UCD School of Computer Science

School of Computer Science - Research Publications 2022/23

Below is the list of research publications for the School of Computer Science in the academic year 2022/23.

• Book
• Chapter
• Conference Paper
• Journal article
• Preprint
• Software / Code

Book

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Chapter

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Conference Paper

Byrne, A., Caffrey, I., & Le, Q. (2023). Towards a Framework for the Global Assessment of Sensitive Attribute Bias Within Binary Classification Algorithms. In CEUR Workshop Proceedings Vol. 3442.

 

Gibert, D., Planes, J., Le, Q., & Zizzo, G. (2023). A Wolf in Sheep's Clothing: Query-Free Evasion Attacks Against Machine Learning-Based Malware Detectors with Generative Adversarial Networks. In Proceedings - 8th IEEE European Symposium on Security and Privacy Workshops, Euro S and PW 2023 (pp. 415-426). doi:10.1109/EuroSPW59978.2023.00052

Assoc Professor Nhien An Le Khac

Lokugam Hewage, C. N., Vo, A. V., Bertolotto, M., Le-Khac, N. A., & Laefer, D. (2022). 4SA: OPTIMIZING SPACE FILLING CURVE BASED GRID CELL INDEXING TO SCALABLY MANAGE REMOTELY SENSED IMAGES IN KEY-VALUE DATABASES. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. 10 (pp. 143-150). doi:10.5194/isprs-annals-X-4-W3-2022-143-2022

Nicholls, J., Kuppa, A., & Le-Khac, N. A. (2023). SoK: The Next Phase of Identifying Illicit Activity in Bitcoin. In 2023 IEEE International Conference on Blockchain and Cryptocurrency, ICBC 2023. doi:10.1109/ICBC56567.2023.10174963

Vo, A., Bertolotto, M., Laefer, D., Le Khac, N. A., & Ofterdinger, U. (2023). A Big Data approach for building basement detection using airborne LiDAR data. In ISMLG 2023 - 4th International Symposium on Machine Learning and Big Data in Geoscience.

Dr David Lillis

Zhang, G., Nulty, P., & Lillis, D. (2023). Argument Mining with Graph Representation Learning. In Proceedings of the Nineteenth International Conference on Artificial Intelligence and Law. ACM. doi:10.1145/3594536.3595152

Dr Madhusanka Liyanage

Ratnayake, R., Liyanage, M., & Murphy, L. (2023). Trust Management and Bad Data Reduction in Internet of Vehicles Using Blockchain and AI. In IEEE Vehicular Technology Conference Vol. 2023-June. doi:10.1109/VTC2023-Spring57618.2023.10200207

Assoc Professor Brian Mac Namee

Lu, J., Zhu, D., Han, W., Zhao, R., Namee, B. M., & Tan, F. (2022). What Makes Pre-trained Language Models Better Zero-shot Learners?. In The 61st Annual Meeting of the Association for Computational Linguistics (ACL’23). Retrieved from http://arxiv.org/abs/2209.15206v3

 

Lu, J., Zhao, R., Namee, B. M., & Tan, F. (2022). PUnifiedNER: A Prompting-based Unified NER System for Diverse Datasets. In The 61st Annual Meeting of the Association for Computational Linguistics. Retrieved from http://arxiv.org/abs/2211.14838v2

 

Ruan, Q., Namee, B. M., & Dong, R. (2023). The Influence of Media Bias on News Recommender Systems. In UMAP 2023 - Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (pp. 301-305). doi:10.1145/3565472.3595619

Professor Eleni Mangina

Domínguez, A., Cabrero, Á., Simões, B., Chiazzese, G., Farella, M., Arrigo, M., et al. (2023). Collaborative Augmented Reality Tools for Behavioral Lessons. In Lecture Notes in Networks and Systems Vol. 633 LNNS (pp. 102-109). doi:10.1007/978-3-031-26876-2_10

Glowatz, M., & Mangina, E. (2023). "Augmenting the Learning Experience: The ALEX Implementation Framework for Higher Business Education". In 2023 International Immersive Learning Research Network Conference.

Assoc Professor Gavin McArdle

Zarbakhsh, N., & McArdle, G. (2023). Points-of-Interest from Mapillary Street-level Imagery: A Dataset For Neighborhood Analytics. In Proceedings - 2023 IEEE 39th International Conference on Data Engineering Workshops, ICDEW 2023 (pp. 154-161). doi:10.1109/ICDEW58674.2023.00030

Burse, R., Bertolotto, M., & McArdle, G. (2023). Facilitating SNOMED-CT Template Creation by Targeting Stopwords. In Proceedings of the 16th International Joint Conference on Biomedical Engineering Systems and Technologies. SCITEPRESS - Science and Technology Publications. doi:10.5220/0011660500003414

Assoc Professor Catherine Mooney

Runa, S. N., Becker, B. A., & Mooney, C. (2022). Variations in Sense of Belonging in Undergraduate Computing Students Through the COVID-19 Pandemic. In ACM International Conference Proceeding Series. doi:10.1145/3555009.3555029

Wei, L., & Mooney, C. (2023). Investigating the Need for Pediatric-Specific Machine Learning Approaches for Seizure Detection in EEG. In 2023 11th International Conference on Bioinformatics and Computational Biology, ICBCB 2023 (pp. 57-63). doi:10.1109/ICBCB57893.2023.10246719

Runa, S. N., Antoniadi, A. M., Becker, B. A., & Mooney, C. (2023). Student Sense of Belonging: The Role of Gender Identity and Minoritisation in Computing and Other Sciences. In ACM International Conference Proceeding Series (pp. 87-96). doi:10.1145/3576123.3576133

Wei, L., & Mooney, C. (2023). Transfer Learning-based Seizure Detection on Multiple Channels of Paediatric EEGs. In 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

 

Wei, L., & Mooney, C. (2023). A Machine Learning Approach for Sex and Age Classification of Paediatric EEGs. In 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Professor Liam Murphy

Ratnayake, R., Liyanage, M., & Murphy, L. (2023). Trust Management and Bad Data Reduction in Internet of Vehicles Using Blockchain and AI. In IEEE Vehicular Technology Conference Vol. 2023-June. doi:10.1109/VTC2023-Spring57618.2023.10200207

Dr Avishek Nag

Walsh, D., Dev, S., & Nag, A. (2023). Hilbert-Huang-Transform Based Features for Accent Classification of Non-Native English Speakers. In 2023 34th Irish Signals and Systems Conference, ISSC 2023. doi:10.1109/ISSC59246.2023.10162075

Dr Vivek Nallur

Nault, E., Bettosi, C. J., Baillie, L., Smith, R., Mataric, M., Nallur, V., et al. (2023). Socially Assistive Robots as Decision Makers: Transparency, Motivations, and Intentions. In Conference on Human Factors in Computing Systems - Proceedings. doi:10.1145/3544549.3573822

Nallur, V., Hines, A., & Ni Fhaolain, L. (2023). Statutory Professions in AI governance and their consequences for explainable AI. In L. Longo (Ed.), Communications in Computer and Information Science. Springer Communications in Computer and Information Science: Springer Nature. doi:10.48550/arXiv.2306.08959

Dr Arjun Pakrashi

Sadhukhan, P., Pakrashi, A., Palit, S., & Namee, B. (2023). Integrating Unsupervised Clustering and Label-Specific Oversampling to Tackle Imbalanced Multi-Label Data. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence. SCITEPRESS - Science and Technology Publications. doi:10.5220/0011901200003393

Dr Liliana Pasquale

Ntafloukas, K., Pasquale, L., Martinez-Pastor, B., & McCrum, D. P. (2023). A Vulnerability Assessment Approach for Internet of Things Enabled Transportation Networks Subjected To Cyber-Physical Attacks. In International Conference on Civil, Structural and Transportation Engineering. doi:10.11159/iccste23.172

Konstantinos, N., Pasquale, L., Martinez-Pastor, B., & McCrum, D. P. (2023). Identification of Vulnerable IoT Enabled Transportation Infrastructure into a Cyber-Physical Transportation Network. In Proceedings of the 2023 IEEE International Conference on Cyber Security and Resilience, CSR 2023 (pp. 400-405). doi:10.1109/CSR57506.2023.10224993

Onwuegbuche, F. C., Jurcut, A. D., & Pasquale, L. (2023). Enhancing Ransomware Classification with Multi-stage Feature Selection and Data Imbalance Correction. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) Vol. 13914 LNCS (pp. 285-295). doi:10.1007/978-3-031-34671-2_20

Dr Alessandro Ragano

Ullah, A., Ragano, A., & Hines, A. (2023). Improving Phoneme Recognition with Augmented Autoregressive Predictive Coding. In 2023 34th Irish Signals and Systems Conference, ISSC 2023. doi:10.1109/ISSC59246.2023.10162109

Ragano, A., Benetos, E., Chinen, M., Martinez, H. B., Reddy, C. K. A., Skoglund, J., & Hines, A. (2023). A Comparison Of Deep Learning MOS Predictors For Speech Synthesis Quality. In 2023 34th Irish Signals and Systems Conference, ISSC 2023. doi:10.1109/ISSC59246.2023.10162088

Ragano, A., Benetos, E., & Hines, A. (2023). Audio Quality Assessment of Vinyl Music Collections Using Self-Supervised Learning. In ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE. doi:10.1109/icassp49357.2023.10096274

