Mingyuan Zhou is an Associate Professor at the University of Texas at Austin. He received his Ph.D. in Electrical and Computer Engineering from Duke University in 2013. His research lies at the intersection of machine learning and probabilistic modeling, covering a diverse set of research topics in statistical theory and methods, generative models, statistical inference for big data, and deep learning. He is currently focused on advancing both statistical inference with deep learning and deep learning with probabilistic methods. He is an action editor of the Journal of Machine Learning Research and has frequently served as (senior) area chairs for leading machine learning conferences, including NeurIPS, ICML, ICLR, and AAAI.