Please note that this page is intended only for looking up invited session IDs for abstract submission. The sessions are not listed in conference schedule order.
| Session ID | Session Title | Organizer | Chair |
|---|---|---|---|
| 01 | Neural Networks in Dimension Reduction and Causal Inference | Yanyuan Ma (Penn State University) | Yin Tang (University of Kentucky) |
| 02 | Learning, Inference and Decision Making in Complex Structures | Yanyuan Ma (Penn State University) | Tianying Wang (Colorado State University) |
| 03 | Mediation Analysis and Causal Inference in Biomedical Research | Heping Zhang (Yale University School of Public Health) | Ying Wei (Columbia University) |
| 04 | Analysis of Omic Data, and AI and Data-Driven Science | Heping Zhang (Yale University School of Public Health) | Qiao Liu (Yale University School of Public Health) |
| 05 | Statistical Learning in Complex System | Zhezhen Jin (Columbia University) | Yushu Shi (Weill Cornell Medicine) |
| 06 | Statistical Learning in Biomedical Studies | Zhezhen Jin (Columbia University) | Shanshan Ding (Department of Applied Economics and Statistics, University of Delaware) |
| 07 | New Statistical Tools for High-Dimensional Biomedical Data Analysis | Boxiang Wang (University of Iowa) | Boxiang Wang (University of Iowa) |
| 08 | Conformal Prediction with Partially Observed Data | Matteo Sesia (University of Southern California) | Vladimir Svetnik (Merck & Co.) |
| 09 | Advances in High-Dimensional Statistics and Random Matrix Theory | Joshua Cape (University of Wisconsin-Madison) | Joshua Cape (University of Wisconsin-Madison) |
| 10 | Statistical Advances in the Analysis of Embeddings, Networks, and Graphs | Joshua Cape (University of Wisconsin-Madison) | Joshua Cape (University of Wisconsin-Madison) |
| 11 | Topics in Online Statistical Inference and Learning | Zhimei Ren (University of Pennsylvania) | Zhimei Ren (University of Pennsylvania) |
| 12 | Modern Perspectives in Bayesian Statistics | Guanyu Hu (Michigan State University) | Guanyu Hu (Michigan State University) |
| 13 | Navigating the AI Transformation in Biostatistics: Opportunities, Methods, and Evolving Practice | Wen Li (Pfizer) | Wen Li (Pfizer) |
| 14 | Reliable Modeling and Prediction in Complex Data Analysis | Boxiang Wang (University of Iowa) | Boxiang Wang (University of Iowa) |
| 15 | Distribution-Free Statistical Inference for AI | Vladimir Svetnik (Merck & Co.) | Matteo Sesia (University of Southern California) |
| 16 | Causality and AI in Science | Zhonghua Liu (Columbia University) | Zhonghua Liu (Columbia University) |
| 17 | Causal and Statistical Methods for Genomic Data | Zhonghua Liu (Columbia University) | Zhonghua Liu (Columbia University) |
| 18 | Causal and Machine Learning Methods in Health Research | Zhonghua Liu (Columbia University) | Kan Chen (Columbia University) |
| 19 | Emerging Methods and Applications in Single-Cell Analysis | Guanyu Hu (Michigan State University) | Guanyu Hu (Michigan State University) |
| 20 | Reliable Discovery in Complex Data: Advances in High-Dimensional and Interpretable Clustering | Ardavan Yazdanbakhsh (City College of New York) | Ardavan Yazdanbakhsh (City College of New York) |
| 21 | Learning from Neuroimaging Data: Statistical and AI Methods for Brain Aging | Jun Yan (University of Connecticut) | Panpan Zhang (Vanderbilt University Medical Center) |
| 22 | Causal Mechanisms and Inference in Complex Data | Panpan Zhang (Vanderbilt University Medical Center) | Jun Yan (University of Connecticut) |
| 23 | The Interplay Between Statistics and Data-Driven Decision-Making | Zhimei Ren (University of Pennsylvania) | Ying Jin (University of Pennsylvania) |
| 24 | Modeling Structure, Time, and Uncertainty in Medical Imaging Analysis | (Din) Ding-Geng Chen (Arizona State University) | (Din) Ding-Geng Chen (Arizona State University) |
| 25 | Statistical Machine Learning for Complex Data | Tianxi Li (University of Minnesota) | Tianxi Li (University of Minnesota) |
| 26 | Recent Advances in Statistical Network Modeling and Inference | Tianxi Li (University of Minnesota) | Tianxi Li (University of Minnesota) |
