School of Computer Science and Statistics

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Trinity College Dublin
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Ireland

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Professor John Kelleher

Professor John Kelleher

Professor of Computer Science, Computer Science


Biography

I am the Director of the ADAPT Research Center (www.adaptcentre.ie) and the Professor of Computer Science (2016) at the School of Computer Science and Statistics at Trinity College Dublin. My journey in academia began with a BSc. in Computer Applications from Dublin City University in 1997. In 2003, I completed my PhD in Artificial Intelligence, also at Dublin City University, focusing on the intersection of language and vision within the context of situated dialogue. This research studied how humans interact with robots or virtual environments through language, paving the way for advancements in human-computer dialogue systems, and artificial intelligence. Following my doctoral studies, I worked as a post-doctoral researcher at Media Lab Europe and the German Centre for Artificial Intelligence (DFKI). In 2005, I joined the faculty of the School of Computer Science at the Dublin Institute of Technology, later transitioning to Technological University Dublin. In 2017 my research and teaching work was recognized with my appointment as Professor by the Dublin Institute of Technology. I joined the Hamilton Research Institute at Maynooth University as a Professor of Computer Science in 2023. In 2024, I was appointed to the role of Professor of Computer Science at Trinity College Dublin's School of Computer Science and Statistics. Concurrently, I lead the ADAPT Research Center, driving innovation and collaboration in the dynamic field of computer science.

