Pierre Baldi
Biography
Pierre Baldi, Ph.D., is Distinguished Professor in the Department of Computer Science, founding Director of the AI in Science Institute, and founding Associate Director of the Center for Machine Learning and Intelligent Systems at the University of California, Irvine. He holds joint appointments in the Departments of Biomedical Engineering, Mathematics, and Statistics. Baldi received his Ph.D. in Mathematics from the California Institute of Technology in 1986.
Baldi has made contributions across artificial intelligence, machine learning, and their applications to the natural sciences. His work spans deep learning theory, including foundational studies on autoencoders, dropout learning algorithms, and neural network capacity, as well as applications in high-energy physics, chemistry, genomics, and neuroscience. He has developed machine learning methods for particle physics experiments including ATLAS, NOvA, and DUNE, created computational tools for chemical reaction prediction and drug discovery, and built bioinformatics systems for protein structure prediction and genomic analysis. His research on circadian rhythms has integrated computational approaches with experimental biology to understand metabolic regulation across multiple organ systems.
Baldi is an elected Fellow of the Association for the Advancement of Artificial Intelligence, the American Association for the Advancement of Science, the Institute of Electrical and Electronics Engineers, the Association for Computing Machinery, and the International Society for Computational Biology. He received the 2023 Dennis Gabor Award from the International Neural Network Society and was elected a Foreign Member of the Academy of Sciences of the Bologna Institute in 2024. He has authored over 380 refereed journal articles and five books, including "Deep Learning in Science" and "Bioinformatics: The Machine Learning Approach." From 2001 to 2024, he served as founding Director of the Institute for Genomics and Bioinformatics at UCI.
Return to topEducation
- Ph.D. in Mathematics, California Institute of Technology, 1986
- MS in Computer Science and Engineering, ENSTA, Paris, 1983
- D.E.A in Mathematics, University of Paris VII, 1981
- MS in Mathematics, University of Paris VII, 1980
- MS in Psychology, University of Paris X, 1980
Distinctions
- Elected short-term associated member of ATLAS at CERN, 2015
- Elected Foreign Member of the Academy of Sciences of the Bologna Institute, 2024
- Fellow American Association Advancement of Science (AAAS), 2008
- Member of National Academy of Artificial Intelligence (NAAI), 2025
- Dennis Gabor Award from the International Neural Network Society (INNS), 2023
- Member of NOvA (neutrino experiment consortium), 2017
- Fellow International Society for Computational Biology (ISCB), 2013
- Fellow Association Advancement Artificial Intelligence (AAAI), 2007
- Eduardo R. Caianiello Prize for Scientific Contributions to the Field of Neural Networks, 2010
- Fellow Asia-Pacific Artificial Intelligence Association (AAIA), 2022
Areas of Expertise
- Artificial Intelligence and Machine Learning
- Deep Learning Architectures
- Protein Structure Prediction
- Chemical Reaction Prediction
- Circadian Rhythm Genomics
- High Energy Physics Analysis
- Neutrino Detection Methods
Recent Publications
- Emami S.H., Meibody A.P., Tayebi L., Tavakoli M., Baldi P., “Unraveling the molecular magic: AI explains the formation of the most stretchable hydrogel” (opens in new tab), Reaction Chemistry and Engineering, vol. 11, pp. 346-358, 2026.
- Ryan J. Miller, Alexander E. Dashuta, Brayden Rudisill, David Van Vranken, Pierre Baldi, “Mechanism-Aware Deep Learning for Polar Reaction Prediction” (opens in new tab), Journal of the American Chemical Society (JACS), vol. 147, pp. 41168-41176, 2025.
- M. Acero, B. Acharya, P. Adamson, L. Aliaga, N. Anfimov, A. Antoshkin, E. Arrieta-Diaz, L. Asquith, A. Aurisano, A. Back, C. Backhouse, M. Baird, N. Balashov, P. Baldi, “Monte Carlo method for constructing confidence intervals with unconstrained and constrained nuisance parameters in the NOvA experiment” (opens in new tab), Journal of Instrumentation, vol. 20, no. 02, pp. PT02001, 2025.
- MA Acero, B Acharya, P Adamson, N Anfimov, A Antoshkin, E Arrieta-Diaz, L Asquith, A Aurisano, A Back, N Balashov, P Baldi, “Dual-Baseline Search for Active- to-Sterile Neutrino Oscillations in NOvA” (opens in new tab), Physical Review Letters, vol. 134, no. 8, pp. P081804, 2025.
- EE Robles, A Yankelevich, W Wu, J Bian, P Baldi, “Particle hit clustering and identification using point set transformers in liquid argon time projection chambers” (opens in new tab), Journal of Instrumentation, vol. 20, no. 07, pp. P07030, 2025.
- D. Lin, J. Earls, L. Ma, A. Boag, P. Baldi, “Optimization of Antenna Array Configurations Using Deep Learning” (opens in new tab), IEEE Open Journal of Antennas and Propagation, vol. 6, no. 5, pp. 1367-1374, 2025.
- Sarullo, Kathryn, Samad, Muntaha, Kendale, Samir, Baldi, Pierre, Swamidass, S. Joshua, “Domain Knowledge Inclusive Monotonic Neural Network Guides Patient-Specific Induction of General Anesthesia Dosing” (opens in new tab), Anesthesia and Analgesia Practice, vol. 19, no. 8, pp. e02034, 2025.
- S. Abdelkarim, S. Jaeggi, P. Baldi, “Evaluating the Intelligence of Large Language Models: A Comparative Study Using Verbal and Visual IQ Tests”, Computers in Human Behavior: Artificial Humans, pp. 100170, 2025.
