
Lu, D., Sun, Y., Dai, Q., Li, X., Zhu, D., Du, H., et al. (2022). Msm: A method of multi-neighborhood sampling matching for entity alignment. Intelligent Automation and Soft Computing, 32(2), 1141-1151. doi:10.32604/iasc.2022.020218
Byabazaire, J., O'Hare, G., & Delaney, D. T. (2022). End-to-End Data Quality Assessment Using Trust for Data Shared IoT Deployments. IEEE Sensors Journal. doi:10.1109/JSEN.2022.3203853
Zheng, M., Pan, X., Bermeo, N. V., Thomas, R. J., Coyle, D., O'Hare, G. M. P., & Campbell, A. G. (2022). STARE: Augmented Reality Data Visualization for Explainable Decision Support in Smart Environments. IEEE Access, 10, 29543-29557. doi:10.1109/ACCESS.2022.3156697
Rasti, S., Bleakley, C. J., Holden, N. M., Whetton, R., Langton, D., & O'Hare, G. (2022). A survey of high resolution image processing techniques for cereal crop growth monitoring. Information Processing in Agriculture, 9(2), 300-315. doi:10.1016/j.inpa.2021.02.005
Dr Liliana Pasquale
Ferrari, A., Madhavji, N. H., & Pasquale, L. (2021). Requirements engineering: Foundation for software quality (REFSQ2020). Information and Software Technology, 137. doi:10.1016/j.infsof.2021.106636
Alrimawi, F., Pasquale, L., Mehta, D., Yoshioka, N., & Nuseibeh, B. (2022). Incidents are Meant for Learning, Not Repeating: Sharing Knowledge about Security Incidents in Cyber-Physical Systems. IEEE Transactions on Software Engineering, 48(1), 120-134. doi:10.1109/TSE.2020.2981310
Azzam, M., Pasquale, L., Provan, G., & Nuseibeh, B. (2022). Efficient Predictive Monitoring of Linear Time-Invariant Systems Under Stealthy Attacks. IEEE Transactions on Control Systems Technology. doi:10.1109/TCST.2022.3196809
Pasquale, L., Zippo, P., Curley, C., O'Neill, B., & Mongiello, M. (2022). Digital Age of Consent and Age Verification: Can They Protect Children?. IEEE Software, 39(3), 50-57. doi:10.1109/MS.2020.3044872
Dr Muhammad Salman Pathan
Du, Y., Li, T., Pathan, M. S., Teklehaimanot, H. K., & Yang, Z. (2022). An Effective Sarcasm Detection Approach Based on Sentimental Context and Individual Expression Habits. Cognitive Computation, 14(1), 78-90. doi:10.1007/s12559-021-09832-x
Assoc Professor Gianluca Pollastri
Kaleel, M., Ellinger, L., Lalor, C., Pollastri, G., & Mooney, C. (2021). SCLpred-MEM: Subcellular localization prediction of membrane proteins by deep N-to-1 convolutional neural networks. Proteins: Structure, Function and Bioinformatics, 89(10), 1233-1239. doi:10.1002/prot.26144
Walsh, I., Fishman, D., Garcia-Gasulla, D., Titma, T., Pollastri, G., Capriotti, E., et al. (2021). DOME: recommendations for supervised machine learning validation in biology. Nature Methods, 18(10), 1122-1127. doi:10.1038/s41592-021-01205-4
Walsh, I., Fishman, D., Garcia-Gasulla, D., Titma, T., Pollastri, G., Capriotti, E., et al. (2021). Author Correction: DOME: recommendations for supervised machine learning validation in biology (Nature Methods, (2021), 18, 10, (1122-1127), 10.1038/s41592-021-01205-4). Nature Methods, 18(11), 1409-1410. doi:10.1038/s41592-021-01304-2
Dr Abdul Rehman
Balogun, A. O., Almomani, M., Basri, S., Almomani, O., Capretz, L. F., Khan, A. A., et al. (2022). Towards the sustainability of small and medium software enterprises through the implementation of software process improvement: Empirical investigation. Journal of Software: Evolution and Process, 34(8). doi:10.1002/smr.2466
Dr Colm Ryan
De Kegel, B., Quinn, N., Thompson, N. A., Adams, D. J., & Ryan, C. J. (2021). Comprehensive prediction of robust synthetic lethality between paralog pairs in cancer cell lines. Cell Systems, 12(12), 1144-1159.e6. doi:10.1016/j.cels.2021.08.006
Dr Mohamed Saadeldin
Saadeldin, M., O'Hara, R., Zimmermann, J., Mac Namee, B., & Green, S. (2022). Using deep learning to classify grassland management intensity in ground-level photographs for more automated production of satellite land use maps. Remote Sensing Applications: Society and Environment, 26. doi:10.1016/j.rsase.2022.100741
Dr Takfarinas Saber
Sharma, N., Mangla, M., Yadav, S., Goyal, N., Singh, A., Verma, S., & Saber, T. (2021). A sequential ensemble model for photovoltaic power forecasting. Computers and Electrical Engineering, 96. doi:10.1016/j.compeleceng.2021.107484
Saber, T., Naeher, D., & De Lombaerde, P. (2022). On the Optimal Size and Composition of Customs Unions: An Evolutionary Approach. Computational Economics. doi:10.1007/s10614-022-10307-w
Assoc Professor Mark Scanlon
Du, X., Hargreaves, C., Sheppard, J., & Scanlon, M. (2021). TraceGen: User activity emulation for digital forensic test image generation. Forensic Science International: Digital Investigation, 38. doi:10.1016/j.fsidi.2021.301133
Le, Q., Miralles-Pechuán, L., Sayakkara, A., Le-Khac, N. A., & Scanlon, M. (2021). Identifying Internet of Things software activities using deep learning-based electromagnetic side-channel analysis. Forensic Science International: Digital Investigation, 39. doi:10.1016/j.fsidi.2021.301308
Kanta, A., Coisel, I., & Scanlon, M. (2022). A Novel Dictionary Generation Methodology for Contextual-Based Password Cracking. IEEE Access, 10, 59178-59188. doi:10.1109/ACCESS.2022.3179701
Rizvi, S., Scanlon, M., McGibney, J., & Sheppard, J. (2022). Application of Artificial Intelligence to Network Forensics: Survey, Challenges and Future Directions. IEEE Access. doi:10.1109/ACCESS.2022.3214506
Dr Arsalan Shahid