Publications and Further Research Outputs

  • Fernandez-Lopez, Adriana and Karaali, Ali and Harte, Naomi and Sukno, Federico M, ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020, pp6294--6298Conference Paper, 2020, URL
  • Kacmajor, M. and Kelleher, J.D., Capturing and measuring thematic relatedness, Language Resources and Evaluation, 54, (3), 2020, p645-682Journal Article, 2020, DOI , URL , TARA - Full Text
  • Mahalunkar, A. and Kelleher, J.D., Mutual Information Decay Curves and Hyper-parameter Grid Search Design for Recurrent Neural Architectures, Communications in Computer and Information Science, 1333, 2020, p616-624Journal Article, 2020, DOI , URL , TARA - Full Text
  • Trinh, A.D. and Ross, R.J. and Kelleher, J.D., F-Measure Optimisation and Label Regularisation for Energy-Based Neural Dialogue State Tracking Models, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12397 LNCS, 2020, p798-810Journal Article, 2020, DOI , URL , TARA - Full Text
  • Dobnik, S. and Kelleher, J.D. and Howes, C., Local Alignment of Frame of Reference Assignment in English and Swedish Dialogue, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12162 LNAI, 2020, p251-267Journal Article, 2020, DOI , URL , TARA - Full Text
  • Kerr, A. and Barry, M. and Kelleher, J.D., Expectations of artificial intelligence and the performativity of ethics: Implications for communication governance, Big Data and Society, 7, (1), 2020Journal Article, 2020, DOI , URL , TARA - Full Text
  • Mahalunkar, A. and Kelleher, J.D., Using regular languages to explore the representational capacity of recurrent neural architectures, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11141 LNCS, 2018, p189-198Journal Article, 2018, DOI , URL
  • Peru Bhardwaj, John Kelleher, Luca Costabello, Declan O'Sullivan, Adversarial Attacks on Knowledge Graph Embeddings via Instance Attribution Methods, 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP), Online and Punta Cana, Dominican Republic, November 2022, edited by Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih , Association for Computational Linguistics, 2021, pp8225-8239Conference Paper, 2021, DOI
  • Hunter, E. and Kelleher, J.D., Using a hybrid agent-based and equation based model to test school closure policies during a measles outbreak, BMC Public Health, 21, (1), 2021Journal Article, 2021, DOI , URL , TARA - Full Text
  • Garcia-Rudolph, A. and Opisso, E. and Tormos, J.M. and Madai, V.I. and Frey, D. and Becerra, H. and Kelleher, J.D. and Guitart, M.B. and López, J., Toward personalized web-based cognitive rehabilitation for patients with ischemic stroke: Elo rating approach, JMIR Medical Informatics, 9, (11), 2021Journal Article, 2021, DOI , URL
  • Hunter, E. and Kelleher, J.D., Adapting an agent-based model of infectious disease spread in an irish county to covid-19, Systems, 9, (2), 2021Journal Article, 2021, DOI , URL , TARA - Full Text
  • Jafaritazehjani, S. and Lecorvé, G. and Lolive, D. and Kelleher, J.D., Style as Sentiment Versus Style as Formality: The Same or Different?, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 12895 LNCS, 2021, p487-499Journal Article, 2021, DOI , URL
  • HerrgÃ¥rdh, T. and Madai, V.I. and Kelleher, J.D. and Magnusson, R. and Gustafsson, M. and Milani, L. and Gennemark, P. and Cedersund, G., Hybrid modelling for stroke care: Review and suggestions of new approaches for risk assessment and simulation of scenarios, NeuroImage: Clinical, 31, (102694), 2021Journal Article, 2021, DOI , URL , TARA - Full Text
  • Jennifer Scott, Enock Havyarimana, Albert Navarro-Gallinad, Arthur White, Jason Wyse, Jos van Geffen, Michiel van Weele, Antonia Buettner, Tamara Wanigasekera, Cathal Walsh, Louis Aslett, John D Kelleher, Julie Power, James Ng, Declan O'Sullivan, Lucy Hederman, Neil Basu, Mark A Little, Lina Zgaga, The association between ambient UVB dose and ANCA-associated vasculitis relapse and onset, Arthritis Research & Therapy, 24, (1), 2022, p1 - 14Journal Article, 2022, DOI
  • Nicholson, M. and Agrahari, R. and Conran, C. and Assem, H. and Kelleher, J.D., The interaction of normalisation and clustering in sub-domain definition for multi-source transfer learning based time series anomaly detection, Knowledge-Based Systems, 257, (109894), 2022Journal Article, 2022, DOI , URL