Dr Seán Russell

Alaofi, S., & Russell, S. (2022). The Influence of Foreign Language Classroom Anxiety on Academic Performance in English-based CS1 Courses. In ACM International Conference Proceeding Series. doi:10.1145/3555009.3555020

Blanchard, J., Hott, J. R., Berry, V., Carroll, R., Edmison, B., Glassey, R., et al. (2022). Stop Reinventing the Wheel! Promoting Community Software in Computing Education. In Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE (pp. 261-292). doi:10.1145/3571785.3574129

Russell, S., Alaofi, S., & Alshaigy, B. (2023). Translate Together: Managed Translation and Peer-Review. In Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE Vol. 2 (pp. 595-596). doi:10.1145/3587103.3594160

Russell, S., & Alshaigy, B. (2023). Student Perceptions of Resource Helpfulness. In Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE Vol. 2 (pp. 668). doi:10.1145/3587103.3594191

Russell, S., Caton, S., & Becker, B. A. (2023). Online Programming Exams - An Experience Report. In Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE Vol. 1 (pp. 436-442). doi:10.1145/3587102.3588829

Dr Takfarinas Saber

Farayola, M. M., Tal, I., Malika, B., Saber, T., & Connolly, R. (2023). Fairness of AI in Predicting the Risk of Recidivism: Review and Phase Mapping of AI Fairness Techniques. In ACM International Conference Proceeding Series. doi:10.1145/3600160.3605033

Assoc Professor Guenole Silvestre

Ramo, M., & Silvestre, G. C. M. (2023). A Transformer Architecture for Online Gesture Recognition of Mathematical Expressions. In Communications in Computer and Information Science Vol. 1662 CCIS (pp. 55-67). doi:10.1007/978-3-031-26438-2_5

Ramo, M., Silvestre, G. C. M., & Balado, F. (2023). Small, Multilingual, Explainable Transformers for Online Handwriting Decoding. In 2023 34th Irish Signals and Systems Conference, ISSC 2023. doi:10.1109/ISSC59246.2023.10162050

Dr Ricardo Simon Carbajo

Goktas, P., & Carbajo, R. S. (2023). Unleashing the Power of High-Throughput Bright-field Imaging for Enhanced Mesenchymal Cell Separation: A Novel Supervised Clustering Approach in Vitro Augmentation of Healthy and Stressful Conditions. In Proceedings of SPIE - The International Society for Optical Engineering Vol. 12629. doi:10.1117/12.2675886

Professor Barry Smyth

Tragos, E., O'Reilly-Morgan, D., Geraci, J., Shi, B., Smyth, B., Doherty, C., et al. (2023). Keeping People Active and Healthy at Home Using a Reinforcement Learning-based Fitness Recommendation Framework. In IJCAI International Joint Conference on Artificial Intelligence Vol. 2023-August (pp. 6237-6245).

 

Dolphin, R., Smyth, B., & Dong, R. (2023). Stock Embeddings: Representation Learning for Financial Time Series †. In Engineering Proceedings Vol. 39. doi:10.3390/engproc2023039030

Feely, C., Caulfield, B., Lawlor, A., & Smyth, B. (2023). Modelling the Training Practices of Recreational Marathon Runners to Make Personalised Training Recommendations. In UMAP 2023 - Proceedings of the 31st ACM Conference on User Modeling, Adaptation and Personalization (pp. 183-193). doi:10.1145/3565472.3592952

Assoc Professor Tony Veale

Veale, T. (2023). The Funhouse Mirror Has Two Sides: Visual Storification of Debates with Comics. In CEUR Workshop Proceedings Vol. 3370 (pp. 119-125).

Dr Anthony Ventresque

Laurent, T., Arcaini, P., Trubiani, C., & Ventresque, A. (2022). JSIMutate: understanding performance results through mutations. In ESEC/FSE 2022 - Proceedings of the 30th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering (pp. 1721-1725). doi:10.1145/3540250.3558930

Murphy, A., Lourenço, N., & Ventresque, A. (2023). Initialisation in Structured Grammatical Evolution. In GECCO 2023 Companion - Proceedings of the 2023 Genetic and Evolutionary Computation Conference Companion (pp. 2022-2028). doi:10.1145/3583133.3596412

Dr Anh Vu Vo

Lokugam Hewage, C. N., Vo, A. V., Bertolotto, M., Le-Khac, N. A., & Laefer, D. (2022). 4SA: OPTIMIZING SPACE FILLING CURVE BASED GRID CELL INDEXING TO SCALABLY MANAGE REMOTELY SENSED IMAGES IN KEY-VALUE DATABASES. In ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences Vol. 10 (pp. 143-150). doi:10.5194/isprs-annals-X-4-W3-2022-143-2022

Vo, A., Bertolotto, M., Laefer, D., Le Khac, N. A., & Ofterdinger, U. (2023). A Big Data approach for building basement detection using airborne LiDAR data. In ISMLG 2023 - 4th International Symposium on Machine Learning and Big Data in Geoscience.

Ms Lan Wei

Wei, L., & Mooney, C. (2023). Investigating the Need for Pediatric-Specific Machine Learning Approaches for Seizure Detection in EEG. In 2023 11th International Conference on Bioinformatics and Computational Biology, ICBCB 2023 (pp. 57-63). doi:10.1109/ICBCB57893.2023.10246719

Wei, L., & Mooney, C. (2023). A Machine Learning Approach for Sex and Age Classification of Paediatric EEGs. In 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

 

Wei, L., & Mooney, C. (2023). Transfer Learning-based Seizure Detection on Multiple Channels of Paediatric EEGs. In 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

 

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Journal article

Madhusudhan, H. S., Kumar, S. T., Gupta, P., & McArdle, G. (2023). A Harris Hawk Optimisation system for energy and resource efficient virtual machine placement in cloud data centers. PLoS ONE, 18(8 August). doi:10.1371/journal.pone.0289156

Dr Alzubair Hassan

Shi, Z., Yang, Z., Hassan, A., Li, F., & Ding, X. (2023). A privacy preserving federated learning scheme using homomorphic encryption and secret sharing. Telecommunication Systems, 82(3), 419-433. doi:10.1007/s11235-022-00982-3

Dr Andrew Hines

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, 16(9), 1050-1070. doi:10.1049/sil2.12151

Barakabitze, A. A., Mkwawa, I. H., Hines, A., & Walshe, R. (2023). QoE-Aware Dynamic Resource Management in Future Softwarized and Virtualized Networks. IEEE Access, 11, 93310-93330. doi:10.1109/ACCESS.2023.3309599

Shariat Panah, D., Hines, A., & McKeever, S. (2023). Exploring the impact of noise and degradations on heart sound classification models. Biomedical Signal Processing and Control, 85. doi:10.1016/j.bspc.2023.104932

Assoc Professor Neil Hurley

Roy, A. S., D’amico, E., Lawlor, A., & Hurley, N. (2023). Addressing Fast Changing Fashion Trends in Multi-Stage Recommender Systems. Proceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS, 36. doi:10.32473/flairs.36.133307

Assoc Professor Georgiana Ifrim

Aderinola, T. B., Younesian, H., Whelan, D., Caulfield, B., & Ifrim, G. (2023). Quantifying Jump Height Using Markerless Motion Capture with a Single Smartphone. IEEE Open Journal of Engineering in Medicine and Biology, 4, 109-115. doi:10.1109/OJEMB.2023.3280127

Dhariyal, B., Le Nguyen, T., & Ifrim, G. (2023). Scalable classifier-agnostic channel selection for multivariate time series classification. Data Mining and Knowledge Discovery, 37(2), 1010-1054. doi:10.1007/s10618-022-00909-1

Singh, A., Bevilacqua, A., Nguyen, T. L., Hu, F., McGuinness, K., O’Reilly, M., et al. (2023). Fast and robust video-based exercise classification via body pose tracking and scalable multivariate time series classifiers. Data Mining and Knowledge Discovery, 37(2), 873-912. doi:10.1007/s10618-022-00895-4

Frizzarin, M., Visentin, G., Ferragina, A., Hayes, E., Bevilacqua, A., Dhariyal, B., et al. (2023). Classification of cow diet based on milk Mid Infrared Spectra: A data analysis competition at the “International Workshop on Spectroscopy and Chemometrics 2022”. Chemometrics and Intelligent Laboratory Systems, 234. doi:10.1016/j.chemolab.2023.104755

Dr Anca Delia Jurcut

Albahar, M., Alansari, D., & Jurcut, A. (2022). An Empirical Comparison of Pen-Testing Tools for Detecting Web App Vulnerabilities. Electronics (Switzerland), 11(19). doi:10.3390/electronics11192991

Yamany, B., Elsayed, M. S., Jurcut, A. D., Abdelbaki, N., & Azer, M. A. (2022). A New Scheme for Ransomware Classification and Clustering Using Static Features. Electronics (Switzerland), 11(20). doi:10.3390/electronics11203307

Rustam, F., Mushtaq, M. F., Hamza, A., Farooq, M. S., Jurcut, A. D., & Ashraf, I. (2022). Denial of Service Attack Classification Using Machine Learning with Multi-Features. Electronics (Switzerland), 11(22). doi:10.3390/electronics11223817

Yadav, A., Chithaluru, P., Singh, A., Albahar, M. A., Jurcut, A., Álvarez, R. M., et al. (2022). Suspended Sediment Yield Forecasting with Single and Multi-Objective Optimization Using Hybrid Artificial Intelligence Models. Mathematics, 10(22). doi:10.3390/math10224263

