I am an Associate Professor and a Curtis Mathes Memorial Fellow at The University of Texas at Austin, and concurrently work as a Visiting Faculty Researcher at Google. My primary affiliation is with the Statistics Group at the McCombs School of Business. I also serve as core faculty in the Department of Statistics and Data Sciences (SDS) and am a core member of the Machine Learning Laboratory. I completed my Ph.D. at Duke University in 2013, earned my Master's from the Chinese Academy of Sciences in 2008, and obtained my B.Sc. from Nanjing University in 2005. My Ph.D. advisor was Dr. Lawrence Carin.

I hold the position of an Action Editor at the Journal of Machine Learning Research and have regularly taken on the responsibilities of an Area Chair for conferences like ICLR, ICML, and NeurIPS. Our recent research endeavors have received financial and computing support from NSF, NIH, TACC, Microsoft, and Google.

My research group specializes in the field of probabilistic machine learning, with a current emphasis on advancing generative AI. Our primary areas of focus encompass probabilistic methods, Bayesian analysis, approximate inference, generative models, deep neural networks, and reinforcement learning. We are committed to pushing the boundaries of both statistical inference with deep learning and deep learning with probabilistic methods. The deep probabilistic models and inference algorithms developed within our group have demonstrated their effectiveness in addressing complex challenges across a broad spectrum of research domains. These domains include computer vision, natural language processing, sequential decision making, text analysis, image processing, time series modeling, graph mining, inverse materials design, and bioinformatics.

Most of our PhD graduates enter the tech industry, securing positions with companies like Google, while some choose academic careers at institutions such as the University of Florida and Michigan State University.

Huangjie Zheng is currently on the academic job market, and I wholeheartedly recommend considering him for an assistant professor position in machine learning, generative AI, or a related field. He is truly exceptional!

To prospective Ph.D. students

You are welcome to apply to
Ph.D. in Statistics within the IROM department
Ph.D. in Use-Inspired AI within the IROM department
The statistics and data science Ph.D. program of the SDS department

Research Highlights