معرفی
Adam Elmachtoub is an Associate Professor in the Department of Industrial Engineering and Operations Research at Columbia University, where he holds affiliations with the Data Science Institute and serves as an Amazon Visiting Academic. He earned his B.S. in Operations Research from Cornell University and his Ph.D. in Operations Research from the Massachusetts Institute of Technology (MIT), followed by a postdoctoral position at IBM's T.J. Watson Research Center focusing on Smarter Commerce technologies.
His research bridges machine learning, analytics, and operations, with dual specializations: (1) developing ML-driven personalization methods for retail, logistics, and travel industries; and (2) creating novel models for revenue and supply chain optimization in e-commerce and service systems. His work emphasizes practical applications of optimization under uncertainty, data-driven decision-making, and algorithmic fairness.
Elmachtoub's publication record demonstrates consistent focus on pricing analytics, revenue management, and operational efficiency, with recent work exploring fairness constraints, reusable resources, and pandemic-responsive systems. His research integrates stochastic modeling, statistical learning, and economic theory to solve complex industrial problems.
Notable scientific recognitions include:
- NSF CAREER Award for foundational contributions to data-driven optimization
- IBM Faculty Award for industry-relevant research
- 1st place in INFORMS JFIG Paper Competition
- Great Teacher Award from the Society of Columbia Graduates
- Forbes 30 Under 30 in Science honor
He maintains active research funding through NSF and IBM collaborations. While specific student advisees are unnamed in available sources, his teaching recognition suggests significant mentoring activities. No explicit details regarding dedicated labs or research teams are documented.