Ranaweera, P., Jurcut, A., & Liyanage, M. (2022). MEC-enabled 5G Use Cases: A Survey on Security Vulnerabilities and Countermeasures. ACM Computing Surveys, 54(9). doi:10.1145/3474552

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, 8(4), 1862-1880. doi:10.1109/TCCN.2022.3186331

Ranaweera, P., de Alwis, C., Jurcut, A. D., & Liyanage, M. (2022). Realizing contact-less applications with Multi-Access Edge Computing. ICT Express, 8(4), 575-587. doi:10.1016/j.icte.2022.03.001

Yi, Y., Zhu, N., He, J., Jurcut, A. D., & Zhao, B. (2022). Toward pragmatic modeling of privacy information propagation in online social networks. Computer Networks, 219. doi:10.1016/j.comnet.2022.109429

Yi, Y., Zhu, N., He, J., Jurcut, A. D., Ma, X., & Luo, Y. (2023). A privacy-sensitive data identification model in online social networks. Transactions on Emerging Telecommunications Technologies. doi:10.1002/ett.4876

El-Zoghby, A. M., Said Elsayed, M., Jurcut, A. D., & Azer, M. A. (2023). NG-MVEE: A New Proposed Hybrid Technique for Enhanced Mitigation of Code Re-Use Attack. IEEE Access, 11, 48169-48191. doi:10.1109/ACCESS.2023.3269881

Ranaweera, P., Yadav, A. K., Liyanage, M., & Jurcut, A. D. (2023). A Novel Authentication Protocol for 5 G gNodeBs in Service Migration Scenarios of MEC. IEEE Transactions on Dependable and Secure Computing. doi:10.1109/TDSC.2023.3320647

Yaseen, A., Jurcut, A., Nazir, M., Butt, Z., & Sabah, A. (2023). Machine learning-based business risk analysis for big data: a case study of Pakistan. International Journal of Computational Economics and Econometrics, 1(1). doi:10.1504/ijcee.2023.10057679

Nahhas, L., Albahar, M., Alammari, A., & Jurcut, A. (2023). Android Malware Detection Using ResNet-50 Stacking. Computers, Materials and Continua, 74(2), 3997-4014. doi:10.32604/cmc.2023.028316

Riaz, L., Qadir, H. M., Ali, G., Ali, M., Raza, M. A., Jurcut, A. D., & Ali, J. (2023). A Comprehensive Joint Learning System to Detect Skin Cancer. IEEE Access, 11, 79434-79444. doi:10.1109/ACCESS.2023.3297644

ElKashlan, M., Aslan, H., Said Elsayed, M., Jurcut, A. D., & Azer, M. A. (2023). Intrusion Detection for Electric Vehicle Charging Systems (EVCS). Algorithms, 16(2). doi:10.3390/a16020075

Gyamfi, E., Ansere, J. A., Kamal, M., Tariq, M., & Jurcut, A. (2023). An Adaptive Network Security System for IoT-Enabled Maritime Transportation. IEEE Transactions on Intelligent Transportation Systems, 24(2), 2538-2547. doi:10.1109/TITS.2022.3159450

Rustam, F., Ashraf, I., Jurcut, A. D., Bashir, A. K., & Zikria, Y. B. (2023). Malware detection using image representation of malware data and transfer learning. Journal of Parallel and Distributed Computing, 172, 32-50. doi:10.1016/j.jpdc.2022.10.001

ElKashlan, M., Elsayed, M. S., Jurcut, A. D., & Azer, M. (2023). A Machine Learning-Based Intrusion Detection System for IoT Electric Vehicle Charging Stations (EVCSs). Electronics (Switzerland), 12(4). doi:10.3390/electronics12041044

Cvitic, I., Perakovic, D., Periša, M., & Jurcut, A. D. (2023). Correction to: Methodology for Detecting Cyber Intrusions in e-Learning Systems during COVID-19 Pandemic (Mobile Networks and Applications, (2023), 28, 1, (231-242), 10.1007/s11036-021-01789-3). Mobile Networks and Applications, 28(1), 243. doi:10.1007/s11036-021-01879-2

Cvitic, I., Perakovic, D., Periša, M., & Jurcut, A. D. (2023). Methodology for Detecting Cyber Intrusions in e-Learning Systems during COVID-19 Pandemic. Mobile Networks and Applications. doi:10.1007/s11036-021-01789-3

Ibrahim Hairab, B., Aslan, H. K., Elsayed, M. S., Jurcut, A. D., & Azer, M. A. (2023). Anomaly Detection of Zero-Day Attacks Based on CNN and Regularization Techniques. Electronics (Switzerland), 12(3). doi:10.3390/electronics12030573

Yi, Y., Zhu, N., He, J., Jurcut, A. D., Ma, X., & Luo, Y. (2023). A privacy-dependent condition-based privacy-preserving information sharing scheme in online social networks. Computer Communications, 200, 149-160. doi:10.1016/j.comcom.2023.01.010

Gyamfi, E., & Jurcut, A. D. (2023). Novel Online Network Intrusion Detection System for Industrial IoT Based on OI-SVDD and AS-ELM. IEEE Internet of Things Journal, 10(5), 3827-3839. doi:10.1109/JIOT.2022.3172393

Abdelhamid, A., Elsayed, M. S., Jurcut, A. D., & Azer, M. A. (2023). A Lightweight Anomaly Detection System for Black Hole Attack. Electronics (Switzerland), 12(6). doi:10.3390/electronics12061294

Akram, M. A., Ahmad, H., Mian, A. N., Jurcut, A. D., & Kumari, S. (2023). Blockchain-based privacy-preserving authentication protocol for UAV networks. Computer Networks, 224. doi:10.1016/j.comnet.2023.109638

Eltahlawy, A. M., Aslan, H. K., Abdallah, E. G., Elsayed, M. S., Jurcut, A. D., & Azer, M. A. (2023). A Survey on Parameters Affecting MANET Performance. Electronics (Switzerland), 12(9). doi:10.3390/electronics12091956

Kanwal, K., Rustam, F., Chaganti, R., Jurcut, A. D., & Ashraf, I. (2023). Smartphone Inertial Measurement Unit Data Features for Analyzing Driver Driving Behavior. IEEE Sensors Journal, 23(11), 11308-11323. doi:10.1109/JSEN.2023.3256000

Mesbah, M., Elsayed, M. S., Jurcut, A. D., & Azer, M. (2023). Analysis of ICS and SCADA Systems Attacks Using Honeypots. Future Internet, 15(7). doi:10.3390/fi15070241

El-Gendy, S., Elsayed, M. S., Jurcut, A., & Azer, M. A. (n.d.). Privacy Preservation Using Machine Learning in the Internet of Things. Mathematics, 11(16), 3477. doi:10.3390/math11163477

Professor Mark Keane

Temraz, M., & Keane, M. T. (2022). Solving the class imbalance problem using a counterfactual method for data augmentation. Machine Learning with Applications, 9, 100375. doi:10.1016/j.mlwa.2022.100375

Quinn, M. S., Ford, C., & Keane, M. T. (2022). People's reports of unexpected events for everyday scenarios: Over 1000 textual responses, human-labelled for valence/sentiment, controllability and topic category. Data in Brief, 44. doi:10.1016/j.dib.2022.108545

Kenny, E. M., Delaney, E., & Keane, M. T. (2023). Advancing Post-Hoc Case-Based Explanation with Feature Highlighting. IJCAI International Joint Conference on Artificial Intelligence, 2023-August, 427-435.

 

Pakrashi, A., Ryan, C., Guéret, C., Berry, D. P., Corcoran, M., Keane, M. T., & Mac Namee, B. (2023). Early detection of subclinical mastitis in lactating dairy cows using cow-level features. Journal of Dairy Science, 106(7), 4978-4990. doi:10.3168/jds.2022-22803

Aryal, S., & Keane, M. T. (2023). Even If Explanations: Prior Work, Desiderata & Benchmarks for Semi-Factual XAI. Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence. doi:10.24963/ijcai.2023/732

Ford, C., & Keane, M. T. (2023). Explaining Classifications to Non-experts: An XAI User Study of Post-Hoc Explanations for a Classifier When People Lack Expertise. Unknown Journal, 246-260. doi:10.1007/978-3-031-37731-0_15

Professor Mohand Tahar Kechadi

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). doi:10.1093/cdn/nzac123

Chergui, N., & Kechadi, M. T. (2022). Data analytics for crop management: a big data view. Journal of Big Data, 9(1). doi:10.1186/s40537-022-00668-2

Dhelim, S., Aung, N., Kechadi, M. T., Ning, H., Chen, L., & Lakas, A. (2023). Trust2Vec: Large-Scale IoT Trust Management System Based on Signed Network Embeddings. IEEE Internet of Things Journal, 10(1), 553-562. doi:10.1109/JIOT.2022.3201772

Thantilage, R. D., Le-Khac, N. A., & Kechadi, M. T. (2023). Healthcare data security and privacy in Data Warehouse architectures. Informatics in Medicine Unlocked, 39. doi:10.1016/j.imu.2023.101270

Aung, N., Dhelim, S., Chen, L., Lakas, A., Zhang, W., Ning, H., et al. (2023). VeSoNet: Traffic-Aware Content Caching for Vehicular Social Networks Using Deep Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems, 24(8), 8638-8649. doi:10.1109/TITS.2023.3250320