| 27 | Advances in Statistical Learning for Real-World Evidence | Rui Duan (Harvard University) | Rui Duan (Harvard University) |
| 28 | Recent Advancement in Network Analysis | Tracy Ke (Harvard University) | Tracy Ke (Harvard University) |
| 29 | Advances in Nonparametric Learning and Inference for Complex Data | Zhao Ren (University of Pittsburgh) | Zhao Ren (University of Pittsburgh) |
| 30 | Modern Statistical Learning and Representation Methods for Complex Biomedical Data | Hai Shu (New York University, Department of Biostatistics) | Hai Shu (New York University, Department of Biostatistics) |
| 31 | From Statistical Inference to Production AI: Industry Case Studies in Causality and Intelligent Systems | Wanjun Liu (LinkedIn Corporation) | Wanjun Liu (LinkedIn Corporation) |
| 32 | Causal Inference and Decision-Making on Networks | Emma Jingfei Zhang (Emory University) | Emma Zhang (Emory University) |
| 33 | Embeddings and Dynamics in Complex Networks | Emma Jingfei Zhang (Emory University) | Emma Jingfei Zhang (Emory University) |
| 34 | Statistical Inference under Data Perturbation, Structure, and Heterogeneity | Elynn Chen (New York University) | Elynn Chen (New York University) |
| 35 | Statistical Inference and Learning in High-Dimensional Structured Models | Marianna Pensky (University of Central Florida) | Marianna Pensky (University of Central Florida) |
| 36 | Network Interference, Spillover and Temporal Effects | Keith Levin (University of Wisconsin-Madison) | Keith Levin (University of Wisconsin-Madison) |
| 37 | Valid Uncertainty Quantification in Modern Statistical Learning | Yuan Zhang (Ohio State University) | Yuan Zhang (Ohio State University) |
| 38 | Statistical Methods for AI: Attribution, Alignment, Representation Learning, and Generative Evaluation | Yuan Zhang (yzhanghf@stat.osu.edu) | Yuan Zhang (Ohio State University) |
| 39 | Statistical Learning and Inference for Metric-Space-Valued Data | Mladen Kolar (USC & MBZUAI) | Mladen Kolar (USC & MBZUAI) |
| 40 | Data Attribution in Statistical Science and AI | Weijing Tang (Carnegie Mellon University) | Weijing Tang (Carnegie Mellon University) |
| 41 | Innovative Methods in Statistics and Data Science in Aging | Jaime Lynn Speiser (Wake Forest University School of Medicine) | Jaime Lynn Speiser (Wake Forest University School of Medicine) |
| 42 | Impactful Applications in Statistics and Data Science in Aging | Jaime Lynn Speiser (Wake Forest University School of Medicine) | Panpan Zhang (Vanderbilt University Medical Center) |
| 43 | Large Language Models and Statistical Foundations | Yan Sun (New Jersey Institute of Technology) | Yan Sun (New Jersey Institute of Technology) |
| 44 | Robust Inference & Learning Strategies in Modern Data Science | Chi-Kuang Yeh (Georgia State University) | Chi-Kuang Yeh (Georgia State University) |
| 45 | Statistical Learning and Network Analysis for Complex Biological Data | Quefeng Li (UNC Chapel Hill) | Quefeng Li (UNC Chapel Hill) |
| 46 | Statistical Principles and Optimization for High-Dimensional Learning and AI | Quefeng Li (UNC Chapel Hill) | Quefeng Li (UNC Chapel Hill) |
| 47 | High-Dimensional Data in Neuroimaging and AI | Guanqun Cao (Michigan State University) | Todd Ogden (Columbia University) |
| 48 | Integrative Statistical Learning for Complex Biomedical Data | Guanqun Cao (Michigan State University) | Guanqun Cao (Michigan State University) |
| 49 | Advances in Statistical Inference for Complex Data | Yufeng Liu (University of Michigan) | Yufeng Liu (University of Michigan) |
| 50 | Uncertainty, Dependence, and Structure in Modern Data Analysis | Yufeng Liu (University of Michigan) | Hang Zhou (University of North Carolina) |
| 51 | Advances in Random Matrix Theory and Its Statistical Applications | Rong Ma (Harvard University) | Rong Ma (Harvard University) |
| 52 | New Statistical Insights on Learning and Selection | Rong Ma (Harvard University) | Rong Ma (Harvard University) |
| 53 | Advances in Machine Learning for Neuroimaging and Behavioral Data in Mental Health Research | Yuanjia Wang (Columbia University) | Yuan Bian (Columbia University) |