  • Martinez, H.B. and Cisek, K. and García-Rudolph, A. and Kelleher, J.D. and Hines, A., Understanding and Predicting Cognitive Improvement of Young Adults in Ischemic Stroke Rehabilitation Therapy, Frontiers in Neurology, 13, (886477), 2022Journal Article, 2022, DOI , URL
  • Nayak, P. and Haque, R. and Kelleher, J.D. and Way, A., Investigating Contextual Influence in Document-Level Translation, Information (Switzerland), 13, (5), 2022Journal Article, 2022, DOI , URL
  • Nedumpozhimana, V. and KlubiÄ ka, F. and Kelleher, J.D., Shapley Idioms: Analysing BERT Sentence Embeddings for General Idiom Token Identification, Frontiers in Artificial Intelligence, 5, (813967), 2022Journal Article, 2022, DOI , URL
  • Hunter, E. and Kelleher, J.D., Age Specific Models to Capture the Change in Risk Factor Contribution by Age to Short Term Primary Ischemic Stroke Risk, Frontiers in Neurology, 13, (803749), 2022Journal Article, 2022, DOI , URL
  • García-Rudolph, A. and Saurí, J. and Cegarra, B. and Madai, V.I. and Frey, D. and Kelleher, J.D. and Cisek, K. and Opisso, E. and Tormos, J.M. and Bernabeu, M., Long-term trajectories of motor functional independence after ischemic stroke in young adults: Identification and characterization using inpatient baseline assessments, NeuroRehabilitation, 50, (4), 2022, p453-465Journal Article, 2022, DOI , URL
  • Hunter, E. and McGarry, B.L. and Kelleher, J.D., Simulating Delay in Seeking Treatment for Stroke Due to COVID-19 Concerns with a Hybrid Agent-Based and Equation-Based Model, 2022, pp379-391Conference Paper, 2022, DOI , URL
  • Hunter, E. and Kelleher, J.D., A review of risk concepts and models for predicting the risk of primary stroke, Frontiers in Neuroinformatics, 16, (883762), 2022Journal Article, 2022, DOI , URL
  • Hunter, E. and Saha, S. and Kumawat, J. and Carroll, C. and Kelleher, J.D. and Buckley, C. and McAloon, C. and Kearney, P. and Gilbert, M. and Martin, G., Assessing the impact of contact tracing with an agent-based model for simulating the spread of COVID-19: The Irish experience, Healthcare Analytics, 4, (100229), 2023Journal Article, 2023, DOI , URL
  • García-Rudolph, A. and Sanchez-Pinsach, D. and Frey, D. and Opisso, E. and Cisek, K. and Kelleher, J.D., Know an Emotion by the Company It Keeps: Word Embeddings from Reddit/Coronavirus, Applied Sciences (Switzerland), 13, (11), 2023Journal Article, 2023, DOI , URL
  • Lindh, A. and Ross, R. and Kelleher, J.D., Show, Prefer and Tell: Incorporating User Preferences into Image Captioning, 2023, pp1139-1142Conference Paper, 2023, DOI , URL
  • Mehak, S. and Leva, M.C. and Kelleher, J.D. and Guilfoyle, M., Action Classification in Human Robot Interaction Cells in Manufacturing: Moving Towards Mutual Performance Monitoring Capacity, 2023, pp214-220Conference Paper, 2023, DOI , URL
  • Hunter, E. and Kelleher, J.D., Determining the Proportionality of Ischemic Stroke Risk Factors to Age, Journal of Cardiovascular Development and Disease, 10, (2), 2023Journal Article, 2023, DOI , URL
  • English, P.C. and Kelleher, J.D. and Carson-Berndsen, J., Discovering Phonetic Feature Event Patterns in Transformer Embeddings, 2023-August, 2023, pp4733-4737Conference Paper, 2023, DOI , URL
  • Cisek, K. and Kelleher, J.D., Current Topics in Technology-Enabled Stroke Rehabilitation and Reintegration: A Scoping Review and Content Analysis, IEEE Transactions on Neural Systems and Rehabilitation Engineering, 31, 2023, p3341-3352Journal Article, 2023, DOI , URL
  • Garcia-Rudolph, A. and Sauri, J. and Cisek, K. and Kelleher, J.D. and Madai, V.I. and Frey, D. and Opisso, E. and Tormos, J.M. and Bernabeu, M., Long-term trajectories of community integration: identification, characterization, and prediction using inpatient rehabilitation variables, Topics in Stroke Rehabilitation, 30, (7), 2023, p714-726Journal Article, 2023, DOI , URL
  • Sardina, J. and Sardina, C. and Kelleher, J.D. and O†Sullivan, D., Analysis of Attention Mechanisms in Box-Embedding Systems, Communications in Computer and Information Science, 1662 CCIS, 2023, p68-80Journal Article, 2023, DOI , URL
  • Agrahari, R. and Nicholson, M. and Conran, C. and Assem, H. and Kelleher, J.D., Assessing Feature Representations for Instance-Based Cross-Domain Anomaly Detection in Cloud Services Univariate Time Series Data, IoT, 3, (1), 2022, p123-144Journal Article, 2022, DOI , URL
