We conduct research in diverse areas of computational biology, data science and machine learning, including multi-omics data integration of cancers, optimal treatment design for heterogeneous and evolving tumors, single-cell omics data analysis, evolution of biomolecular networks and human populations, topological characterization of networks, and unsupverised learning using deep neural networks. Group members will gain experience in learning domain knowledge, performing scientific reasoning, formulating and solving mathematical models, developing algorithms, writing programs and using existing packages, collecting and analyzing big data, and interacting closely with international and domestic collaborators. We look for motivated persons curious about open scientific problems and willing to dedicate energy and time to solve them.