Dr. Ma’s research spans machine learning, natural language processing, and biomedical research. He is particularly interested in exploring and modeling relational structures of data, especially the graphs that characterize interactions of a complex system. He has explored various aspects of deep graph learning and its applications, including development of one of earliest scalable graph learning methods FastGCN; and he is also an expert in time series analysis and natural language processing. He has published over 60 papers in top-tier AI conferences such as NeurIPS, ICLR, ICML, AAAI, EMNLP, and he is also a recipient of the best paper award in ISWC 2021 research track.