Michael Huang

Michael Huang is an Assistant Professor at the Zicklin School of Business, Baruch College, where he serves in the N. Paul Loomba Department of Management. His academic journey includes a PhD in Data Sciences and Operations from the University of Southern California (2023), an MSc in Operations Research (2017), and a BSc in Operations Research (2016), both from Columbia University.

• PhD, Data Sciences and Operations, University of Southern California, 2023
• MSc, Operations Research, Columbia University, 2017
• BSc, Operations Research, Columbia University, 2016

Huang’s research bridges machine learning with operations management, focusing on data-driven optimization and decision-aware learning. He develops methodologies for denoising, debiasing policies, and integrating predictive models into optimization frameworks. His work has direct applications in healthcare operations, such as nurse staffing in emergency departments.

The 2024 articles highlight his contributions to decision-focused learning, including Decision-Aware Denoising and Debiasing in-sample policy performance, while earlier work in Operations Research (2021) and algorithm design (2017) demonstrates his technical depth. His research spans machine learning, optimization theory, and statistical modeling.

Scientific Awards

• Marshall PhD Teaching Award (2022)
• Marshall PhD Fellowship (2021)
• Marshall Outstanding Researcher Award (2021)
• The Robert Gartland Fellowship (2016)

Huang actively participates in academic service as a reviewer and session chair for top-tier conferences and journals, including NeurIPS, INFORMS, and ICML.