Willie Neiswanger

Machine learning at Stanford Computer Science SAIL / StatsML

I am a postdoc in computer science at Stanford University, working with Stefano Ermon and affiliated with the StatsML Group, Stanford AI Lab, and SLAC.

Research: I work on algorithms and systems to help scale and automate machine learning. My interests include distributed inference, AutoML, computer vision, computational biology, materials science, and analysis of text and network data. I also work on sequential decision making under uncertainty, which I apply to problems in science and engineering.

Education: I completed my PhD in Machine Learning at Carnegie Mellon University, where I was advised by Eric Xing and collaborated with Jeff Schneider and Barnabas Poczos.

Previously, I studied at Columbia University, where I worked with the Wiggins Lab and Frank Wood.




A full list of my publications can be found here.