The primary focus of the Jian Ma Lab's ongoing research is the development of machine learning algorithms to study the structure and function of the human genome and cellular organization, as well as their implications for evolution, health, and disease. The lab also explores machine learning methods for the cohesive integration of multimodal biomedical data and techniques to enhance model interpretability and generalizability. Recent interests include nuclear organization, single-cell epigenomics, spatial omics, comparative genomics, and complex molecular interactions.

Ma lab is leading a UM1 Center in the NIH 4D Nucleome (4DN) Program [CMU News]. Jian is also serving as Co-Chair of the Steering Committee of the NIH 4DN Program. In addition, the Ma lab is involved in the NIH SenNet Consortium and the IGVF Consortium. 

Jian Ma is the Program Chair for RECOMB 2024.