Lewis, D. M., & Shahid, A. (2022). Glycemic Variability Assessment in Newly Treated Exocrine Pancreatic Insufficiency With Type 1 Diabetes. Journal of Diabetes Science and Technology. doi:10.1177/19322968221108414
Shahid, A., & Lewis, D. M. (2022). Large-Scale Data Analysis for Glucose Variability Outcomes with Open-Source Automated Insulin Delivery Systems. Nutrients, 14(9). doi:10.3390/nu14091906
Shahid, A., Bazargani, M. H., Banahan, P., Namee, B. M., Kechadi, T., Treacy, C., et al. (2022). A Two-Stage De-Identification Process for Privacy-Preserving Medical Image Analysis. Healthcare (Switzerland), 10(5). doi:10.3390/healthcare10050755
Tufford, A. R., Diou, C., Lucassen, D. A., Ioakimidis, I., O'Malley, G., Alagialoglou, L., et al. (2022). Toward Systems Models for Obesity Prevention: A Big Role for Big Data.. Current developments in nutrition, 6(9), nzac123. doi:10.1093/cdn/nzac123
Professor Barry Smyth
Smyth, B., & Lawlor, A. (2021). Longer Disciplined Tapers Improve Marathon Performance for Recreational Runners. Frontiers in Sports and Active Living, 3. doi:10.3389/fspor.2021.735220
Khan, M. A., Smyth, B., & Coyle, D. (2021). Addressing the complexity of personalized, context-aware and health-aware food recommendations: an ensemble topic modelling based approach. Journal of Intelligent Information Systems, 57(2), 229-269. doi:10.1007/s10844-021-00639-8
Cunningham, E., Smyth, B., & Greene, D. (2021). Unknown Title. Humanities and Social Sciences Communications, 8(1). doi:10.1057/s41599-021-00957-w
Cunningham, E., Smyth, B., & Greene, D. (2021). Collaboration in the time of COVID: a scientometric analysis of multidisciplinary SARS-CoV-2 research. Humanities and Social Sciences Communications, 8(1). doi:10.1057/s41599-021-00922-7
Wang, Q., Oreilly-Morgan, D., Tragos, E. Z., Hurley, N., Smyth, B., Lawlor, A., & Dong, R. (2022). Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems. IEEE Access, 10, 71961-71972. doi:10.1109/ACCESS.2022.3188709
Smyth, B. (2022). The fading impact of lockdowns: A data analysis of the effectiveness of Covid-19 travel restrictions during different pandemic phases. PLoS ONE, 17(6 June). doi:10.1371/journal.pone.0269774
Mr Andres Suarez-Cetrulo
Suárez-Cetrulo, A. L., Burnham-King, L., Haughton, D., & Carbajo, R. S. (2022). Wind power forecasting using ensemble learning for day-ahead energy trading. Renewable Energy, 191, 685-698. doi:10.1016/j.renene.2022.04.032
Dr Elias Tragos
Wang, Q., Oreilly-Morgan, D., Tragos, E. Z., Hurley, N., Smyth, B., Lawlor, A., & Dong, R. (2022). Learning Domain-Independent Representations via Shared Weight Auto-Encoder for Transfer Learning in Recommender Systems. IEEE Access, 10, 71961-71972. doi:10.1109/ACCESS.2022.3188709
Dr Nestor Velasco Bermeo
Zheng, M., Pan, X., Bermeo, N. V., Thomas, R. J., Coyle, D., O'Hare, G. M. P., & Campbell, A. G. (2022). STARE: Augmented Reality Data Visualization for Explainable Decision Support in Smart Environments. IEEE Access, 10, 29543-29557. doi:10.1109/ACCESS.2022.3156697
Dr Anthony Ventresque
Pereira, J. A., Acher, M., Martin, H., Jézéquel, J. M., Botterweck, G., & Ventresque, A. (2021). Learning software configuration spaces: A systematic literature review. Journal of Systems and Software, 182. doi:10.1016/j.jss.2021.111044
Razzaq, A., Ventresque, A., Koschke, R., De Lucia, A., & Buckley, J. (2022). The Effect of Feature Characteristics on the Performance of Feature Location Techniques. IEEE Transactions on Software Engineering, 48(6), 2066-2085. doi:10.1109/TSE.2021.3049735
Laurent, T., Klikovits, S., Arcaini, P., Ishikawa, F., & Ventresque, A. (2022). Parameter Coverage for Testing of Autonomous Driving Systems Under Uncertainty. ACM Transactions on Software Engineering and Methodology. doi:10.1145/3550270
Dr Anh Vu Vo
Zhang, P., Vo, A. V., Laefer, D. F., & Porfiri, M. (2021). Integrated Evolutionary Algorithms/Computational Fluid Dynamics for Drag Reduction in Highway Design. Journal of Infrastructure Systems, 27(3). doi:10.1061/(ASCE)IS.1943-555X.0000625
Truong-Hong, L., Jia, F., Che, E., Emamgholian, S., Laefer, D., & Vo, A. V. (2021). Preface: 3D GeoInfo 2021. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 8(4/W2-2021), 2. doi:10.5194/isprs-annals-VIII-4-W2-2021-1-2021
Vo, A. V., Lokugam Hewage, C. N., Le Khac, N. A., Bertolotto, M., & Laefer, D. (2021). A PARALLEL ALGORITHM for LOCAL POINT DENSITY INDEX COMPUTATION of LARGE POINT CLOUDS. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 8(4/W2-2021), 75-82. doi:10.5194/isprs-annals-VIII-4-W2-2021-75-2021
Vo, A. V., Laefer, D. F., & Byrne, J. (2021). Optimizing urban LiDAR flight path planning using a genetic algorithm and a dual parallel computing framework. Remote Sensing, 13(21). doi:10.3390/rs13214437
Dr Shen Wang
Golpayegani, F., Gueriau, M., Laharotte, P. A., Ghanadbashi, S., Guo, J., Geraghty, J., & Wang, S. (2022). Intelligent Shared Mobility Systems: A Survey on Whole System Design Requirements, Challenges and Future Direction. IEEE Access, 10, 35302-35320. doi:10.1109/ACCESS.2022.3162848
Li, J., Li, S., Cheng, L., Liu, Q., Pei, J., & Wang, S. (2022). BSAS: A Blockchain-Based Trustworthy and Privacy-Preserving Speed Advisory System. IEEE Transactions on Vehicular Technology. doi:10.1109/TVT.2022.3189410
Dr Lina Xu
Konjaang, J. K., & Xu, L. (2021). Multi-objective workflow optimization strategy (MOWOS) for cloud computing. Journal of Cloud Computing, 10(1). doi:10.1186/s13677-020-00219-1