  • Abbas, A.N. and Chasparis, G.C. and Kelleher, J.D., Hierarchical framework for interpretable and specialized deep reinforcement learning-based predictive maintenance, Data and Knowledge Engineering, 149, (102240), 2024Journal Article, 2024, DOI , URL
  • Nedumpozhimana, V. and Rautmare, S. and Gower, M. and Popovic, M. and Jain, N. and Buffini, P. and Kelleher, J., Medical Concept Mention Identification in Social Media Posts using a Small Number of Sample References, 2023, pp777-784Conference Paper, 2023, DOI , URL
  • Moslem, Y. and Romani, G. and Molaei, M. and Haque, R. and Kelleher, J.D. and Way, A., Domain Terminology Integration into Machine Translation: Leveraging Large Language Models, 2023, pp900-909Conference Paper, 2023, URL
  • KlubiÄ ka, F. and Nedumpozhimana, V. and Kelleher, J.D., Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space, 2023, pp45-57Conference Paper, 2023, URL
  • Jafaritazehjani, S. and Lecorvé, G. and Lolive, D. and Kelleher, J.D., Local or Global: The Variation in the Encoding of Style Across Sentiment and Formality, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 14263 LNCS, 2023, p492-504Journal Article, 2023, DOI , URL
  • Jennifer Scott, Arthur White, Cathal Walsh, Louis Aslett, Matthew A Rutherford, James Ng, Conor Judge, Kuruvilla Sebastian, Sorcha O'Brien, John Kelleher, Julie Power, Niall Conlon, Sarah M Moran, Raashid Ahmed Luqmani, Peter A Merkel, Vladimir Tesar, Zdenka Hruskova Mark A Little, Computable phenotype for real-world, data-driven retrospective identification of relapse in ANCA-associated vasculitis, RMD Open, 10, (2), 2024, p1-11Journal Article, 2024, DOI
  • John D. Kelleher, Understanding the assumptions of an SEIR compartmental model using agentization and a complexity hierarchy, Journal of Computational Mathematics and Data Science, 4, 2022, p100056Journal Article, 2022, DOI
  • Tilda Herrgårdh, Elizabeth Hunter, Kajsa Tunedal, Håkan Örman, Julia Amann, Francisco Abad Navarro, Catalina Martinez-Costa, John D. Kelleher, Gunnar Cedersund, Digital twins and hybrid modelling for simulation of physiological variables and stroke risk, 2022Journal Article, 2022, DOI
  • Zihni, Esra and Kelleher , John D. and McGarry, Bryony, An Analysis of the Interpretability of Neural Networks trained on Magnetic Resonance Imaging for Stroke Outcome Prediction , Proceedings of the International Society for Magnetic Resonance in Medicine, 2021Journal Article, 2021, DOI
  • Katryna Cisek and Thi Nguyet Que Nguyen and Alejandro Garcia-Rudolph and Joan Saur{\'{\i, Understanding Social Risk Variation Across Reintegration of Post-Ischemic Stroke Patients, Cerebral Ischemia, 2021, p201--220Journal Article, 2021, DOI
  • Elizabeth Hunter, Brian Mac Namee, John D. Kelleher, A Model for the Spread of Infectious Diseases in a Region, International Journal of Environmental Research and Public Health, 17, (9), 2020, p3119Journal Article, 2020, DOI
  • Annika Lindh, Robert J. Ross, Abhijit Mahalunkar, Giancarlo Salton, John D. Kelleher, Generating Diverse and Meaningful Captions, 2018, p176--187Journal Article, 2018, DOI
  • Cisek K.K., Nguyen T.N.Q., Garcia-Rudolph A., Sauri J., Becerra Martinez H., Hines A., Kelleher J.D., Predictors of social risk for post-ischemic stroke reintegration, Scientific Reports, 14, (1), 2024Journal Article, 2024, DOI
  • Mehak S., Kelleher J.D., Guilfoyle M., Leva M.C., Action Recognition for Human"Robot Teaming: Exploring Mutual Performance Monitoring Possibilities, Machines, 12, (1), 2024Journal Article, 2024, DOI
  • Sardina, Jeffrey and Kelleher, John D. and O'Sullivan, Declan, TWIG: Towards pre-hoc Hyperparameter Optimisation and Cross-Graph Generalisation via Simulated KGE Models, 2024 IEEE 18th International Conference on Semantic Computing (ICSC), 2024 IEEE 18th International Conference on Semantic Computing (ICSC), 2024, pp122-129Conference Paper, 2024, DOI
  • English, Patrick Cormac and Shams, Erfan A. and Kelleher, John D. and Carson-Berndsen, Julie, Following the Embedding: Identifying Transition Phenomena in Wav2vec 2.0 Representations of Speech Audio, IEEE Xplore, ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Seoul, Korea, Republic of, 14-19 April 2024, IEEE, 2024, pp6685 - 6689Conference Paper, 2024, DOI