| 54 | Learning from Real-World Health Data: Methods for Imbalance, Heterogeneity, Equity, and Real-World Evidence Translation | Rui Duan (Harvard University) | Tian Gu (Columbia University) |
| 55 | Statistical-Computational Gaps in Network and Tensor Data | Keith Levin (University of Wisconsin-Madison) | Keith Levin (University of Wisconsin-Madison) |
| 56 | Novel Network Models and Model Selection | Keith Levin (University of Wisconsin-Madison) | Keith Levin (University of Wisconsin-Madison) |
| 57 | Advances in Statistical Learning for Data Integration | Jing Ma (Fred Hutchinson Cancer Center) | Jing Ma (Fred Hutchinson Cancer Center) |
| 58 | Advances in Methodology and Theory for Network Analysis | Jingming Wang (University of Virginia) | Jingming Wang (University of Virginia) |
| 59 | Modern Network Analysis and Applications Across Disciplines | Jingming Wang (University of Virginia) | Huimin Cheng (Boston University) |
| 60 | Robust Causal Inference Under Real-World Complications: Extrapolation, High Dimensions, and Missing Data | Siyu Heng (New York University) | Siyu Heng (New York University) |
| 61 | AI/ML and Advanced Statistical Methods in Clinical Development | Yue Shentu (Merck & Co.) | Yue Shentu (Merck & Co) |
| 62 | Structure Learning and Inference in High-Dimensional Dynamic Systems | Mladen Kolar (USC & MBZUAI) | Paromita Dubey (USC) |
| 63 | Statistical Foundations of Modern Generative and Decision Models | Grace Yi (University of Western Ontario) | Grace Yi (University of Western Ontario) |
| 64 | Emerging Advances in Analysis of Complex Data | Wenqing He (University of Western Ontario) | Wenqing He (University of Western Ontario) |
| 65 | Statistical Challenges in Data Science: Privacy, Explanation Errors, and Dynamic Ratings | Li-Pang Chen (National Chengchi University) | Li-Pang Chen (National Chengchi University) |
| 66 | Statistical Learning for Causal Inference: From Estimation to Decision-Making | Qilu Yu (NIH, National Center for Complementary and Integrative Health) | Qilu Yu (NIH, National Center for Complementary and Integrative Health) |
| 67 | New Frontiers in High-Dimensional Graphical Modeling | Jing Ma (Fred Hutchinson Cancer Center) | Jing Ma (Fred Hutchinson Cancer Center) |
| 68 | Causal Intelligence: Modern Perspectives at the Intersection of Statistical Inference and AI | Honglang Wang (Indiana University Indianapolis) | Kun Zhang (Carnegie Mellon University) |
| 69 | From Spatial Patterns to Biological Intelligence: Statistical Inference for Spatial Omics | Honglang Wang (Indiana University Indianapolis) | Wenpin Hou (Duke University) |
| 70 | Statistical Analysis of LLM and Representation Learning | Yang Ning (Cornell University) | Yang Ning (Cornell University) |
| 71 | Advancement in Nonparametric Method in Complex Data | Wen Zhou (New York University) | Xiwei Tang (UT Dallas) |
| 72 | Methods and Theory for Machine Learning: Estimation and Prediction | Yang Ning (Cornell University) | Yang Ning (Cornell University) |
| 73 | AI/ML for Biomedical Research | Muxuan Liang (The University of Texas MD Anderson Cancer Center) | Muxuan Liang (The University of Texas MD Anderson Cancer Center) |
| 74 | Enhanced Causal Inference and Clinical Trials with AI/ML | Muxuan Liang (The University of Texas MD Anderson Cancer Center) | Wodan Ling (Weill Cornell Medicine) |
| 75 | Causal AI and Representation Learning | Bryon Aragam (University of Chicago) | Bryon Aragam (University of Chicago) |
| 76 | Improving Inference in Nonparametric Models | Ted Westling (University of Massachusetts Amherst) | Ted Westling (University of Massachusetts Amherst) |
| 77 | Novel Methods in Learning Dependent and Dynamical Data | Wen Zhou (New York University) | Wen Zhou (New York University) |
| 78 | AI-Augmented Design and Analysis in Clinical Trials and Scientific Research: Methods, Applications, and Responsible Implementation | Qiqi Deng (Moderna Inc.) | Qiqi Deng (Moderna Inc.) |
| 79 | Recent Advances in Empirical Bayes: Theory, Applications, and Methods | Yanjun Han (New York University) | Yanjun Han (New York University) |
| 80 | Spatial Causal Inference | Ted Westling (University of Massachusetts Amherst) | Ted Westling (University of Massachusetts) |
