Published multiple papers including but not limited to: biophysics-based protein language models, multi-omic pathway analysis, Chemical Language Model Linker method for text-based chemical generation, predicting protein fitness using structure-based models, etc. Participated in collaborative machine learning projects such as benchmarking and evaluation in biology workshop and ADMET assay property prediction community challenge.
Research Experience
Conducts computational biology research at the University of Wisconsin-Madison and the Morgridge Institute for Research. Co-taught Computational Network Biology with Sushmita Roy in Fall 2019 through 2025, co-taught Introduction to Artificial Intelligence with Yin Li, Yingyu Liang, and Daifeng Wang in Fall 2020, taught Advanced Bioinformatics in Spring 2016-2018, and a special topics course on Cancer Bioinformatics in Spring 2015.
Background
Research interests include designing algorithms to leverage biological networks to connect different types of data and detect surprising relationships among them. Particularly focused on the study of human diseases, especially cancer and viral infections. Also focuses on the dynamic behaviors of biological networks and develops techniques to reconstruct dynamic models of signaling pathways and transcriptional regulatory networks from high-throughput proteomic and transcriptomic data.