  • John D. Kelleher, Deep Learning, 1st Edition, MIT Press, The MIT Press, 2019, 1 - 296ppBook, 2019, URL
  • Martinez H.B., Cisek K., Garcia-Rudolph A., Kelleher J.D., Hines A., Transparently Predicting Therapy Compliance of Young Adults Following Ischemic Stroke, Communications in Computer and Information Science, 2156 CCIS, 2024, p24 - 41, p24-41Journal Article, 2024, DOI
  • Abbas, A.N. and Amazu, C.W. and Mietkiewicz, J. and Briwa, H. and Perez, A.A. and Baldissone, G. and Demichela, M. and Chasparis, G.C. and Kelleher, J.D. and Leva, M.C., Analyzing Operator States and the Impact of AI-Enhanced Decision Support in Control Rooms: A Human-in-the-Loop Specialized Reinforcement Learning Framework for Intervention Strategies, International Journal of Human-Computer Interaction, 2024Journal Article, 2024, DOI , URL
  • Jain, A. and Long, P. and Villani, V. and Kelleher, J.D. and Chiara Leva, M., CoBT: Collaborative Programming of Behaviour Trees from One Demonstration for Robot Manipulation, 2024, pp12993-12999Conference Paper, 2024, DOI , URL
  • Hunter, E. and Kelleher, J.D., Estimating Population Burden of Stroke with an Agent-Based Model, Springer Proceedings in Complexity, 2024, p9-20Journal Article, 2024, DOI , URL
  • English, P.C. and Shams, E.A. and Kelleher, J.D. and Carson-Berndsen, J., FOLLOWING THE EMBEDDING: IDENTIFYING TRANSITION PHENOMENA IN WAV2VEC 2.0 REPRESENTATIONS OF SPEECH AUDIO, 2024, pp6685-6689Conference Paper, 2024, DOI , URL
  • KlubiÄ ka, F. and Kelleher, J.D., ReproHum #1018-09: Reproducing Human Evaluations of Redundancy Errors in Data-To-Text Systems, 2024, pp163-198Conference Paper, 2024, URL
  • PopoviÄ , M. and Nedumpozhimana, V. and Gower, M. and Rautmare, S. and Jain, N. and Kelleher, J., Using MT for multilingual covid-19 case load prediction from social media texts, 2023, pp461-470Conference Paper, 2023, URL
  • KlubiÄ ka, F. and Kelleher, J.D., HumEval†23 Reproduction Report for Paper 0040: Human Evaluation of Automatically Detected Over- and Undertranslations, 2023, pp153-189Conference Paper, 2023, DOI , URL
  • Belz, A. and Thomson, C. and Reiter, E. and Abercrombie, G. and Alonso-Moral, J.M. and Arvan, M. and Braggaar, A. and Cieliebak, M. and Clark, E. and van Deemter, K. and Dinkar, T. and DuÅ¡ek, O. and Eger, S. and Fang, Q. and Gao, M. and Gatt, A. and Gkatzia, D. and González-Corbelle, J. and Hovy, D. and HÃŒrlimann, M. and Ito, T. and Kelleher, J.D. and KlubiÄ ka, F. and Krahmer, E. and Lai, H. and van der Lee, C. and Li, Y. and Mahamood, S. and Mieskes, M. and van Miltenburg, E. and Mosteiro, P. and Nissim, M. and Parde, N. and Plátek, O. and Rieser, V. and Ruan, J. and Tetreault, J. and Toral, A. and Wan, X. and Wanner, L. and Watson, L. and Yang, D., Missing Information, Unresponsive Authors, Experimental Flaws: The Impossibility of Assessing the Reproducibility of Previous Human Evaluations in NLP, 2023, pp1-10Conference Paper, 2023, URL
  • Nayak, P. and Haque, R. and Kelleher, J.D. and Way, A., Instance-Based Domain Adaptation for Improving Terminology Translation, 1, 2023, pp222-234Conference Paper, 2023, URL
  • Moslem, Y. and Haque, R. and Kelleher, J.D. and Way, A., Adaptive Machine Translation with Large Language Models, 2023, pp227-237Conference Paper, 2023, URL
  • KlubiÄ ka, F. and Kelleher, J.D., Probing Taxonomic and Thematic Embeddings for Taxonomic Information, 2023, pp1-13Conference Paper, 2023, URL
  • Rubab, Maira and Kelleher, John D. , Assessing the relative importance of vitamin D deficiency in cardiovascular health, Frontiers in Cardiovascular Medicine, 11, 2024Journal Article, 2024, DOI , URL , TARA - Full Text
  • Nguyen, Thi Nguyet Que and García-Rudolph, Alejandro and Saurí, Joan and Kelleher, John D. , Multi-task learning for predicting quality-of-life and independence in activities of daily living after stroke: a proof-of-concept study, Frontiers in Neurology, 15, 2024Journal Article, 2024, DOI , URL , TARA - Full Text
  • Eduardo Cueto-Mendoza and John D. Kelleher, A framework for measuring the training efficiency of a neural architecture, Artificial Intelligence Review, 57, (349), 2024, p1 - 33Journal Article, 2024, DOI , TARA - Full Text

