Dr. Mingon Kang’s research interests include Machine Learning, Big Data Analytics, Data Science, and Bioinformatics. Specifically, Dr. Kang has been focusing on developing novel computational methodologies for sparse learning, subspace learning, and integrative and interpretable deep learning. He has published more than 50 research papers in prestigious journals and conferences, including Bioinformatics, BMC Bioinformatics, Nature Methods, IEEE/ACM Transactions on Computational Biology and Bioinformatics, Methods, Pacific Symposium on Biocomputing (PSB). His research has been supported from Oracle, The Institute for National Security Strategy (INSS), General Electric, and KNOWCK lnc, and collaborated with medical research centers such as Memorial Sloan Kettering Cancer Center, University of Texas Southwestern Medical Center, Gyeongsang National University, and Cincinnati Children’s Hospital Medical Center. He currently serves as an organizing member in IEEE International Conference on Bioinformatics & Biomedicine (IEEE BIBM), International Symposium on Bioinformatics Research and Applications (ISBRA), and Korean Computer Scientists and Engineers Association in America (KOCSEA). Dr. Kang obtained his Ph.D. and master degrees from The University of Texas at Arlington in 2015 and 2010 respectively, and he has a B.E. in Computer Engineering from Hanyang University in South Korea in 2006.
Machine Learning, Bioinformatics, Big Data Analytics