| 81 | Causal and Interpretable Learning for Heterogeneous and Longitudinal Effects in Clinical Studies | yue_shentu@merck.com (Merck & Co) | Jinchun Zhang (Merck & Co) |
| 82 | Artificial Intelligence in Rare Disease Therapeutics: Integrating Drug Repurposing, Hybrid Trial Design, and Real-World Evidence | Bryan McComb (Pfizer, Inc.) | Bryan McComb (Pfizer, Inc.) |
| 83 | Statistical Methods for Dissecting Heterogeneity and Decision-Making in Precision Medicine Research | Yuanjia Wang (Columbia University) | Yinjun Zhao (Columbia University) |
| 84 | Analyzing Complex-Structured Data with Latent Geometry and Heterogeneity | Yinqiu He (University of Wisconsin-Madison) | Yinqiu He (University of Wisconsin-Madison) |
| 85 | Trustworthy Learning and Inference at Scale | Yinqiu He (University of Wisconsin-Madison) | Yinqiu He (University of Wisconsin-Madison) |
| 86 | Machine Learning for Causal Inference and Econometrics | Lihua Lei (Stanford University) | Lihua Lei (Stanford University) |
| 87 | Human-AI Collaboration | Lihua Lei (Stanford University) | Lihua Lei (Stanford University) |
| 88 | Advances in Methods for Leveraging External Information in Precision Medicine | Nicholas Henderson (University of Michigan) | Nicholas Henderson (University of Michigan) |
| 89 | Equilibrium-Aware A/B Testing | Lihua Lei (Stanford University) | Lihua Lei (Stanford University) |
| 90 | Mechanism Design for Data Science and AI | Lihua Lei (Stanford University) | Lihua Lei (Stanford University) |
| 91 | AI Foundations: Statistical Principles for Modern Learning and Large-Scale Models | Xiwei Tang (University of Texas at Dallas) | Xiwei Tang (University of Texas at Dallas) |
| 92 | Advances in Graphical Models for Causality and Missingness | Caleb Miles (Columbia University) | Oliver Hines (Columbia University) |
| 93 | Causal Inference in Complex Real-World Data Applications | Caleb Miles (Columbia University) | Taehyeon Koo (Columbia University) |
| 94 | Statistical Foundations for Reliable and Interpretable AI | Xiwei Tang (University of Texas at Dallas) | Haowen Zhou (University of Virginia) |
| 95 | Statistical Foundations and Interpretability for LLM Evaluation and Reasoning | Yuqi Gu (Columbia University) | Yuqi Gu (Columbia University) |
| 96 | When Does Explainable AI Actually Open the Black Box | Srikar Katta (Duke University) | Lesia Semenova (Rutgers University) |
| 97 | Transparent Machine Learning Through Visualization and Human-Centered Design | Zachery Boner; Lesia Semenova (Duke University; Rutgers University) | Jon Donnelly (Duke University) |
| 98 | Robustness Bayesian Methods with Machine Learning Applications | Jami Mulgrave (NC State University) | Jami Mulgrave (NC State University) |
| 99 | Digital Twins and Synthetic Data for Clinical Research | Qilu Yu (NIH, National Center for Complementary and Integrative Health) | Qilu Yu and Tae Hyun Jung (NIH NCCIH, FDA CDER) |
| 100 | The Role of the Rashomon Effect in Responsible AI | Chudi Zhong (University of North Carolina at Chapel Hill) | Srikar Katta (Duke University) |
| 101 | Advances in Transfer Learning | Maryclare Griffin (University of Massachusetts Amherst) | Maryclare Griffin (University of Massachusetts Amherst) |
| 102 | Making Sense of Multivariate Data | Maryclare Griffin (University of Massachusetts Amherst) | Nathan Wycoff (University of Massachusetts Amherst) |
| 103 | Recent Methodological Advances in Causal Inference | Caleb Miles (Columbia University) | Daniel Malinsky (Columbia University) |
| 104 | AI-Driven Clinical Intelligence: Integrating Generative Models, Predictive Analytics & Clinical Decision Making | Xing Chen (Moderna) | QiQi Deng (Moderna) |
| 105 | Statistical Learning for Dynamical Systems and Scientific Applications | Shihao Yang (Georgia Institute of Technology) | Shihao Yang (Georgia Institute of Technology) |
| 106 | From Data to Structure and Inference | Marianthi Markatou (SUNY Buffalo) | Zhezhen Jin (Columbia University) |
| 107 | Next-Generation Decision Intelligence: From Underwriting and Uplift Modeling to LLM-Driven Statistical Experiment Lifecycle Automation and Clinical Assessment | Jieying Jiao (New York Life) | Jieying Jiao (New York Life) |