Dr Vimal Kumar Kumar

Upadhyay, P. K., Rastogi, S., & Kumar, K. V. (2022). Coherent convolution neural network based retinal disease detection using optical coherence tomographic images. Journal of King Saud University - Computer and Information Sciences, 34(10), 9688-9695. doi:10.1016/j.jksuci.2021.12.002

Assoc Professor Alexey Lastovetsky

Manumachu, R. R., Khaleghzadeh, H., & Lastovetsky, A. (2023). Acceleration of Bi-Objective Optimization of Data-Parallel Applications for Performance and Energy on Heterogeneous Hybrid Platforms. IEEE Access, 11, 27226-27245. doi:10.1109/ACCESS.2023.3258684

Lastovetsky, A., & Manumachu, R. R. (2023). Energy-Efficient Parallel Computing: Challenges to Scaling. Information (Switzerland), 14(4). doi:10.3390/info14040248

Mr Thomas Laurent

Laurent, T., Arcaini, P., Trubiani, C., & Ventresque, A. (2022). Mutation-based analysis of queueing network performance models. Journal of Systems and Software, 191. doi:10.1016/j.jss.2022.111385

Ojdanic, M., Ma, W., Laurent, T., Chekam, T. T., Ventresque, A., & Papadakis, M. (2022). On the use of commit-relevant mutants. Empirical Software Engineering, 27(5). doi:10.1007/s10664-022-10138-1

Dr Aonghus Lawlor

Smyth, B., Lawlor, A., Berndsen, J., & Feely, C. (2022). Recommendations for marathon runners: on the application of recommender systems and machine learning to support recreational marathon runners. User Modeling and User-Adapted Interaction, 32(5), 787-838. doi:10.1007/s11257-021-09299-3

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), 32, 11, (7998-8007), 10.1007/s00330-022-08784-6). European Radiology, 32(11), 8054. 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, 32(11), 7998-8007. doi:10.1007/s00330-022-08784-6

Potocnik, J., Thomas, E., Killeen, R., Foley, S., Lawlor, A., & Stowe, J. (2022). Automated vetting of radiology referrals: exploring natural language processing and traditional machine learning approaches. Insights into Imaging, 13(1). doi:10.1186/s13244-022-01267-8

Konkolewska, A., Phang, S., Conaghan, P., Milbourne, D., Lawlor, A., & Byrne, S. (2023). Genomic prediction of seasonal forage yield in perennial ryegrass. Grassland Research. doi:10.1002/glr2.12058

Kelly, B. S., Mathur, P., Plesniar, J., Lawlor, A., & Killeen, R. P. (2023). Using deep learning–derived image features in radiologic time series to make personalised predictions: proof of concept in colonic transit data. European Radiology. doi:10.1007/s00330-023-09769-9

Kelly, B. S., Quinn, C., Belton, N., Lawlor, A., Killeen, R. P., & Burrell, J. (2023). Cybersecurity considerations for radiology departments involved with artificial intelligence. European Radiology. doi:10.1007/s00330-023-09860-1

Roy, A. S., D’amico, E., Lawlor, A., & Hurley, N. (2023). Addressing Fast Changing Fashion Trends in Multi-Stage Recommender Systems. Proceedings of the International Florida Artificial Intelligence Research Society Conference, FLAIRS, 36. doi:10.32473/flairs.36.133307

Feely, C., Smyth, B., Caulfield, B., & Lawlor, A. (2023). Estimating the cost of training disruptions on marathon performance. Frontiers in Sports and Active Living, 4. doi:10.3389/fspor.2022.1096124

Kelly, B. S., Kirwan, A., Quinn, M. S., Kelly, A. M., Mathur, P., Lawlor, A., & Killeen, R. P. (2023). The ethical matrix as a method for involving people living with disease and the wider public (PPI) in near-term artificial intelligence research. Radiography, 29, S103-S111. doi:10.1016/j.radi.2023.03.009

Kelly, B., Martinez, M., Do, H., Hayden, J., Huang, Y., Yedavalli, V., et al. (2023). DEEP MOVEMENT: Deep learning of movie files for management of endovascular thrombectomy. European Radiology, 33(8), 5728-5739. doi:10.1007/s00330-023-09478-3

Dr Quan Le

Gibert, D., Planes, J., Mateu, C., & Le, Q. (2022). Fusing feature engineering and deep learning: A case study for malware classification. Expert Systems with Applications, 207. doi:10.1016/j.eswa.2022.117957

Rakholia, R., Le, Q., Vu, K., Ho, B. Q., & Carbajo, R. S. (2022). AI-based air quality PM<inf>2.5</inf> forecasting models for developing countries: A case study of Ho Chi Minh City, Vietnam. Urban Climate, 46. doi:10.1016/j.uclim.2022.101315

Ho, B. Q., Vu, K., Nguyen, T., Le, Q., Rakholia, R., & Carbajo, R. S. (2022). The Emissions and Measures in Greenhouse Gases Management for Climate Change Mitigation in Developing Countries: A Case of Ho Chi Minh City, Vietnam. International Journal of Environmental Science and Development, 13(6), 257-263. doi:10.18178/ijesd.2022.13.6.1402

Rakholia, R., Le, Q., Vu, K. H. N., Ho, B. Q., & Carbajo, R. S. (2023). Outdoor air quality data for spatiotemporal analysis and air quality modelling in Ho Chi Minh City, Vietnam: A part of HealthyAir Project. Data in Brief, 46. doi:10.1016/j.dib.2022.108774

Rakholia, R., Le, Q., Quoc Ho, B., Vu, K., & Simon Carbajo, R. (2023). Multi-output machine learning model for regional air pollution forecasting in Ho Chi Minh City, Vietnam. Environment International, 173. doi:10.1016/j.envint.2023.107848

Assoc Professor Nhien An Le Khac

Kuppa, A., & Le-Khac, N. A. (2022). Learn to adapt: Robust drift detection in security domain. Computers and Electrical Engineering, 102. doi:10.1016/j.compeleceng.2022.108239

Lokugam Hewage, C. N., Laefer, D. F., Vo, A. V., Le-Khac, N. A., & Bertolotto, M. (2022). Scalability and Performance of LiDAR Point Cloud Data Management Systems: A State-of-the-Art Review. Remote Sensing, 14(20). doi:10.3390/rs14205277

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, 8(4), 1862-1880. 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, 30(6), 1041-1055. doi:10.1093/jigpal/jzac012

Thantilage, R. D., Le-Khac, N. A., & Kechadi, M. T. (2023). Healthcare data security and privacy in Data Warehouse architectures. Informatics in Medicine Unlocked, 39. doi:10.1016/j.imu.2023.101270

Sachintha, S., Le-Khac, N. A., Scanlon, M., & Sayakkara, A. P. (2023). Data Exfiltration through Electromagnetic Covert Channel of Wired Industrial Control Systems. Applied Sciences (Switzerland), 13(5). doi:10.3390/app13052928

Dr David Lillis

Lu, Z., Delaney, D. T., & Lillis, D. (2023). A Survey on Microservices Trust Models for Open Systems. IEEE Access, 11, 28840-28855. doi:10.1109/ACCESS.2023.3260147

Dr Madhusanka Liyanage

McEnroe, P., Wang, S., & Liyanage, M. (2022). A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges. IEEE Internet of Things Journal, 9(17), 15435-15459. doi:10.1109/JIOT.2022.3176400

Hewa, T., Braeken, A., Liyanage, M., & Ylianttila, M. (2022). Fog Computing and Blockchain-Based Security Service Architecture for 5G Industrial IoT-Enabled Cloud Manufacturing. IEEE Transactions on Industrial Informatics, 18(10), 7174-7185. doi:10.1109/TII.2022.3140792

Sandeepa, C., Siniarski, B., Kourtellis, N., Wang, S., & Liyanage, M. (2022). A survey on privacy for B5G/6G: New privacy challenges, and research directions. Journal of Industrial Information Integration, 30. doi:10.1016/j.jii.2022.100405

Kalla, A., de Alwis, C., Porambage, P., Gür, G., & Liyanage, M. (2022). A survey on the use of blockchain for future 6G: Technical aspects, use cases, challenges and research directions. Journal of Industrial Information Integration, 30. doi:10.1016/j.jii.2022.100404

Fernando, P., Dadallage, K., Gamage, T., Seneviratne, C., Madanayake, A., & Liyanage, M. (2022). Proof of Sense: A Novel Consensus Mechanism for Spectrum Misuse Detection. IEEE Transactions on Industrial Informatics, 18(12), 9206-9216. doi:10.1109/TII.2022.3169978

Ranaweera, P., de Alwis, C., Jurcut, A. D., & Liyanage, M. (2022). Realizing contact-less applications with Multi-Access Edge Computing. ICT Express, 8(4), 575-587. doi:10.1016/j.icte.2022.03.001

Yadav, A. K., Misra, M., Pandey, P. K., Braeken, A., & Liyange, M. (2022). An improved and provably secure symmetric-key based 5G-AKA Protocol. Computer Networks, 218, 109400. doi:10.1016/j.comnet.2022.109400

Ranaweera, P., Jurcut, A., & Liyanage, M. (2022). MEC-enabled 5G Use Cases: A Survey on Security Vulnerabilities and Countermeasures. ACM Computing Surveys, 54(9). doi:10.1145/3474552

Javed, A. R., Saadia, A., Mughal, H., Gadekallu, T. R., Rizwan, M., Maddikunta, P. K. R., et al. (2023). Artificial Intelligence for Cognitive Health Assessment: State-of-the-Art, Open Challenges and Future Directions. Cognitive Computation. doi:10.1007/s12559-023-10153-4

