Sessions
Session 1:Modern Bayesian Methods for Structured and High-Dimensional Models
Organize:JaeyongLeeSeoul National University
Chair:JaeyongLeeSeoul National University
 speaker  affiliation  title
Won  Chang  Seoul National University Challenges and Design Principles for Fast Bayesian Inference with Normalizing Flows
JoungyounKim  University of Seoul   Bayesian Donor Set Selection in Synthetic Control Method
KyeongwonLee  Inha University  Posterior Contraction for Sparse Neural Networks in Besov Spaces with Intrinsic Dimensionality
KwangminLee   Chonnam National University  Conditional Dirichlet Processes and Functional Condition Models
Session 2:Bayesian Inference for Complex Structured Data
Organize:ShijiaWangShanghaiTech University
Chair:ShijiaWangShanghaiTech University
 speaker  affiliation  title
Yanfei  Kang  Beihang University Bayesian Forecast Combination with Predictive Priors via Particle Filtering
Kanfei  Kang Sun Yat-Sen University Beyond Overall Diagnosis: A Longitudinal Multi-Domain Latent Structure Model for Domain-specific Parkinson's Disease Progression
ShijiaWang ShanghaiTech University A Delayed Acceptance Sequential Monte Carlo with Random Forests for Bayesian Phylogenetic Inference
Rongqian Sun Shenzhen University Directed Network Discovery with Latent Variables: Identifiability and Estimation
Session 3:Bayesian Modeling of Heterogeneous Structures: From Mixtures to Metric Space Regression
Organize:XinyuanSongThe Chinese University of Hong Kong
Chair:XinyuanSongThe Chinese University of Hong Kong
 speaker  affiliation  title
JinghengCai Sun Yat-Sen University Bayesian Analysis of Mixture Models with Yeo-Johnson Transformation
Hefei Liu Yunnan University of Finance and Economics Bayesian Analysis of Frechet Regression
FangdaSong The Chinese University of Hong Kong, Shenzhen Identifying the Outbreak Mechanism of Animal Infectious Diseases Using Time-to-event Data
Rongqian  Shi  East China Normal University Bayesian tree-based heterogeneous mediation analysis with a time-to-event outcome
Session 4:Bayesian Methods in Unconventional Areas
Organize:XiaodanFanThe Chinese University of Hong Kong
Chair:XiaodanFanThe Chinese University of Hong Kong
 speaker  affiliation  title
Han Li Shenzhen University A Bayesian Stratified Mallows Model for Rank Aggregation
Ran Liu Beijing Normal University A Bayesian Framework for Multi-Scale Hierarchical Motif Modeling and Its Application in Immune Recognition
JiandongShi The Chinese University of Hong Kong Bayesian Updating Meta-Analysis
Lijun  Wang  Zhejiang University A Bayesian Approach for Knockoffs with Annotation Information
Session 5:Advanced Models with Grouping Learning for Omics Data
Organize:XiaodanFanThe Chinese University of Hong Kong
Chair:XiaodanFanThe Chinese University of Hong Kong
 speaker  affiliation  title
Shanjun Mao Hunan University Gaussian Graphical Models Based on scRNA-seq Data: Integration of Homogeneity and Heterogeneity
Chaojie Wang Jiangsu University STransfer: A Transfer Learning-Enhanced GCN for Spatial Transcriptomics Data
Zhang Zhen The First Institute, Kunming Institute of Physics DIHap: A Direct Bayesian Inference method of Haplotypes from Sequencing Data
Bencong Zhu The Chinese University of Hong Kong BISON: bi-clustering of spatial omics data with feature selection
Session 6:Bayesian Methods for Complex Biomedical and Behavioral Data
Organize: Feng LiPeking University
Chair:Feng LiPeking University
 speaker  affiliation  title
Shufei Ge
ShanghaiTech University Bayesian Information Borrowing for (Ultra) High-Dimensional Brain Connectivity Inference
Feng Li Peking University Deep Isometric Manifold Embedding for Video Gestures
Wenliang Pan Academy of Mathematics and Systems Science, CAS Ball Impurity: Measuring Heterogeneity in General Metric Spaces
Yalie Yang Peking University Cancer Hospital Quantitative Analysis of Glucose Metabolic Parameters via Dynamic PET Imaging Using A Segmentation-Driven Probabilistic Graphical Model
Session 7:Bayesian Methods for Complex Dynamics and Latent Structures: From Survival and Sequential Data to Educational Measurement
Organize: Zhihua MaShenzhen University
Chair:Zhihua MaShenzhen University
 speaker  affiliation  title
Fang Liu
Northeast Normal University Decomposition of WAIC for assessing the information gain with application to educational testing
Shaochuan Lv Beijing Normal University Robust Bayesian change point detection
Zhihua Ma Shenzhen University Modeling Nonlinear Ability Trajectories and Learner Heterogeneity in Online Learning: A Bayesian Nonparametric Dynamic IRT Framework
