معرفی
Kun Liang is an Associate Professor in the Department of Statistics and Actuarial Science at the University of Waterloo, part of the Faculty of Mathematics. His research focuses on large-scale inference, statistical genetics, high-dimensional statistics, and machine learning with applications in bioinformatics and genomics.
Education:
- Ph.D. in Statistics, Iowa State University
- M.S. in Statistics, Iowa State University
- M.S. in Automation, Tsinghua University
- B.E. in Automation, Tsinghua University
Research Interests: His work emphasizes statistical methodologies for genomic data analysis, including false discovery rate control, ChIP-seq analysis, and integration of auxiliary information in RNA sequencing. He develops computational tools for gene ontology analysis and biomarker discovery in autoimmune diseases like psoriatic arthritis.
Publications: Recent work includes advancements in directional hypothesis testing, grouped false discovery rate control, and proteomic profiling of inflammatory arthritis. His research bridges statistical theory and biomedical applications, with contributions to malaria studies and epigenetic regulation analysis.
Awards: No awards explicitly listed in the provided texts.
Advising & Grants: Advising details not specified here; his grants likely focus on statistical genomics and bioinformatics, though explicit mentions are absent.
Labs/Teams: Engaged in interdisciplinary collaborations at the University of Waterloo, particularly in bioinformatics and statistical genetics.