Ranaweera, P., Yadav, A. K., Liyanage, M., & Jurcut, A. D. (2023). A Novel Authentication Protocol for 5&amp;#x00A0;G gNodeBs in Service Migration Scenarios of MEC. IEEE Transactions on Dependable and Secure Computing. doi:10.1109/TDSC.2023.3320647

Fernando, P., Dadallage, K., Gamage, T., Seneviratne, C., Braeken, A., Madanayake, A., & Liyanage, M. (2023). Distributed-Proof-of-Sense: Blockchain Consensus Mechanisms for Detecting Spectrum Access Violations of the Radio Spectrum. IEEE Transactions on Cognitive Communications and Networking. doi:10.1109/TCCN.2023.3291366

Borhani, M., Avgouleas, I., Liyanage, M., & Gurtov, A. (2023). KDC Placement Problem in Secure VPLS Networks. IEEE Transactions on Information Forensics and Security, 18, 1951-1962. doi:10.1109/TIFS.2023.3254447

Bashir, A. K., Victor, N., Bhattacharya, S., Huynh-The, T., Chengoden, R., Yenduri, G., et al. (2023). Federated Learning for the Healthcare Metaverse: Concepts, Applications, Challenges, and Future Directions. IEEE Internet of Things Journal. doi:10.1109/JIOT.2023.3304790

Yadav, A. K., Wijethilaka, S., Braeken, A., Misra, M., & Liyanage, M. (2023). An Enhanced Cross-Network-Slice Authentication Protocol for 5G. IEEE Transactions on Sustainable Computing. doi:10.1109/TSUSC.2023.3283615

Mishra, R. A., Kalla, A., Braeken, A., & Liyanage, M. (2023). Blockchain Regulated Verifiable and Automatic Key Refreshment Mechanism for IoT. IEEE Access, 11, 21758-21770. doi:10.1109/ACCESS.2023.3251651

Alwis, C. D., Porambage, P., Dev, K., Gadekallu, T. R., & Liyanage, M. (2023). A Survey on Network Slicing Security: Attacks, Challenges, Solutions and Research Directions. IEEE Communications Surveys and Tutorials. doi:10.1109/COMST.2023.3312349

Hewa, T., Porambage, P., Kovacevic, I., Weerasinghe, N., Harjula, E., Liyanage, M., & Ylianttila, M. (2023). Blockchain-Based Network Slice Broker to Facilitate Factory-As-a-Service. IEEE Transactions on Industrial Informatics, 19(1), 519-530. doi:10.1109/TII.2022.3173928

Weerasinghe, N., Mishra, R., Porambage, P., Liyanage, M., & Ylianttila, M. (2023). Proof-of-Monitoring (PoM): A Novel Consensus Mechanism for Blockchain-based Secure Service Level Agreement Management. IEEE Transactions on Network and Service Management, 1. doi:10.1109/tnsm.2023.3234862

Karunarathna, S., Wijethilaka, S., Ranaweera, P., Hemachandra, K. T., Samarasinghe, T., & Liyanage, M. (2023). The Role of Network Slicing and Edge Computing in the Metaverse Realization. IEEE Access, 11, 25502-25530. doi:10.1109/ACCESS.2023.3255510

Hakak, S., Gadekallu, T. R., Maddikunta, P. K. R., Ramu, S. P., M, P., De Alwis, C., & Liyanage, M. (2023). Autonomous vehicles in 5G and beyond: A survey. Vehicular Communications, 39. doi:10.1016/j.vehcom.2022.100551

Yadav, A. K., Misra, M., Pandey, P. K., & Liyanage, M. (2023). An EAP-Based Mutual Authentication Protocol for WLAN-Connected IoT Devices. IEEE Transactions on Industrial Informatics, 19(2), 1343-1355. doi:10.1109/TII.2022.3194956

Hewa, T., Porambage, P., Kalla, A., Osorio, D. P. M., Liyanage, M., & Ylianttila, M. (2023). Blockchain and Game Theory Convergence for Network Slice Brokering. Computer, 56(3), 80-91. doi:10.1109/MC.2022.3165533

Mathur, S., Kalla, A., Gür, G., Bohra, M. K., & Liyanage, M. (2023). A Survey on Role of Blockchain for IoT: Applications and Technical Aspects. Computer Networks, 227. doi:10.1016/j.comnet.2023.109726

Liyanage, M., Braeken, A., Shahabuddin, S., & Ranaweera, P. (2023). Open RAN security: Challenges and opportunities. Journal of Network and Computer Applications, 214. doi:10.1016/j.jnca.2023.103621

Wijethilaka, S., & Liyanage, M. (2023). The role of security orchestrator in network slicing for future networks. Journal of Communications and Networks, 25(3), 355-369. doi:10.23919/jcn.2023.000030

Huynh-The, T., Gadekallu, T. R., Wang, W., Yenduri, G., Ranaweera, P., Pham, Q. V., et al. (2023). Blockchain for the metaverse: A Review. Future Generation Computer Systems, 143, 401-419. doi:10.1016/j.future.2023.02.008

Volosin, M., Slapak, E., Becvar, Z., Maksymyuk, T., Petik, A., Liyanage, M., & Gazda, J. (2023). Blockchain-Based Route Selection With Allocation of Radio and Computing Resources for Connected Autonomous Vehicles. IEEE Transactions on Intelligent Transportation Systems, 24(7), 7230-7243. doi:10.1109/TITS.2023.3255301

De Alwis, C., Kumar, P., Pham, Q. V., Dev, K., Kalla, A., Liyanage, M., & Hwang, W. J. (2023). Towards 6G: Key technological directions. ICT Express, 9(4), 525-533. doi:10.1016/j.icte.2022.10.005

Assoc Professor Brian Mac Namee

Miralles-Pechuán, L., Qureshi, M. A., & Namee, B. M. (2023). Real-time bidding campaigns optimization using user profile settings. Electronic Commerce Research, 23(2), 1297-1322. doi:10.1007/s10660-021-09513-9

Pakrashi, A., Ryan, C., Guéret, C., Berry, D. P., Corcoran, M., Keane, M. T., & Mac Namee, B. (2023). Early detection of subclinical mastitis in lactating dairy cows using cow-level features. Journal of Dairy Science, 106(7), 4978-4990. doi:10.3168/jds.2022-22803

Professor Eleni Mangina

Iqbal, M. Z., Mangina, E., & Campbell, A. G. (2022). Current Challenges and Future Research Directions in Augmented Reality for Education. Multimodal Technologies and Interaction, 6(9). doi:10.3390/mti6090075

Langan, P., Bernád, V., Walsh, J., Henchy, J., Khodaeiaminjan, M., Mangina, E., & Negrão, S. (2022). Phenotyping for waterlogging tolerance in crops: current trends and future prospects. Journal of Experimental Botany, 73(15), 5149-5169. doi:10.1093/jxb/erac243

Kane, D., Ryan, G., Mangina, E., & McAuliffe, F. M. (2022). A randomized control trial of a virtual reality learning environment in obstetric medical student teaching. International Journal of Medical Informatics, 168. doi:10.1016/j.ijmedinf.2022.104899

Ryan, G., Callaghan, S., Rafferty, A., Murphy, J., Higgins, M., Barry, T., et al. (2022). Virtual reality in midwifery education: A mixed methods study to assess learning and understanding. Nurse Education Today, 119. doi:10.1016/j.nedt.2022.105573

Mangina, E., Psyrra, G., Screpanti, L., & Scaradozzi, D. (2023). Robotics in the Context of Primary and Pre-School Education: A Scoping Review. IEEE Transactions on Learning Technologies. doi:10.1109/TLT.2023.3266631

Ryan, G., Rafferty, A., Murphy, J., Higgins, M. F., Mangina, E., & McAuliffe, F. M. (2023). Virtual reality learning: A randomized controlled trial assessing medical student knowledge of fetal development. International Journal of Gynecology and Obstetrics, 162(1), 292-299. doi:10.1002/ijgo.14684

Chen, S., Zeng, X., Laefer, D. F., Truong-Hong, L., & Mangina, E. (2023). Flight Path Setting and Data Quality Assessments for Unmanned-Aerial-Vehicle-Based Photogrammetric Bridge Deck Documentation. Sensors, 23(16). doi:10.3390/s23167159

Dr Ravi Manumachu

Manumachu, R. R., Khaleghzadeh, H., & Lastovetsky, A. (2023). Acceleration of Bi-Objective Optimization of Data-Parallel Applications for Performance and Energy on Heterogeneous Hybrid Platforms. IEEE Access, 11, 27226-27245. doi:10.1109/ACCESS.2023.3258684

Lastovetsky, A., & Manumachu, R. R. (2023). Energy-Efficient Parallel Computing: Challenges to Scaling. Information (Switzerland), 14(4). doi:10.3390/info14040248

Dr Mark Matthews

Frank, E., Wallace, M. L., Matthews, M. L., Kendrick, J., Leach, J., Moore, T., et al. (2022). Personalized digital intervention for depression based on social rhythm principles adds significantly to outpatient treatment. Frontiers in Digital Health, 4. doi:10.3389/fdgth.2022.870522

Blair, J., Brozena, J., Matthews, M., Richardson, T., & Abdullah, S. (2022). Financial technologies (FinTech) for mental health: The potential of objective financial data to better understand the relationships between financial behavior and mental health. Frontiers in Psychiatry, 13. doi:10.3389/fpsyt.2022.810057