- P. Baldi, A. Alexos, I. Domingo, A. Rahmansetayesh, “A Theory of Synaptic Neural Balance: From Local to Global Order” (opens in new tab), Artificial Intelligence, vol. 346, pp. P104360, 2025.
- M. Tavakoli, Y. T. Chiu, A. M. Carlton, D. Van Vranken, P. Baldi, “Chemically Informed Deep Learning for Interpretable Radical Reaction Prediction” (opens in new tab), Journal of Chemical Information and Modeling, vol. 65, no. 3, pp. P1228-1242, 2025.
- A Abed Abud, B Abi, R Acciarri, MA Acero, “The track-length extension fitting algorithm for energy measurement of interacting particles in liquid argon TPCs and its performance with ProtoDUNE-SP data” (opens in new tab), Journal of Instrumentation, vol. 20, no. 02, pp. P02021, 2025.
- A. Abed Abud, R. Acciarri, M. Acero, M. Adames, “Neutrino Interaction Vertex Reconstruction in DUNE with Pandora Deep Learning” (opens in new tab), The European Physical Journal C, vol. 85, pp. 697, 2025.
- A. Abed Abud, B. Abi, R. Acciarri, M. Acero, “Supernova pointing capabilities of DUNE” (opens in new tab), Physical Review D, vol. 111, no. 9, pp. P092006, 2025.
- MA Acero, B Acharya, P Adamson, L Aliaga, “Measurement of d2sigma/d| q| dEavail in charged current neutrino-nucleus interactions at< Ev>= 1.86 GeV using the NOvA Near Detector”, Physical Review D, vol. 111, no. 5, 2025.
- P. Baldi, P. Fariselli, G. Parisi, “Build an international AI "telescope" to curb the power of big tech companies”, Nature, vol. 634, no. 8035, pp. 782-782, 2024.
- J. Dagoon, P.F. Baldi, S. Abdelkarim, J. Liu, M.E. Riazi, M. Andrade, A. Azzam, P.R. Esfahani, S. Chang, A. Browne, “Annotation of surgical tool depth in vitreoretinal surgical videos: Agreement and performance between vitreoretinal surgeons vs. non-surgeon graders”, Investigative Ophthalmology & Visual Science, vol. 65, no. 07, pp. P3762-3762, 2024.
- Kiki Chen, Kousha Changizi Ashtiani, Roudabeh Vakil Monfared, Pierre Baldi, Amal Alachkar, “Circadian Cilia Transcriptome in Mouse Brain Across Physiological and Pathological States” (opens in new tab), Molecular Brain, vol. 17, pp. 67, 2024.
- M. Fenton, A. Schmakov, H. Okawa, Y. Li, K. Hsiao, S. Hsu, D. Whiteson, P. Baldi, “Reconstruction of Unstable Heavy Particles Using Deep Symmetry-Preserving Attention Networks” (opens in new tab), Nature Communications Physics, vol. 7, pp. 139, 2024.
- Tavakoli, Mohammadamin, Miller, Ryan, Angel, Mirana, Pfeiffer, Michael, Gutman, Eugene, Mood, Aaron, Van Vranken, David, Baldi, Pierre, “PMechDB: A Public Database of Elementary Polar Reaction Steps” (opens in new tab), Journal of Chemical Information and Modeling, vol. 64, no. 6, pp. 1975–1983, 2024.
Most Cited Publications
- P. Baldi, S. Brunak, Y. Chauvin, H. Nielsen, “Assessing the Accuracy of Prediction Algorithms for Classification: An Overview” (opens in new tab), Bioinformatics, vol. 16, no. 5, pp. 412-424, 2000.
- S. Shao, S. McAleer, R. Yan, P. Baldi, “Highly-Accurate Machine Fault Diagnosis Using Deep Transfer Learning” (opens in new tab), IEEE Transactions on Industrial Informatics (TII), vol. 15, no. 4, pp. 2446-2455, 2018.
- P. Baldi, A. D. Long, “A Bayesian Framework for the Analysis of Microarray Expression Data: Regularized t-Test and Inference of Gene Changes” (opens in new tab), Bioinformatics, vol. 17, no. 6, pp. 509-519, 2001.
- P. Baldi, K. Hornik, “Neural Networks and Principal Component Analysis: Learning from Examples without Local Minima” (opens in new tab), Neural Networks, vol. 2, no. 1, pp. 53-58, 1988.
- Baldi P., Sadowski P., Whiteson D., “Searching for exotic particles in high-energy physics with deep learning” (opens in new tab), Nature Communications, vol. 5, 2014.
- J. Cheng, A. Randall, P. Baldi, “Prediction of Protein Stability Changes for Single Site Mutations Using Support Vector Machines” (opens in new tab), Proteins Structure Function and Genetics, vol. 62, no. 4, pp. 1125-1132, 2006.
- J. Cheng, A. Z. Randall, M. Sweredoski, P. Baldi, “SCRATCH: a Protein Structure and Structural Feature Prediction Server” (opens in new tab), Nucleic Acids Research, vol. 33, no. 9, pp. W72-76, 2005.
- L. Itti, P. Baldi, “Bayesian Surprise Attracts Human Attention” (opens in new tab), Vision Research, vol. 49, no. 10, pp. 1295-1306, 2009.
- M. Brandon, P. Baldi, D. C. Wallace, “Mitochondrial Mutations in Cancer” (opens in new tab), Oncogene, vol. 25, no. 34, pp. 4647-4662, 2006.
- G. Pollastri, D. Przybylski, B. Rost, P. Baldi, “Improving the Prediction of Protein Secondary Structure in Three and Eight Classes Using Recurrent Neural Networks and Profiles” (opens in new tab), Proteins Structure Function and Genetics, vol. 47, no. 2, pp. 228-235, 2002.
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Last updated on 5/23/2026.