School of Computer Science and Statistics

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Trinity College Dublin
Dublin 2
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. Over the years, my dedication to research and teaching was recognized, culminating in my appointment as Professor by the Dublin Institute of Technology in 2017. 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
  • 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
  • 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
  • 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
  • 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
  • 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
  • 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

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. * "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. * "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) * "Topic Aware Probing: From Sentence Length Prediction to Idiom Identification" (arXiv preprint, 2024) * "Local or Global: The Variation in the Encoding of Style Across Sentiment and Formality" (International Conference on Artificial Neural Networks, 2023) * "Idioms, Probing and Dangerous Things: Towards Structural Probing for Idiomaticity in Vector Space" (Proceedings of the 19th Workshop on Multiword Expressions, 2023) * "Adaptive Machine Translation with Large Language Models" (Proceedings of the 24th Annual Conference of the European Association for Machine Translation, 2023) Ny work on AI for Medicine primarily revolve 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) * "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) * "Age-specific models to capture the change in risk factor contribution by age to short-term primary ischemic stroke risk" (Frontiers in Neurology, 2022)

Information & Communication Technology, Computer science - Artificial Intelligence,