Expert Profile
Padhraic Smyth

Distinguished Professor of Computer Science and Director of the Data Science Initiative
Padhraic Smyth studies machine learning, artificial intelligence, pattern recognition and applied statistics.
Areas of Expertise
- Machine Learning
- Artificial Intelligence
- Pattern Recognition
- Statistics
Biography
Padhraic Smyth holds the Hasso Plattner Endowed Chair in Artificial Intelligence and is a Distinguished Professor in the Department of Computer Science at UC Irvine. He also has joint faculty appointments in the Department of Statistics and in the Department of Education. His research interests include machine learning, artificial intelligence, pattern recognition, and applied statistics and he has published over 200 papers on these topics. He is an ACM Fellow, IEEE Fellow, AAAI Fellow and AAAS Fellow, and was a recipient of the ACM SIGKDD Innovation Award. He is co-author of the text Modeling the Internet and the Web: Probabilistic Methods and Algorithms (Wiley, 2003) and Principles of Data Mining (MIT Press, 2001). He served as program chair of the ACM SIGKDD 2011 and UAI 2013 conferences, associate program chair for IJCAI 2022, general chair for AI-Stats 1997, and in various senior/area chair positions for conferences such as NeurIPS, ICML, and AAAI. He has also served in editorial and advisory positions for journals such as the Journal of Machine Learning Research, the Journal of the American Statistical Association, and the IEEE Transactions on Knowledge and Data Engineering.
Padhraic was the founding director of the UCI Center for Machine Learning and Intelligent Systems from 2007 to 2014 and founding director from 2014 to 2018 of the UCI Data Science Initiative. While at UC Irvine he has received research funding from agencies such as NSF, NIH, IARPA, NASA, NIST, ONR, and DOE, and from companies such as Google, Qualcomm, Microsoft, eBay, Adobe, IBM, SAP, Xerox, and Experian. In addition to his academic research he is also active in industry consulting, working with companies such as Toshiba, Samsung, Oracle, Nokia, and AT&T, as well as serving as scientific advisor to local startups in Orange County. He also served as an academic advisor to Netflix for the Netflix prize competition from 2006 to 2009.
Padhraic grew up in Kilmovee, County Mayo, in the west of Ireland and received a first class honors degree in Electronic Engineering from National University of Ireland (University of Galway) in 1984, and the MSEE and PhD degrees (in 1985 and 1988 respectively) in Electrical Engineering from the California Institute of Technology. From 1988 to 1996 he was a researcher at the Jet Propulsion Laboratory, Pasadena, and has been on the faculty at UC Irvine since 1996.
Media





Media Appearances
How UCI and AI go waaay back
Newswise, 12/4/2023
A call to hit the ‘pause’ button on AI experiments
University of California, 4/7/2023
Event Appearances
Bayesian consensus prediction for correlated human experts and classifiers
2025 | International Conference on Machine Learning (ICML) (Vancouver, Canada)
Understanding gender bias in AI-generated product description
2025 | ACM Conference on Fairness, Accountability, and Transparency (ACM FAccT) (Athens, Greece)
ELBOing Stein: Variational Bayes with Stein mixture inference
2025 | International Conference on Learning Representations (Singapore)
Dynamic conditional optimal transport through simulation-free flows
2024 | Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (Vancouver, Canada)
Benchmark data repositories for better benchmarking
2024 | Proceedings of the Thirty-Eighth Annual Conference on Neural Information Processing Systems (Vancouver, Canada)
Articles
JANET: Joint adaptive prediction-region estimation for time-series
Machine Learning
What large language models know and what people think they know
Nature Machine Intelligence
A generative diffusion model for probabilistic ensembles of precipitation maps conditioned on multisensor satellite observations
IEEE Transactions on Geoscience and Remote Sensing
Dynamic conditional optimal transport through simulation-free flows
Advances in Neural Information Processing Systems
Likelihood ratios for changepoints in categorical event data with applications in digital forensics
Journal of Forensic Sciences
Education
California Institute of Technology
Ph.D., Electrical Engineering, 1988
California Institute of Technology
MSEE, Electrical Engineering, 1985
National University of Ireland
BE, Engineering (Electronic), 1984
Accomplishments
- Outstanding Paper with Lead Student Author, International Conference on AI and Statistics
- Qualcomm Faculty Award
- Fellow, Institute for Electrical and Electronic Engineers (IEEE)
- Fellow, American Association for the Advancement of Science (AAAS)
- Best Paper, Educational Data Mining Conference (EDM)
Patents
Hidden Markov Models for Fault Detection in Dynamic Systems,
U.S. Patent no. 5465321
Cross-Connect Switch and Method for Providing Test Access Thereto,
U.S. Patent no. 4845736
Cross-Connect Switch
U.S. Patent no. 4807280
Affiliations
- AAAI President’s Fellows Advisory Board : Member, 2019–present
Research Grants
CAIG: Advancing Wildfire Science, Prediction, and Management with Machine Learning
NSF 2425932, 10/2024-9/2027
Time Series Prediction with Deep Learning
Google, 9/2024
Individualized Learning and Prediction for Heterogeneous Multimodal Data from Wearable Devices
NIH R01 CA297869-01,, 7/2024-6/2028
AI/ML and Data Science Training Datasets
NIH 3OT2OD032581,, 1/2023-3/2024
Improving Prediction of Fire Extremes in the GEOS Forecasting System on Daily and Seasonal Timescales,
NASA, 9/2021-6/2025