Preprint

Dr Sahraoui Dhelim
dhelim, S., Kechadi, T., Chen, L., Aung, N., Ning, H., & Atzori, L. (2022). Edge-enabled Metaverse: The Convergence of Metaverse and Mobile Edge Computing. doi:10.36227/techrxiv.19606954.v1
Dr Derek Greene
Cunningham, E., Smyth, B., & Greene, D. (2022). Author Multidisciplinarity and Disciplinary Roles in Field of Study Networks. doi:10.21203/rs.3.rs-1420119/v1
Professor Mohand Tahar Kechadi
dhelim, S., Kechadi, T., Chen, L., Aung, N., Ning, H., & Atzori, L. (2022). Edge-enabled Metaverse: The Convergence of Metaverse and Mobile Edge Computing. doi:10.36227/techrxiv.19606954
dhelim, S., Kechadi, T., Chen, L., Aung, N., Ning, H., & Atzori, L. (2022). Edge-enabled Metaverse: The Convergence of Metaverse and Mobile Edge Computing. doi:10.36227/techrxiv.19606954.v1
Dr Michael O'Grady
Woulfe, F., Fadahunsi, K. P., O'Grady, M., Chirambo, G. B., Mawkin, M., Majeed, A., et al. (2022). Modification and Validation of an mHealth App Quality Assessment Methodology for International Use: Cross-sectional and eDelphi studies (Preprint). doi:10.2196/preprints.36912
Dr Colm Ryan
De Kegel, B., & Ryan, C. J. (2022). Paralog dispensability shapes homozygous deletion patterns in tumor genomes. doi:10.1101/2022.06.20.496722
Professor Barry Smyth
Cunningham, E., Smyth, B., & Greene, D. (2022). Author Multidisciplinarity and Disciplinary Roles in Field of Study Networks. doi:10.21203/rs.3.rs-1420119/v1

UCD School of Computer Science

School of Computer Science - Research Publications 2021/2022

UCD School of Computer Science

School of Computer Science - Research Publications 2021/2022

Address

Research

UCD Home

Contact UCD

Useful Links