Frank, E., Wallace, M. L., Matthews, M. J., Kendrick, J., Leach, J., Moore, T., et al. (2023). Corrigendum: Personalized digital intervention for depression based on social rhythm principles adds significantly to outpatient treatment(Front. Digit. Health, (2022), 4, (870522), 10.3389/fdgth.2022.870522). Frontiers in Digital Health, 5. doi:10.3389/fdgth.2023.1136316

Assoc Professor Gavin McArdle

Jain, M., Sengar, V. S., Gollini, I., Bertolotto, M., McArdle, G., & Dev, S. (2022). LAMSkyCam: A low-cost and miniature ground-based sky camera. HardwareX, 12. doi:10.1016/j.ohx.2022.e00346

Dunne, L., & McArdle, G. (2022). A LARGE SCALE METHOD FOR EXTRACTING GEOGRAPHICAL FEATURES ON BUS ROUTES FROM OPENSTREETMAP AND ASSESSMENT OF THEIR IMPACT ON BUS SPEED AND RELIABILITY. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 48(4/W5-2022), 37-44. doi:10.5194/isprs-archives-XLVIII-4-W5-2022-37-2022

Zarbakhsh, N., & McArdle, G. (2022). PREDICTING TRAFFIC CONGESTION DURING COVID19 USING HUMAN MOBILITY AND STREET-WASTE FEATURES. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 10(4/W3-2022), 301-308. doi:10.5194/isprs-annals-X-4-W3-2022-301-2022

Burse, R., McArdle, G., & Bertolotto, M. (2022). Targeting stopwords for quality assurance of SNOMED-CT. International Journal of Medical Informatics, 167. doi:10.1016/j.ijmedinf.2022.104870

Mohammadi, S., Saber, M., Amini, S., Mostafavi, M. A., McArdle, G., & Rabiei-Dastjerdi, H. (2022). Environmental Conditions in Middle Eastern Megacities: A Comparative Spatiotemporal Analysis Using Remote Sensing Time Series. Remote Sensing, 14(22). doi:10.3390/rs14225834

Rabiei-Dastjerdi, H., Mohammadi, S., Samouei, R., Kazemi, M., Matthews, S., McArdle, G., et al. (2023). MEASURING SPATIAL ACCESSIBILITY TO HEALTHCARE FACILITIES IN ISFAHAN METROPOLITAN AREA IN IRAN. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 10(4/W1-2022), 623-630. doi:10.5194/isprs-annals-X-4-W1-2022-623-2023

McArdle, G., Kergosien, E., Sallaberry, C., & Schoen-Phelan, B. (2023). Special Track on GeoInformation Analysis (ACM SAC, GIA track). Proceedings of the ACM Symposium on Applied Computing, 493-494.

 

Madhusudhan, H. S., Kumar, S. T., Gupta, P., & McArdle, G. (2023). A Harris Hawk Optimisation system for energy and resource efficient virtual machine placement in cloud data centers. PLoS ONE, 18(8 August). doi:10.1371/journal.pone.0289156

Assoc Professor Catherine Mooney

Mazo, C., Aura, C., Rahman, A., Gallagher, W. M., & Mooney, C. (2022). Application of Artificial Intelligence Techniques to Predict Risk of Recurrence of Breast Cancer: A Systematic Review. Journal of Personalized Medicine, 12(9). doi:10.3390/jpm12091496

Du, Y., Antoniadi, A. M., McNestry, C., McAuliffe, F. M., & Mooney, C. (2022). The Role of XAI in Advice-Taking from a Clinical Decision Support System: A Comparative User Study of Feature Contribution-Based and Example-Based Explanations. Applied Sciences (Switzerland), 12(20). doi:10.3390/app122010323

Wei, L., Ventura, S., Ryan, M. A., Mathieson, S., Boylan, G. B., Lowery, M., & Mooney, C. (2022). Deep-spindle: An automated sleep spindle detection system for analysis of infant sleep spindles. Computers in Biology and Medicine, 150. doi:10.1016/j.compbiomed.2022.106096

Du, Y., Rafferty, A. R., McAuliffe, F. M., Wei, L., & Mooney, C. (2022). An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus. Scientific Reports, 12(1). doi:10.1038/s41598-022-05112-2

Brindley, E., Heiland, M., Mooney, C., Diviney, M., Mamad, O., Hill, T. D. M., et al. (2023). Brain cell-specific origin of circulating microRNA biomarkers in experimental temporal lobe epilepsy. Frontiers in Molecular Neuroscience, 16. doi:10.3389/fnmol.2023.1230942

Du, Y., Rafferty, A. R., McAuliffe, F. M., Mehegan, J., & Mooney, C. (2023). Towards an explainable clinical decision support system for large-for-gestational-age births. PLoS ONE, 18(2 February). doi:10.1371/journal.pone.0281821

Du, Y., McNestry, C., Wei, L., Antoniadi, A. M., McAuliffe, F. M., & Mooney, C. (2023). Machine learning-based clinical decision support systems for pregnancy care: A systematic review. International Journal of Medical Informatics, 173. doi:10.1016/j.ijmedinf.2023.105040

Dr Conor Muldoon

Görgü, L., Hawtree, D., O'Grady, M. J., Muldoon, C., Masterson, B., Meijer, W. G., et al. (2023). The MÉRA Data Extraction toolkit. Meteorological Applications, 30(1). doi:10.1002/met.2111

Professor John Murphy

Siniarski, B., Le, D. D., McArdle, C., Murphy, J., & Barry, L. (2022). DROAD: Demand-aware reconfigurable optically-switched agile data center network. Optical Switching and Networking, 45. doi:10.1016/j.osn.2022.100683

Ryan, G., Callaghan, S., Rafferty, A., Murphy, J., Higgins, M., Barry, T., et al. (2022). Virtual reality in midwifery education: A mixed methods study to assess learning and understanding. Nurse Education Today, 119. doi:10.1016/j.nedt.2022.105573

Ryan, G., Rafferty, A., Murphy, J., Higgins, M. F., Mangina, E., & McAuliffe, F. M. (2023). Virtual reality learning: A randomized controlled trial assessing medical student knowledge of fetal development. International Journal of Gynecology and Obstetrics, 162(1), 292-299. doi:10.1002/ijgo.14684

Dr Avishek Nag

Sharma, S., Nag, A., & Ramamurthy, B. (2022). Cross-Atlantic Experiments on EU-US Test-Beds. IEEE Networking Letters, 4(3), 108-112. doi:10.1109/lnet.2022.3177712

Pathan, M. S., Nag, A., Pathan, M. M., & Dev, S. (2022). Analyzing the impact of feature selection on the accuracy of heart disease prediction. Healthcare Analytics, 2. doi:10.1016/j.health.2022.100060

Yanhui, L., Jianbiao, Z., Salman Pathan, M., Yijian, Y., Puzhe, Z., Maroc, S., & Nag, A. (2022). Research on identity authentication system of Internet of Things based on blockchain technology. Journal of King Saud University - Computer and Information Sciences, 34(10), 10365-10377. doi:10.1016/j.jksuci.2022.10.027

Wang, Y., Yu, X., Zhao, Y., Nag, A., & Zhang, J. (2022). Pre-established entanglement distribution algorithm in quantum networks. Journal of Optical Communications and Networking, 14(12), 1020-1033. doi:10.1364/JOCN.465432

Batra, S., Wang, H., Nag, A., Brodeur, P., Checkley, M., Klinkert, A., & Dev, S. (2022). DMCNet: Diversified model combination network for understanding engagement from video screengrabs. Systems and Soft Computing, 4. doi:10.1016/j.sasc.2022.200039

Sharma, S., & Nag, A. (2023). Cognitive Software Defined Networking and Network Function Virtualization and Applications. Future Internet, 15(2). doi:10.3390/fi15020078

Zhu, Q., Yu, X., Zhao, Y., Nag, A., & Zhang, J. (2023). Resource Allocation in Quantum-Key-Distribution- Secured Datacenter Networks With Cloud-Edge Collaboration. IEEE Internet of Things Journal, 10(12), 10916-10932. doi:10.1109/JIOT.2023.3242725

Dr Vivek Nallur

Duboc, L., Bahsoon, R., Alrebeish, F., Mera-Gómez, C., Nallur, V., Kazman, R., et al. (2021). Systematic Scalability Modeling of QoS-aware Dynamic Service Composition. ACM Transactions on Autonomous and Adaptive Systems, 16(3-4), 1-39. doi:10.1145/3529162

Ramanayake, R., Wicke, P., & Nallur, V. (2023). Immune moral models? Pro-social rule breaking as a moral enhancement approach for ethical AI. AI & SOCIETY, 38(2), 801-813. doi:10.1007/s00146-022-01478-z

Nallur, V., Dennis, L., Bringsjord, S., & Govindarajulu, N. S. (2023). A Partially Synthesized Position on the Automation of Machine Ethics. Digital Society, 2(2). doi:10.1007/s44206-023-00040-8

Assoc Professor Mel Ó Cinnéide

Hemati Moghadam, I., Ó Cinnéide, M., Sardarian, A., & Zarepour, F. (2023). Model-based source code refactoring with interaction and visual cues. Journal of Software: Evolution and Process. doi:10.1002/smr.2596

Dr Michael O'Grady

O’Grady, M. (2023). Transformative education for sustainable development: A faculty perspective. Environment, Development and Sustainability. doi:10.1007/s10668-023-03609-y

