Hello! My name is Zi Wang, and I am a research scientist at Google Brain. I received my Ph.D. in computer science from MIT, with a dissertation on robot learning with strong priors. Previously, I was an undergraduate at Tsinghua and a visiting scholar at USC where I started working on machine learning. Before that, I worked on research projects in the realm of mathematical optimization and modeling.
My goal is to build sample efficient learning machines with certifications, which requires intelligent data acquisition strategies and understanding of circumstances where we have performance guarantees. My work lies in the intersections of Bayesian optimization, active learning, prior learning, rule learning, integrated learning and planning, and symbolic AI.
- Learn about new advances in Bayesian optimization at Google BayesOpt Speaker Series on YouTube. More to come!
- Check out the Gaussian Process Seminar Series on YouTube – we had an amazing series of talks on Gaussian Processes, Spatiotemporal Modeling, and Decision-making Systems and hosted a NeurIPS 2022 Workshop on these topics. Stay tuned for more.
Work related: wangzi ‘at’ google ‘dot’ com
Everything else: ziw ‘at’ csail ‘dot’ mit ‘dot’ edu