Shenda Hong’s research interests are data mining and artificial intelligence algorithms for healthcare, especially deep learning methods for temporal medical data – such as temporal events, time series (e.g. longitudinal data, EHRs, claims data), and physiological signals (e.g. ECG, EEG, PSG, heart rates). He serves as a program committee member or reviewer for international conferences including KDD, ICLR, NeurIPS, ICML, AAAI and IJCAI. He also led a team that won the first place of the 18th PhysioNet/Computing in Cardiology Challenge.