Görgü, L., Hawtree, D., O'Grady, M. J., Muldoon, C., Masterson, B., Meijer, W. G., et al. (2023). The MÉRA Data Extraction toolkit. Meteorological Applications, 30(1). doi:10.1002/met.2111

Professor Gregory O'Hare

Byabazaire, J., O'hare, G. M. P., & Delaney, D. T. (2022). End-to-End Data Quality Assessment Using Trust for Data Shared IoT Deployments. IEEE Sensors Journal, 22(20), 19995-20009. doi:10.1109/JSEN.2022.3203853

Görgü, L., Hawtree, D., O'Grady, M. J., Muldoon, C., Masterson, B., Meijer, W. G., et al. (2023). The MÉRA Data Extraction toolkit. Meteorological Applications, 30(1). doi:10.1002/met.2111

Thomas, R. J., O'Hare, G., & Coyle, D. (2023). Understanding technology acceptance in smart agriculture: A systematic review of empirical research in crop production. Technological Forecasting and Social Change, 189. doi:10.1016/j.techfore.2023.122374

Nolan, T. M., Reynolds, L. J., Sala-Comorera, L., Martin, N. A., Stephens, J. H., O'Hare, G. M. P., et al. (2023). Land use as a critical determinant of faecal and antimicrobial resistance gene pollution in riverine systems. Science of the Total Environment, 871. doi:10.1016/j.scitotenv.2023.162052

Rasti, S., Bleakley, C. J., Silvestre, G. C. M., O'Hare, G. M. P., & Langton, D. (2023). Assessment of deep learning methods for classification of cereal crop growth stage pre and post canopy closure. Journal of Electronic Imaging, 32(3). doi:10.1117/1.JEI.32.3.033014

Gao, G., O’Sullivan, J. J., Corkery, A., Bedri, Z., O’Hare, G. M. P., & Meijer, W. G. (2023). The Use of Transport Time Scales as Indicators of Pollution Persistence in a Macro-Tidal Setting. Journal of Marine Science and Engineering, 11(5), 1073. doi:10.3390/jmse11051073

Byabazaire, J., O’Hare, G. M. P., Collier, R., & Delaney, D. (2023). IoT Data Quality Assessment Framework Using Adaptive Weighted Estimation Fusion. Sensors, 23(13). doi:10.3390/s23135993

Byabazaire, J., O’Hare, G. M. P., Collier, R., Kulatunga, C., & Delaney, D. (2023). A Comprehensive Approach to Assessing Yield Map Quality in Smart Agriculture: Void Detection and Spatial Error Mapping. Agronomy, 13(7). doi:10.3390/agronomy13071943

Dr Arjun Pakrashi

Pakrashi, A., Ryan, C., Guéret, C., Berry, D. P., Corcoran, M., Keane, M. T., & Mac Namee, B. (2023). Early detection of subclinical mastitis in lactating dairy cows using cow-level features. Journal of Dairy Science, 106(7), 4978-4990. doi:10.3168/jds.2022-22803

Dr Liliana Pasquale

Ntafloukas, K., McCrum, D. P., & Pasquale, L. (2022). A Cyber-Physical Risk Assessment Approach for Internet of Things Enabled Transportation Infrastructure. Applied Sciences (Switzerland), 12(18). doi:10.3390/app12189241

Azzam, M., Pasquale, L., Provan, G., & Nuseibeh, B. (2023). Forensic readiness of industrial control systems under stealthy attacks. Computers and Security, 125. doi:10.1016/j.cose.2022.103010

Azzam, M., Pasquale, L., Provan, G., & Nuseibeh, B. (2023). Efficient Predictive Monitoring of Linear Time-Invariant Systems Under Stealthy Attacks. IEEE Transactions on Control Systems Technology, 31(2), 735-747. doi:10.1109/TCST.2022.3196809

Ntafloukas, K., Pasquale, L., Martinez-Pastor, B., & McCrum, D. P. (2023). A Vulnerability Assessment Approach for Transportation Networks Subjected to Cyber–Physical Attacks. Future Internet, 15(3). doi:10.3390/fi15030100

Dr Duong Cao Phan

Pham, T. D., Ha, N. T., Saintilan, N., Skidmore, A., Phan, D. C., Le, N. N., et al. (2023). Advances in Earth observation and machine learning for quantifying blue carbon. Earth-Science Reviews, 243, 104501. doi:10.1016/j.earscirev.2023.104501

Assoc Professor Gianluca Pollastri

Mahmoud, S. S. M., Portelli, B., D’agostino, G., Pollastri, G., Serra, G., & Fogolari, F. (2023). A Comparison of Mutual Information, Linear Models and Deep Learning Networks for Protein Secondary Structure Prediction. Current Bioinformatics, 18(8), 631-646. doi:10.2174/1574893618666230417103346

Villaman, C., Pollastri, G., Saez, M., & Martin, A. J. M. (2023). Benefiting from the intrinsic role of epigenetics to predict patterns of CTCF binding. Computational and Structural Biotechnology Journal, 21, 3024-3031. doi:10.1016/j.csbj.2023.05.012

Dr Alessandro Ragano

Benetos, E., Ragano, A., Sgroi, D., & Tuckwell, A. (2022). Measuring national mood with music: using machine learning to construct a measure of national valence from audio data. Behavior Research Methods, 54(6), 3085-3092. doi:10.3758/s13428-021-01747-7

Dr Rajnish Rakholia

Ho, B. Q., Vu, K., Nguyen, T., Le, Q., Rakholia, R., & Carbajo, R. S. (2022). The Emissions and Measures in Greenhouse Gases Management for Climate Change Mitigation in Developing Countries: A Case of Ho Chi Minh City, Vietnam. International Journal of Environmental Science and Development, 13(6), 257-263. doi:10.18178/ijesd.2022.13.6.1402

Rakholia, R., Le, Q., Vu, K., Ho, B. Q., & Carbajo, R. S. (2022). AI-based air quality PM<inf>2.5</inf> forecasting models for developing countries: A case study of Ho Chi Minh City, Vietnam. Urban Climate, 46. doi:10.1016/j.uclim.2022.101315

Rakholia, R., Le, Q., Vu, K. H. N., Ho, B. Q., & Carbajo, R. S. (2023). Outdoor air quality data for spatiotemporal analysis and air quality modelling in Ho Chi Minh City, Vietnam: A part of HealthyAir Project. Data in Brief, 46. doi:10.1016/j.dib.2022.108774

Rakholia, R., Le, Q., Quoc Ho, B., Vu, K., & Simon Carbajo, R. (2023). Multi-output machine learning model for regional air pollution forecasting in Ho Chi Minh City, Vietnam. Environment International, 173. doi:10.1016/j.envint.2023.107848

Dr Seán Russell

Collier, R., Russell, S., Ghanadbashi, S., & Golpayegani, F. (2022). Towards the Use of Hypermedia MAS and Microservices for Web Scale Agent-Based Simulation. SN Computer Science, 3(6). doi:10.1007/s42979-022-01424-2

Jagutis, M., Russell, S., & Collier, R. (2023). Flexible simulation of traffic with microservices, agents &amp; REST. International Journal of Parallel, Emergent and Distributed Systems. doi:10.1080/17445760.2023.2242183

Dr Colm Ryan

Upadhya, S. R., & Ryan, C. J. (2022). Experimental reproducibility limits the correlation between mRNA and protein abundances in tumor proteomic profiles. Cell Reports Methods, 2(9). doi:10.1016/j.crmeth.2022.100288

Upadhya, S. R., & Ryan, C. J. (2023). Antibody reliability influences observed mRNA-protein correlations in tumour samples. Life Science Alliance, 6(8). doi:10.26508/lsa.202201885

Ryan, C. J., Mehta, I., Kebabci, N., & Adams, D. J. (2023). Targeting synthetic lethal paralogs in cancer. Trends in Cancer, 9(5), 397-409. doi:10.1016/j.trecan.2023.02.002

Ryan, C. J. (2023). Genetic interactions under the microscope. Cell Systems, 14(5), 341-342. doi:10.1016/j.cels.2023.04.005

Dr Takfarinas Saber

Howell, A., Saber, T., & Bendechache, M. (2023). Measuring node decentralisation in blockchain peer to peer networks. Blockchain: Research and Applications, 4(1). doi:10.1016/j.bcra.2022.100109

Farayola, M. M., Tal, I., Connolly, R., Saber, T., & Bendechache, M. (2023). Ethics and Trustworthiness of AI for Predicting the Risk of Recidivism: A Systematic Literature Review. Information (Switzerland), 14(8). doi:10.3390/info14080426

Assoc Professor Mark Scanlon

Scanlon, M., Nikkel, B., & Geradts, Z. (2023). Digital forensic investigation in the age of ChatGPT. Forensic Science International: Digital Investigation, 44. doi:10.1016/j.fsidi.2023.301543

Sachintha, S., Le-Khac, N. A., Scanlon, M., & Sayakkara, A. P. (2023). Data Exfiltration through Electromagnetic Covert Channel of Wired Industrial Control Systems. Applied Sciences (Switzerland), 13(5). doi:10.3390/app13052928

Kanta, A., Coisel, I., & Scanlon, M. (2023). Harder, better, faster, stronger: Optimising the performance of context-based password cracking dictionaries. Forensic Science International: Digital Investigation, 44. doi:10.1016/j.fsidi.2023.301507

