ACTIVITIES
Mentoring and Supervision
2024- Ziyi Liang (with Annie Qu), Statistics, Postdoc UCI
2024- Zhishun Yang (with Norbert Fortin), Systems Biology, PhD UCI
2022- Yang Meng (with Stephan Mandt), Statistics, PhD UCI
2021- Zahra Moslemi, Statistics, PhD UCI
2020- Brian Schetzsle, Statistics, PhD UCI
2022-2024 Wenzhuo Zhou, Statistics, Postdoc (with Annie Qu) Assistant Professor, UCI
2020-2024 Yueqi Ren, Systems Biology, MD/PhD (with Craig Stark) MD Student, UCI
2022-2023 Rui Miao, Statistics, Postdoc (with Annie Qu) Mathematical Statistician, NIH
2018-2023 Derenik Haghverdian, Statistics, PhD (NSF-GRFP) Applied Scientist, Microsoft
2020-2022 Francesco Denti, Statistics, Postdoc Assistant Professor, U of Padua
2017-2022 Michelle Ngo, Systems Biology, PhD Data Scientist, Merck
2016-2021 Luis De Jesus Martinez Lomeli, Systems Biology, PhD Research Scientist, Metrum
2015-2020 Lingge Li, Statistics, PhD (with Pierre Baldi) Data Scientist, Meta
2014-2019 Tian Chen, Statistics, PhD Data Scientist, Cylance
2013-2018 Andrew Holborook, Statistics, PhD (NSF CAREER Award) Assistant Professor, UCLA
2012-2017 Cheng Zhang, Mathematics, PhD (with Hongkai Zhao) Assistant Professor, Peking U
2015-2017 Alexander Vandenberg-Rodes, Statistics, Postdoc Data Scientist, Obsidian Security
2011-2016 Sepehr Akhavan, Statistics, PhD (with Dan Gillen) Data Scientist, Meta
2010-2015 Bo Zhou, Statistics, PhD Principal Analyst, Capital One
2009-2013 Shiwei Lan, Statistics, PhD Associate Professor, ASU
Selected Invited Talks And Conference Presentations
Department of Biostatistics, UCLA, 2025
Biostatistics, UC San Diego, 2024
Department of Statistics and Actuarial Science, University of Waterloo, 2024.
IMS International Conference on Statistics and Data Science, Nice, France, 2024.
Advances in Inference and Theory for Bayesian Neural Networks, JSM 2024.
International Pediatric & lifespan Data Science Conference, Anaheim, 2024.
UCI Systems Biology, 2024.
Conceptualizing and Conducting Successful Training and Research Programs in Data Science, JSM 2023.
Data-Driven Mechanistic Models, Lawrence Livermore National Lab, 2022.
Improving Data Science Education Infrastructure at Community Colleges, Teaching, and Research Universities, JSM, 2022.
Latent Representation of Neural Data, ASU, 2021.
MCMC with surrogate functions, UCLA, 2020.
Workshop on Computational Statistics and Data-Driven Models (Virtual), Brown University, ICERM 2020.
Novel Statistical Methods for Complex Data, Vina del Mar, Chile, March 25 to 29, 2019.
Dynamic Bayesian models for Neural Data Analysis, 9th International Purdue Symposium on Statistics, June 2018
Decoding of Hippocampal Neural Activity Using Deep Learning Methods, Workshop on Deep Learning, Tokyo, March 2018
Wormhole Hamiltonian Monte Carlo, MCQMC at Stanford, August 2016
Variational Hamiltonian Monte Carlo, ICERM at Brown University, July 2016
Scalable Monte Carlo Methods, UCLA, October 28, 2015
Scalable Monte Carlo Methods, University of Texas at Austin, October 16, 2015
A Dynamic Bayesian Model for Cross-Neuronal Interactions, JSM, Seattle, August 13, 2015
Dependent Matern Process, 3rd Meeting on Statistics, Athens, June 2015
UCI Neurology Grand Rounds, October 2014
A Non-stationary Copula Model for Simultaneously-recorded Neurons, California State University, Fullerton, 2014
Dirichlet Process Mixture of Gaussian Processes for Joint Modeling of Longitudinal and Survival Data, ISBA 2014
A Gaussian Process Model for Estimating Within-Subject Volatility in Longitudinal Models, UCSD, Spring 2014
A Semiparametric Bayesian Model for Detecting Multiway Synchrony Among Neurons, ENAR 2014
Geometric Methods in Markov Chain Monte Carlo, UCSC, Spring 2014
A Gaussian Process Model for Estimating Within-Subject Volatility in Longitudinal Models, UCSD, Spring 2014
Dirichlet Process Mixture of Gaussian Processes for Joint Modeling of Longitudinal and Survival Data, ISBA 2014
Towards Scalable Bayesian Inference, Duke University, 2013
Split Hamiltonian Monte Carlo, JSM, 2013
Hamiltonian Monte Carlo and Its Variations, Department of Mathematics, UCI, 2013
Split Hamiltonian Monte Carlo, University of Washington, 2012
Bayesian Gene Set Analysis, MD Anderson, 2012
Bayesian Nonparametric Variable Selection, JSM, 2012
Bayesian Relevance Determination, California State University, Fullerton, 2012
Bayesian Relevance Determination, WNAR, 2011
Bayesian Gene Set Analysis, SDSU, 2010
Editorial Works And Reviews
Associate editor for JASA, Theory and Methods, 2023-Present
Associate editor for JASA/TAS Reviews, 2014-2019
Associate editor for CHANCE, 2011-2019
Member of Scientific Review Committee (SRC) at UCI, 2012-2014
I have severed in several NSF panels
I have reviewed manuscripts for many journals including:
Journal of the Royal Statistical Society, Journal of the American Statistical Association (JASA), Bayesian Analysis, Biometrics, Statistical Science, Journal of Machine Learning Research (JMLR), Statistics in Medicine, Statistical Analysis and Data Mining, Artificial Intelligence, Journal of Applied Statistics, Biometrical Journal, IEEE Transactions on Neural Networks, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Statistical Applications in Genetics and Molecular Biology, Physics in Medicine and Biology, Pattern Recognition Letter, Nature Biotechnology
Affiliations
Centers
Data Science Initiative (Director, 2020-2024)
Center for Machine Learning and Intelligent Systems
Center for Multiscale Cell Fate Research
Center for Complex Biological Systems
Organizations
Elected Fellow of American Statistical Association (ASA)
The International Society for Bayesian Analysis (ISBA)
(949) 824-0623
2222 ISEB, UC Irvine, CA 92697
babaks at uci dot edu
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