Haiquan Li received his Ph.D. in Bioinformatics and Data Mining from the National University of Singapore where he developed algorithms for pattern mining (e.g. protein binding motif pairs) and network motif mining (e.g. bipartite mining). After graduation, he joined Noble Foundation and built machine learning models for prediction and functional characterization of membrane transporters for various sequencing projects.  He switched to translational bioinformatics after working at The University of Chicago as a research faculty in 2010. His research interests focus on unveiling the cooperative biological mechanisms among single nucleotide polymorphisms associated with complex diseases, and genetic underpinning of complex disease comorbidity. His research is highly interdisciplinary, spanning personalized medicine, clinical informatics, big data, and statistics. He received a Distinguished Paper Award from the American Medical Informatics Association (AMIA) Annual Symposium 2011.