Dr Arsalan Shahid

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). doi:10.1093/cdn/nzac123

Cooper, D., Reinhold, B., Shahid, A., & Lewis, D. M. (2023). Glucose Variability Analysis in Two Large-Scale and Real-World Data Sets of Open-Source Automated Insulin Delivery Systems. Journal of Diabetes Science and Technology. doi:10.1177/19322968231198871

Zafar, A., Lewis, D. M., & Shahid, A. (2023). Long-Term Glucose Forecasting for Open-Source Automated Insulin Delivery Systems: A Machine Learning Study with Real-World Variability Analysis. Healthcare (Switzerland), 11(6). doi:10.3390/healthcare11060779

Lewis, D. M., & Shahid, A. (2023). Survey of Pancreatic Enzyme Replacement Therapy Dosing Experiences in Adults with Exocrine Pancreatic Insufficiency. Healthcare (Switzerland), 11(16). doi:10.3390/healthcare11162316

Assoc Professor Guenole Silvestre

Rasti, S., Bleakley, C. J., Silvestre, G. C. M., O'Hare, G. M. P., & Langton, D. (2023). Assessment of deep learning methods for classification of cereal crop growth stage pre and post canopy closure. Journal of Electronic Imaging, 32(3). doi:10.1117/1.JEI.32.3.033014

Dr Ricardo Simon Carbajo

Ho, B. Q., Vu, K., Nguyen, T., Le, Q., Rakholia, R., & Carbajo, R. S. (2022). The Emissions and Measures in Greenhouse Gases Management for Climate Change Mitigation in Developing Countries: A Case of Ho Chi Minh City, Vietnam. International Journal of Environmental Science and Development, 13(6), 257-263. doi:10.18178/ijesd.2022.13.6.1402

Rakholia, R., Le, Q., Vu, K., Ho, B. Q., & Carbajo, R. S. (2022). AI-based air quality PM<inf>2.5</inf> forecasting models for developing countries: A case study of Ho Chi Minh City, Vietnam. Urban Climate, 46. doi:10.1016/j.uclim.2022.101315

Rakholia, R., Le, Q., Vu, K. H. N., Ho, B. Q., & Carbajo, R. S. (2023). Outdoor air quality data for spatiotemporal analysis and air quality modelling in Ho Chi Minh City, Vietnam: A part of HealthyAir Project. Data in Brief, 46. doi:10.1016/j.dib.2022.108774

Dr Bartlomiej Siniarski

Siniarski, B., Le, D. D., McArdle, C., Murphy, J., & Barry, L. (2022). DROAD: Demand-aware reconfigurable optically-switched agile data center network. Optical Switching and Networking, 45. doi:10.1016/j.osn.2022.100683

Sandeepa, C., Siniarski, B., Kourtellis, N., Wang, S., & Liyanage, M. (2022). A survey on privacy for B5G/6G: New privacy challenges, and research directions. Journal of Industrial Information Integration, 30. doi:10.1016/j.jii.2022.100405

Professor Barry Smyth

Smyth, B., Maunder, E., Meyler, S., Hunter, B., & Muniz-Pumares, D. (2022). Decoupling of Internal and External Workload During a Marathon: An Analysis of Durability in 82,303 Recreational Runners. Sports Medicine, 52(9), 2283-2295. doi:10.1007/s40279-022-01680-5

Smyth, B., Lawlor, A., Berndsen, J., & Feely, C. (2022). Recommendations for marathon runners: on the application of recommender systems and machine learning to support recreational marathon runners. User Modeling and User-Adapted Interaction, 32(5), 787-838. doi:10.1007/s11257-021-09299-3

Cunningham, E., Smyth, B., & Greene, D. (2022). Author multidisciplinarity and disciplinary roles in field of study networks. Applied Network Science, 7(1). doi:10.1007/s41109-022-00517-4

Hagemann, N., O’Mahony, M. P., & Smyth, B. (2023). Visual Module Exploration: A Live-User Evaluation. KI - Kunstliche Intelligenz. doi:10.1007/s13218-023-00800-1

Feely, C., Smyth, B., Caulfield, B., & Lawlor, A. (2023). Estimating the cost of training disruptions on marathon performance. Frontiers in Sports and Active Living, 4. doi:10.3389/fspor.2022.1096124

Mr Andres Suarez-Cetrulo

Suárez-Cetrulo, A. L., Quintana, D., & Cervantes, A. (2023). A survey on machine learning for recurring concept drifting data streams. Expert Systems with Applications, 213. doi:10.1016/j.eswa.2022.118934

Miralles-Pechuán, L., Kumar, A., & Suárez-Cetrulo, A. L. (2023). Forecasting COVID-19 cases using dynamic time warping and incremental machine learning methods. Expert Systems, 40(6). doi:10.1111/exsy.13237

Dr Hadi Tabatabaee

Kazmi, A., Chaudhry, S. R., Malazi, H. T., Dhara, S., & Clarke, S. (2022). Interoperable Internet of Things for Smart Transportation Systems in Circular Cities. Computer, 55(12), 86-97. doi:10.1109/MC.2022.3202298

Khazael, B., Vahidi Asl, M., & Tabatabaee Malazi, H. (2023). Geospatial complex event processing in smart city applications. Simulation Modelling Practice and Theory, 122. doi:10.1016/j.simpat.2022.102675

Chaudhry, S. R., Malazi, H. T., Dhara, S., Kazmi, A. H., & Clarke, S. (2023). Toward Context-Aware Information Dissemination in Autonomous Networks of Vehicles. IEEE Communications Standards Magazine, 7(2), 8-15. doi:10.1109/MCOMSTD.0002.2200008

Dr Anthony Ventresque

Ojdanic, M., Ma, W., Laurent, T., Chekam, T. T., Ventresque, A., & Papadakis, M. (2022). On the use of commit-relevant mutants. Empirical Software Engineering, 27(5). doi:10.1007/s10664-022-10138-1

Laurent, T., Arcaini, P., Trubiani, C., & Ventresque, A. (2022). Mutation-based analysis of queueing network performance models. Journal of Systems and Software, 191. doi:10.1016/j.jss.2022.111385

Sampath, S., & Ventresque, A. (2023). Message from the ICST 2023 General Chairs. Proceedings - 2023 IEEE 16th International Conference on Software Testing, Verification and Validation, ICST 2023, XIII-XIV. doi:10.1109/ICST57152.2023.00006

Laurent, T., Klikovits, S., Arcaini, P., Ishikawa, F., & Ventresque, A. (2023). Parameter Coverage for Testing of Autonomous Driving Systems under Uncertainty. ACM Transactions on Software Engineering and Methodology, 32(3). doi:10.1145/3550270

Dr Anh Vu Vo

Lokugam Hewage, C. N., Laefer, D. F., Vo, A. V., Le-Khac, N. A., & Bertolotto, M. (2022). Scalability and Performance of LiDAR Point Cloud Data Management Systems: A State-of-the-Art Review. Remote Sensing, 14(20). doi:10.3390/rs14205277

Vo, A. V., Bertolotto, M., Ofterdinger, U., & Laefer, D. F. (2023). In Search of Basement Indicators from Street View Imagery Data: An Investigation of Data Sources and Analysis Strategies. KI - Kunstliche Intelligenz, 37(1), 41-53. doi:10.1007/s13218-022-00792-4

Dr Shen Wang

McEnroe, P., Wang, S., & Liyanage, M. (2022). A Survey on the Convergence of Edge Computing and AI for UAVs: Opportunities and Challenges. IEEE Internet of Things Journal, 9(17), 15435-15459. doi:10.1109/JIOT.2022.3176400

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, 71(11), 11421-11430. doi:10.1109/TVT.2022.3189410

Sandeepa, C., Siniarski, B., Kourtellis, N., Wang, S., & Liyanage, M. (2022). A survey on privacy for B5G/6G: New privacy challenges, and research directions. Journal of Industrial Information Integration, 30. doi:10.1016/j.jii.2022.100405

Guo, J., Cheng, L., & Wang, S. (2023). CoTV: Cooperative Control for Traffic Light Signals and Connected Autonomous Vehicles Using Deep Reinforcement Learning. IEEE Transactions on Intelligent Transportation Systems. doi:10.1109/TITS.2023.3276416

Li, S., Li, J., Pei, J., Wu, S., Wang, S., & Cheng, L. (2023). Eco-CSAS: A Safe and Eco-Friendly Speed Advisory System for Autonomous Vehicle Platoon Using Consortium Blockchain. IEEE Transactions on Intelligent Transportation Systems, 24(7), 7802-7812. doi:10.1109/TITS.2022.3232851

Ms Lan Wei

Wei, L., Ventura, S., Ryan, M. A., Mathieson, S., Boylan, G. B., Lowery, M., & Mooney, C. (2022). Deep-spindle: An automated sleep spindle detection system for analysis of infant sleep spindles. Computers in Biology and Medicine, 150. doi:10.1016/j.compbiomed.2022.106096

Du, Y., Rafferty, A. R., McAuliffe, F. M., Wei, L., & Mooney, C. (2022). An explainable machine learning-based clinical decision support system for prediction of gestational diabetes mellitus. Scientific Reports, 12(1). doi:10.1038/s41598-022-05112-2

Du, Y., McNestry, C., Wei, L., Antoniadi, A. M., McAuliffe, F. M., & Mooney, C. (2023). Machine learning-based clinical decision support systems for pregnancy care: A systematic review. International Journal of Medical Informatics, 173. doi:10.1016/j.ijmedinf.2023.105040

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