Rate My Professor Paat Rusmevichientong

Paat Rusmevichientong is the Justin Dart Professor of Operations Management and Professor of Data Sciences and Operations in the Marshall School of Business at the University of Southern California, contributing to the Business & Economics faculty. He received a B.A. in Mathematics from the University of California, Berkeley in 1997, graduating with Highest Honors in Mathematics and Highest Distinction in General Scholarship. He earned an M.S. in Engineering-Economic Systems and Operations Research from Stanford University in 1999 and a Ph.D. in Management Science and Engineering from Stanford University in 2003. His doctoral thesis, titled 'A Non-Parametric Approach to Multi-Product Pricing: Theory and Application,' was chaired by Benjamin Van Roy. Before joining USC Marshall in 2011 as Associate Professor, he was Assistant Professor from 2004 to 2010 and Associate Professor with tenure from 2010 to 2011 in the School of Operations Research and Information Engineering at Cornell University. He also served as a Data Miner and Software Engineer in the data mining and personalization group at Amazon.com from 2003 to 2004. At USC, he advanced to full Professor in 2015, McAlister Associate Professor from 2013 to 2015, and Co-Director of the Master Program in Business Analytics from 2014 to 2015. He held a visiting position as Research Professor at NYU Stern School of Business in Fall 2017.

His academic interests center on revenue management, choice modeling, pricing, assortment optimization, and large-scale dynamic programming. Rusmevichientong has authored numerous papers in top-tier journals. Notable publications include 'Revenue-Utility Tradeoff in Assortment Optimization under the Multinomial Logit Model with Totally Unimodular Constraints' with Sumida, Gallego, Topaloglu, and Davis (Management Science, 2021); 'Small-Data, Large-Scale Linear Optimization with Uncertain Objectives' with Gupta (Management Science, 2021); 'Dynamic Assortment Optimization for Reusable Products with Random Usage Durations' with Sumida and Topaloglu (Management Science, 2020); 'An Approximation Algorithm for Network Revenue Management under Nonstationary Arrivals' with Ma, Sumida, and Topaloglu (Operations Research, 2020); and 'Revenue Management with Heterogeneous Resources: Unit Resource Capacities, Advance Bookings, and Itineraries over Time Intervals' with Sumida, Topaloglu, and Bai (Operations Research, 2022). He has earned prestigious awards such as the INFORMS George B. Dantzig Dissertation Award (First Prize, 2003), NSF CAREER Award (2008), INFORMS Revenue Management and Pricing Section Prize (2019), Operations Research Meritorious Service Award (2012), USC Marshall Dean's Award for Research Excellence (2013), and multiple Golden Apple Awards for teaching excellence (2013, 2016, 2022, 2023), along with the USC Marshall Excellence in Teaching Award (2023) and Evan C. Thompson Faculty Mentoring and Leadership Award (2022). He serves as Associate Editor for Operations Research, Management Science, Manufacturing & Service Operations Management, and Senior Editor for Production and Operations Management.