Prof. Zeyu Zheng
Industrial Engineering and Operations Research
University of California Berkeley
Talk:
A Few Discussions on A/B Tests
Abstract:
A/B tests have been used at scale by data-driven enterprises to guide decisions and test innovative ideas to improve core business metrics such as revenue, engagements and customer satisfaction. In this presentation, we plan to discuss a few situations where standard A/B tests receive challenges in industry practices. We then discuss some of the remedies for solvable challenges and some of the difficult-to-solve challenges. We discuss some of the gaps between theoretical work and applied work in A/B tests, followed by some possibilities to fill the gaps.
Biography:
Zeyu Zheng is an associate professor in the Department of Industrial Engineering and Operations Research (IEOR) at the University of California Berkeley and a member of the Berkeley Artificial Intelligence Research (BAIR) Lab. He received a Ph.D. in Management Science and Engineering (2018), Ph.D. minor in Statistics (2018) and M.A. in Economics (2016) from Stanford University, and B.S. in Mathematics (2012) from Peking University. He directs the Berkeley Artificial Intelligence and Simulation Lab, where his research group works on simulation, inference, generative AI models, stochastic optimization, experiment design and non-stationary learning. He collaborates in addition on asset pricing. He serves on the editorial boards for Operations Research, Naval Research Logistics, and Probability in the Engineering and Informational Sciences.
