IFoDS 2026 Program

All times are Beijing Time.

Friday, July 3, 2026

Saturday, July 4, 2026

  • 8:00-8:30: Registration
  • 8:30-8:40: Opening Ceremony (Location: Lecture Hall 2, Yifu Building)
  • 8:40-11:30: Keynotes (Location: Lecture Hall 2, Yifu Building)
  • 11:30-13:30: Lunch Break
  • 13:30-15:10: Parallel Session I (Location: Public Teaching Building No. 2 (PTB2))
    • Session 1: Advanced Statistical Methods for Complex Data Modeling (Chair: Haixiang Zhang) (Location: PTB2-2103)
      • Inference for Mark-Specific Causal Effects (Speaker: Lianqiang Qu)
      • Joint Modeling for Zero-Inflation in Microbiome-Metabolome Association Analysis (Speaker: Peng Ye)
      • Distributed Privacy-Preserving Group Inference for High-Dimensional Generalized Linear Models (Speaker: Dongxiao Han)
    • Session 2: Frontiers in Statistical Learning and Inference (Chair: Xiaoling Lu) (Location: PTB2-2104)
      • Decoupled Functional Central Limit Theorems for Two-Time-Scale Stochastic Approximation (Speaker: Yuze Han)
      • Design-Based Edge-Level Causal Inference with Machine Learning Assisted Covariate Adjustment (Speaker: Hanzhong Liu)
      • A Weighted Subspace Approach to Variable Importance Evaluation (Speaker: Yiwei Fan)
      • Transfer Learning with Heterogeneous Feature Spaces in Linear Regression (Speaker: Junlong Zhao)
    • Session 3: Statistical Learning Methods for Biomedical Data and Precision Medicine (Chair: Lu Tang) (Location: PTB2-2105)
      • Modeling Time-Varying Effects of Recurrent Exposures: A Time-Adapted Exponential Model to Assess Impact of Post-LVAD Bleeding on Mortality (Speaker: Guangyu Yang)
      • Neural Network on Interval-Censored Data: Application to the Prediction of Alzheimer's Disease (Speaker: Tao Sun)
      • Incorporating External Data for Analyzing Randomized Clinical Trials: A Transfer Learning Approach (Speaker: Wei Ma)
      • Kernel Smoothing-Based Methods for Estimating the Optimal Individualized Treatment Rule for Binary Outcomes (Speaker: Min Zhang)
    • Session 4: Statistical and Computational Foundations of Machine Learning (Chair: Feng Zhou) (Location: PTB2-2106)
      • Mild Over-Parameterization Benefits Tensor PCA (Speaker: Cong Fang)
      • Understanding Deep Learning from Data Statistics (Speaker: Zhiqin Xu)
      • Data Selection for LLM: Evolving from Closed to Open (Speaker: Jun Shu)
      • Implicit Models Made Explicit: From Structural Understanding to Efficient Inference (Speaker: Zenan Ling)
    • Session 5: AI-Powered Statistical Inference (Chair: Wei Lin) (Location: PTB2-2107)
      • A Conditional Distribution Equality Testing Framework Using Deep Generative Learning (Speaker: Siming Zheng)
      • Generative Doubly Robust Estimation for General Treatment Effects (Speaker: Qixian Zhong)
      • Optimal Semi-Supervised Inference for Estimating Equations: A Nonparametric Projection Approach Using ReQU Neural Networks (Speaker: Shanshan Song)
      • Metric Conformal Prediction Based on the Expected Local Radius (Speaker: Rui Qiu)
  • 15:10-15:30: Break
  • 15:30-17:10: Parallel Session II (Location: Public Teaching Building No. 2 (PTB2))
    • Session 6: Geometric and Statistical Modeling of Complex Data (Chair: Wenliang Pan) (Location: PTB2-2103)
      • Deep Isometric Manifold Embedding for Video (Speaker: Feng Li)
      • Federated LoRA Fine-Tuning for LLMs via Collaborative Alignment (Speaker: Long Feng)
      • Hidden Block Regression: A General Framework for Multi-Response Models with Group Structures and Hidden Variables (Speaker: Yuehan Yang)
      • Ball Impurity: Measuring Heterogeneity in General Metric Spaces (Speaker: Ting Li)
    • Session 7: Modern Statistical Methods for High-Dimensional, Fairness and Deep Learning Models (Chair: Zhibo Cai) (Location: PTB2-2104)
      • Allocation of Large Portfolio by Sparse Group Lasso (Speaker: Lei Huang)
      • A High-Dimensional Regression Model Based on Residual-Driven Nonlinear Screening (Speaker: Shouri Hu)
      • Random Subset Averaging (Speaker: Jie Hu)
      • Nonparametric-Based Fairness Auditing (Speaker: Xianli Zeng)
    • Session 8: Statistical Aspects of Modern Machine Learning (Chair: Jun Yan) (Location: PTB2-2105)
      • Leading Science and Clinical Research-Biostatistics in the Age of AI (Speaker: Haoda Fu)
      • Non-Asymptotic Theories of Neural Networks for Dependent Data (Speaker: Gan Yuan)
      • Robustness and Fairness in Medical Machine Learning: Optimization Strategies for Reliable and Equitable Chest X-Ray AI (Speaker: Lu Tang)
      • Learning from the Unseen: Offline Reinforcement Learning with Hidden Actions (Speaker: Ying Zhou)
    • Session 9: Frontier Methods in Biostatistics (Chair: Jing Zhou) (Location: PTB2-2106)
      • BayesRare: Bayesian Mixture Model for Population-Level Rare Cell Type Detection in Multi-Subject Single-Cell RNA Sequencing (Speaker: Yinqiao Yan)
      • An Efficient Two-Dimensional Functional Mixed-Effect Model Framework for Wearable Device Data Analysis in Large Population Studies (Speaker: Xinyue Li)
      • Joint Modeling of Longitudinal Biomarkers and Time-to-Event Data via Ordinary Differential Equations (Speaker: Ziyang Gong)
      • LLM-Assisted Clinical Trial Emulation Using Diverse Private Data (Speaker: Hao Mei)
    • Session 10: Trustworthy AI and Statistical Governance (Chair: Xiaodong Yan) (Location: PTB2-2107)
      • Asymptotic Theory and Sequential Test for General Multi-Armed Bandit Process (Speaker: Li Yang)
      • Generalized Boundary FDR Control under Arbitrary Dependence: An Approach on Closure Principle (Speaker: Haojie Ren)
      • Online Differentially Private Inference with Streaming Data (Speaker: Jinhan Xie)
      • Neural Wasserstein Two-Sample Tests (Speaker: Xiaoyu Hu)