Research Expertise

My research interests and expertise lie at the intersection of Artificial Intelligence (AI), machine learning, natural language processing, and the field of AI for Medicine. I have authored several books in the fields of machine learning and data science, including: "Fundamentals of Machine Learning for Predictive Data Analytics: Algorithms, Worked Examples, and Case Studies" (MIT Press, 2020), co-authored with Brian Mac Namee and Aoife D'arcy; "Deep Learning" (MIT Press, 2019), offering a deep dive into this transformative branch of AI; and "Data Science" (MIT Press, 2018), co-authored with Brendan Tierney, offering an encompassing overview of this dynamic field. In the domain of natural language processing (NLP), my recent focus has been on unraveling the intricacies of large language models, particularly in understanding the types of linguistic information encoded within them. This research often involves probing the vector representations generated by these models. Other topics that I have worked on in this field of natural language processing include machine translation, and the related problem of natural language to source code generation. Examples of recent publications on these topics include: "Following the Embedding: Identifying Transition Phenomena in Wav2vec 2.0 Representations of Speech Audio" (ICASSP, 2024, doi: 10.1109/ICASSP48485.2024.10446494); "Topic Aware Probing: From Sentence Length Prediction to Idiom Identification" (arXiv preprint, 2024, doi: 10.48550/arXiv.2403.02009); "Local or Global: The Variation in the Encoding of Style Across Sentiment and Formality" (International Conference on Artificial Neural Networks, 2023, doi: 10.1007/978-3-031-44204-9_41); "Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space" (Proceedings of the 19th Workshop on Multiword Expressions, 2023, doi: 10.18653/v1/2023.mwe-1.8); and "Adaptive Machine Translation with Large Language Models" (Proceedings of the 24th Annual Conference of the European Association for Machine Translation, 2023, url: https://aclanthology.org/2023.eamt-1.22). My work on AI for Medicine primarily revolves around stroke research. Spanning various aspects including prevention, acute treatment, and rehabilitation, my recent publications in this domain include: "Predictors of social risk for post-ischemic stroke reintegration" (Scientific Reports, 2024, doi: 10.1038/s41598-024-60507-7); "Current Topics in Technology-Enabled Stroke Rehabilitation and Reintegration: A Scoping Review and Content Analysis" (IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2023); "A review of risk concepts and models for predicting the risk of primary stroke" (Frontiers in Neuroinformatics, 2022, doi: 10.3389/fninf.2022.883762); "Age-specific models to capture the change in risk factor contribution by age to short-term primary ischemic stroke risk" (Frontiers in Neurology, 2022, doi: 10.3389/fneur.2022.803749)

Computer and information sciences, Artificial intelligence and machine learning,

Recognition

  • Professor of TU Dublin 2017