Current Members
Lab Director
Graduate Vice Chair
Prof of Statistics and Data Science
Prof of Biostatistics (Adjunct)
Univ of California, Los Angeles
.
Postdocs
Dr. Namjoon SuhDr. Chi-Hua Wang
Dr. Shirong Xu (co-advised by Prof. Wei Sun)
PhD Students
Joshua WardXiaofeng Lin: LLM, Foundation model, Synthetic data
Hengzhi He: Applied probability, Theoretical statistics and Theoretical computer science.
Peiyu Yu (co-advised by Prof. Yian Nian Wu)
Lan Tao
Yidong Ouyang: Diffusion model and its applications in images, language, videos, and 3D generation
Minrui Gui
Thomas Kwok: Adaptation of Foundation Models for Autonomous Agent Applications
Chunhe Wang
Master Students
Junpeng Ren (Master in Statistics)Jiaxin Yang (Master in Statistics)
Bill Gu (Master in Statistics)
Henry Liu (MS in Computer Science)
Hochan Son (MASDS)
PhD & Postdoc Alumni
Ritabrata Dutta [Bayesian and Frequentist Model Selection] (PhD, 2008-2012, co-advised by Prof. Jayanta Ghosh)Associate Professor, Dept of Statistics, Univ. of Warwick
Zuofeng Shang [Smoothing Spline Inference & Nonparametric Bayes] (VAP, 2013-2015)
Associate Professor, Department of Mathematical Sciences, NJIT
Wei Sun [High Dimensional Tensor & Statistical Stability of Classification] (Ph.D, 2011-2015)
Associate Professor, Krannert School of Management, Purdue University
Zhuqing Yu [High Dimensional Semiparametric Estimation and Inference] (Ph.D, 2011-2016)
Data Scientist in AbbVie
Meimei Liu [Statistical-and-Computational Trade-off in Big Data] (Ph.D, 2013-2018, co-advised by Prof. Zuofeng Shang)
Assistant Prof. of Statistics, Virginia Tech
Shih-Kang Chao [Distributed and Online Statistical Inference] (Postdoc, 2015-2018)
Sr. Applied Scientist at Amazon
Yao Zheng [Non-Asymptotic Statistical Inference for Dependent Data] (Postdoc, 2017-2019)
Assistant Professor, Dept of Statistics, University of Connecticut [CAREER Awardee!]
Ching-Wei Cheng [Statistical Studies of Genetic Algorithm] (PhD, 2014-2019)
Data Scientist in Lowes
Botao Hao [Statistical Guarantees in Non-Convex Optimization] (PhD, 2014-2019)
Research Scientist in OpenAI
Qing Yang [Random Tensor Theory & Its Applications] (Postdoc, 2017-2020)
Assistant Professor in the School of Management, University of Science and Technology of China
Jincheng Bai [Sparse Deep Neural Networks] (PhD, 2014-2020, co-advised by Prof. Qifan Song)
Applied Scientist at Amazon
Tianyang Hu [Nonparametric Perspective of Deep Learning] (PhD, 2016-2020)
Assisant Professor at Chinese University Hong Kong-Shenzhen
Jiexin Duan [Distributed Nearest Neighbor Classification] (PhD, 2015-2021)
Sr. Financial Modeler at Moody's Analytics
Yang Yu [Distributed Bootstrap for Massive Data] (PhD, 2016-2021)
Data Scientist, Infrastructure Strategy at Meta
Chi-Hua Wang [Statistical Design of Sequential Decision Making] (PhD, 2017-2022)
Postdoc, UCLA
Pratik Ramprasad [Policy Evaluation in Statistical Reinforcement Learning] (PhD from 2017-2022, co-advised by Prof. Wei Sun)
Research scientist, Sentilink
Yue Xing [Statistical Theory for Adversarial Robustness in Machine Learning] (PhD from 2018-2022, co-advised by Prof. Qifan Song)
Assistant Prof. of Statistics and Computer Science & Engineering at Michigan State University
Zhanyu Wang [Statistical Inferences with Differential Privacy Guarantee] (PhD from 2018-2023, co-advised by Prof. Jordan Awan)
Research Scientist, Meta
Marie Maros [Decentralized High-dimensional Statistical Learning] (Postdoc from 2019-2021, co-advised by Prof. Gesualdo Scutari)
Assistant Prof of Industrial Engineering, Texas A&M Univ.
Yuantong Li [Statistical Matching Model in Centralized Two-sided Markets] (PhD from 2019-2024, co-advised by Prof. Wei Sun and Prof. Xiaowu Dai)
Research Scientist, Meta
Chendi Wang [Generative Data with Privacy Guarantees] (Postdoc from 2021-2024, co-advised by Prof. Weijie Su)
Assistant Professor, Xiamen Univ, China
Xianli Zeng [Statistical Foundation of Fairness] (Postdoc from 2020-2024, co-advised by Prof. Edgar Dobriban)
Assistant Professor, Xiamen Univ, China.
Undergrad & Master Alumni
Jacob Swoveland [The Impact of Generative and Real Training Data on Model Vulnerability] (Master from 2021-2023, co-advised by Dr. Chi-hua Wang)Data Analyst in Children's Wisconsin
Ryan O'Dell [Estimating Privacy Leakage of Machine Learning Models] (Master from 2021-2023, co-advised by Dr. Chi-hua Wang)
Data Analyst in Mercury Insurance
Nicklaus Kim [Privacy Auditing of Generative Tabular Data Generators Using Membership Inference Attacks] (Master from 2021-2023, co-advised by Dr. Chi-hua Wang)
Trevor Beer [Generative Data Science: Applications for Early Life Cycle Cost Estimation in the Aerospace Industry] (Master from 2022-2024)