Mengxin Wang
PhD Candidate of Industrial Engineering and Operations Research
University of California, Berkeley
Hi! I am Mengxin (pronounced as 'mong-shin'). I'm a Ph.D. candidate in the Department of Industrial Engineering and Operations Research at the University of California, Berkeley. I am advised by Professor Zuo-Jun (Max) Shen. Before joining Berkeley, I received a B.Eng. in Industrial Engineering at Tsinghua University.
My research uses algorithm and data analytics to make better decisions for digital business, with applications in the online marketplace, supply chain management and logistics systems. I use combinatorial optimization, stochastic and robust optimization, and statistical and data analytics for tackling complex real-world problems. I am also broadly interested in machine learning and its application in operations research. Please feel free to contact me for research discussion and collaboration!
I am on the 2022-2023 job market.
Contact: mengxin_wang at berkeley dot edu
News
(10/22) My paper "Joint Product Design and Dynamic Assortment Optimization: Integrating Strategic and Tactical Revenue Management" is selected as the finalist of the 2022 Jeff McGill Student Paper Award.
(10/22) Our paper "Content Promotion for Online Content Platforms with Diffusion Effect" is selected as the winner of the INFORMS Best Student Paper Award in Social Media Analytics (primarily awarded to student coauthor Yunduan Lin).
(09/22) I will be at INFORMS 2022 for the following talks and sessions. Please come to any if you are interested!
I will be at SC67. New Frontiers of Revenue Management on 12: 30 pm - 1: 45 pm Sunday, Oct 16 to present my work "Coordinating Joint Offline and Online Product Decisions: Practical Insights from Optimization".
I will hold session MB67. Innovation and algorithm advances in online marketplace on 11: 00 am - 12: 15 pm, Monday, Oct 17.
Our work "Content Promotion for Online Content Platforms with Diffusion Effect" is selected as the finalist of the INFORMS Best Student Paper Award in Social Media Analytics. The competition session will be held at MB72 on 11:00 am - 12:15 pm, Monday, Oct .17.