His research interests include scalable and trustworthy AI, e.g., adversarial deep learning, optimization theory and methods, computer vision, and computational biology. He received the Best Student Paper Award at the 42nd IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP’16), and the Best Paper Runner-Up Award at the 38th Conference on Uncertainty in Artificial Intelligence (UAI’22). He has published over 50 papers at top-tier ML/CV conferences, such as NeurIPS, ICML, ICLR, CVPR, ICCV, ECCV, AISTATS, and AAAI (please refer to the CS ranking).

He is currently a Senior Member of IEEE, a Technical Committee (TC) Member of Machine Learning for Signal Processing (MLSP) in the IEEE’s Signal Processing Society, and an affiliated faculty at the MIT-IBM Watson AI Lab, IBM Research. He has organized a series of Adversarial ML workshops in ICML’22 and KDD’19-’22, and provided tutorials on Trustworthy and Scalable ML in AAAI’23, NeurIPS’22, and CVPR’20.