Chong Zhong Hong Kong Polytechnic University On MCMC mixing for predictive inference under unidentified transformation models
Session 8:New Bayesian Approaches in Biomedical Studies
Organize: Weining ShenUniversity of California, Irvine
Chair:Weining ShenUniversity of California, Irvine
 speaker  affiliation  title
Xiangyu Luo
Renmin University of China Batch effect correction for heterogeneous DNA methylation data via Bayesian hierarchical beta mixtures
Juan Shen Fudan University Beyond a Single Biomarker: Adaptive Enrichment Design with Data-Driven Subgroup Rules
Yan Zhang The University of Hong Kong Bayesian Methods for Integrative Post-GWAS Inference
Session 9:Monte Carlo, Diffusion, and Flow Methods for Bayesian Inference
Organize: Cheng LiNational University of Singapore
Chair:Cheng LiNational University of Singapore
 speaker  affiliation  title
Cheng Zhang Peking University Wasserstein Convergence Guarantees for Distributional Diffusion Models
Xiyun Jiao Southern University of Science and Technology A Novel Framework Using Variational Inference with Normalizing Flows to Train Transport Reversible Jump Proposals
Rong Tang Hong Kong University of Science and Technology On Subsampling Metropolis-Hastings Algorithm for Non-smooth Bayesian Posterior Sampling
Ganchao Wei Duke University Jump-Process Flow Matching for High-Dimensional Count Data
Session 10:Recent Advances in Bayesian Theory and Applications
Organize: Ke DengTsinghua University
Chair: Junni ZhangPeking University
 speaker  affiliation  title
Junni Zhang Peking University Estimating COVID-19 Excess Deaths During the Pandemic and After: A New Bayesian Model, With an Application to New Zealand
Cheng Meng Renmin University BanditSIS: Adaptive Subsampling for Scalable Feature Screening
Yang Yang Nankai University Data-Efficient Multi-Functional Bayesian Optimization for Automated Metamaterial Design
Session 11:Bayesian Methods for Causal Inference with Complex Survival Data
Organize: Liangyuan HuRutgers University
Chair:Jingheng  CaiSun Yat-Sen University
 speaker  affiliation  title
Liangyuan Hu Rutgers University Bayesian Structural Nested Failure Time Models for Causal Inference with Time-Varying Confounding and Survival Outcomes
Fan Li Yale University :Identification and Estimation of Causal Mechanisms in Cluster-Randomized Trials with Post-Treatment Confounding Using Bayesian Nonparametrics
Xinyuan Song The Chinese University of Hong Kong Bayesian Tree-Based Heterogeneous Treatment Effect Analysis with a Time-to-Event Outcome
Session 12:Bayesian Inference and Mathematical Guarantees for Generative and Latent-Variable Models
Organize: Rong TangHong Kong University of Science and Technology
Chair:Rong TangHong Kong University of Science and Technology
 speaker  affiliation  title
Biao Cai City University of Hong Kong Generalized Tensor Completion with Non-Random Missingness
Huaqing Jin Tsinghua University Bayesian inference of a spectral graph model for brain oscillations
Gen Li The Chinese University of Hong Kong Faster Convergence for Diffusion-Based Generative Models
Session 13:Modern Bayesian Analysis and Its Novel Applications
Organize: Yichuan ZhaoGeorgia State University
Chair:Puying ZhaoYunnan University
 speaker  affiliation  title
Ke Deng Tsinghua University A Bayesian Criterion for Re-randomization
Wu Jing University of Rhode Island Variational Bayes for Exponential Tilted Likelihood in Stationary Time Series Data
Jian Kang University of Michigan Bayesian Transfer Learning for Brain Computer Interfaces
Catherine Liu  Hong Kong Polytechnic University  Improving MCMC mixing under unidentified transformation models through prior adjustment

Session 14:Robust Bayesian and High-Dimensional Methods for Complex Biomedical and Observational Data
Organize:XiaWangUniversity of Cincinnati
Chair:XiaWangUniversity of Cincinnati
 speaker  affiliation  title
Xuan Cao University of Cincinnati Integrative Bayesian Modeling for Functional MRI Data
Xia Wang University of Cincinnati Consistent and Scalable Variable Selection with Robust Link Functions
Yunan Wu Tsinghua University Robust High-dimensional Inference for Causal Effects Under Unmeasured Confounding and Invalid Instruments with an Application to Multivariable Mendelian Randomization Analysis
I-TangYu  Tunghai University A Bayesian Multivariate Student-t Degradation Model for Dependent Log-Increments
Session 15:Scalable Bayesian Learning for High-Dimensional Structured Data
Organize:Jian KangUniversity of Michigan
Chair:Jian KangUniversity of Michigan
 speaker  affiliation  title
Wei Hao University of Michigan BROWNIE: A Bayesian Random Weight Neural Network Inference Engine as a Scalable Alternative to Deep Learning
Jie He Nanjing University of Aeronautics and Astronautics Prior Knowledge Guided Ultra-high Dimensional Variable Screening with Application to Neuroimaging Data
Ben Wu Renmin University of China Bayesian Scalar-on-Network Regression with the Latent Space Hierarchical Spike-and-Slab Prior
Zhenke Wu   University of Michigan  Taxonomy-Informed Bayesian Semi-supervised Learning with Possibly Coarsened Labels
Session 16:Bayesian Learning and Computation for Complex Data and Sequential Decision-Making
Organize: Li MaThe University of Chicago
Chair:Li MaThe University of Chicago
 speaker  affiliation  title
Cheng Li National University of Singapore Accelerating Sequential Designs with Provably Accurate Hilbert Space Gaussian Processes
Li Ma The University of Chicago Generalized Bayesian density ratio learning
Xinyuan Song The Chinese University of Hong Kong Bayesian learning for longitudinal imaging and survival data
Session17:Modern Bayesian Methods for Complex Data and Learning
Organize:YuexiWangUniversity of Illinois Urbana-Champaign
Chair:YuexiWangUniversity of Illinois Urbana-Champaign
 speaker  affiliation  title
Feng Liang University of Illinois Urbana-Champaign Bayesian Smoothing and Feature Selection via Variational Automatic Relevance Determination
Guanyang Wang Rutgers University Noise as Lens and Lever in Diffusion Models
Bohai Zhang Beijing Normal-Hong Kong Baptist University A Bayesian treed partition model for spatial binary data with application to Arctic sea ice dataset
Session 18:Advances in Statistical Learning and Decision-Making for Complex Data
Organize: Yanxun Xu Johns Hopkins University
Chair:Yanxun Xu Johns Hopkins University
 speaker  affiliation  title
Xiang Ji Iowa State University Action-based phylogenetic likelihood calculations for large state-space models
Aki Nishimura Johns Hopkins University High-dimensional Bayesian transfer learning through skew shrinkage priors: applications to genetic and electronic health records data
Yanxun Xu Johns Hopkins University Robust Bayesian Learning for Optimal Decision Making Under Unmeasured Confounding
Session 19:Bayesian Modeling for Complex Data
Organize: Zehang LiUniversity of California, Santa Cruz
Chair:Sheng JiangThe Chinese University of Hong Kong, Shenzhen
 speaker  affiliation  title
Sheng Jiang The Chinese University of Hong Kong, Shenzhen Errors-in-variables Gaussian Processes for Mixed-input Regression
Weining Shen University of California, Irvine Bayesian data integration in clinical trials
Xiaotian Zheng University of Georgia Bayesian quantile regression for marked temporal point processes
Session 20:Scalable Bayesian and Statistical Learning for Complex Structured Data
Organize: Jiangyan ZhaoEast China Normal University
Chair:Jiangyan ZhaoEast China Normal University
 speaker  affiliation  title
Qingyi Pan Tsinghua University Reliable Multivariate Deep Regression using Moment-Matching Prior Networks
Xiaorui Wang Nanjing University of Information Science & Technology Bayesian analysis of nonlinear structured latent factor models with a Gaussian process prior
JiangyanZhao  East China Normal University   BKP: An R Package for Beta Kernel Process Modeling
Peng Sun Shanghai University of Engineering Science Automated landmark discovery method for integration of spatial omics data
Session 21:Structured Modeling and Shrinkage for Complex and Heterogeneous Data
Organize: Meng LiRice University
Chair:Meng LiRice University
 speaker  affiliation  title
Liang Ding Fudan University The BdryMatérn GP: a new Gaussian process model for incorporating boundary information
Meimei Liu Virginia Tech Contrastive Latent Factor Modeling for Inter-Subject Heterogeneity with Application to Healthcare Time Series
Weixuan Zhu Xiamen University Graph Trend-Filtering for Denoising via Graph Shrinkage Processes
Session 22:Recent developments in Bayesian inference for complex data models
Organize: Gyuhyeong GohKyungpook National University
Chair:Gyuhyeong GohKyungpook National University
 speaker  affiliation  title
Seongmin Kim Ewha Womans University Eigenstructure inference for high-dimensional covariance with generalized shrinkage inverse-Wishart prior
Junwoo Jo Kyungpook National University Fully Bayesian synthetic control methods with sparse convex hull restriction and Gaussian process
Keunbaik Lee Sungkyunkwan University TBA

 
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