H. Satyam Verma

PhD Candidate in Operations Management

Tepper School of Business, Carnegie Mellon University

Human-AI Collaboration · Pricing, Policy, and Consumer Behavior in Health Care Markets · Operations Management · Business Analytics

Curriculum Vitae Google Scholar Email
Portrait of H. Satyam Verma

About

I am a PhD candidate in Operations Management at the Tepper School of Business, Carnegie Mellon University, advised by Sridhar R. Tayur. My research focuses on two distinct streams. The first examines human-AI collaboration during model training and deployment, exploring how algorithms can optimally integrate input from domain experts who are imperfect yet irreplaceable. The second stream investigates pricing, policy, and consumer behavior in healthcare markets. Within this area, I analyze how prices are privately negotiated, the impact of price transparency policies, and the subsequent responses from patients and employers. While healthcare currently serves as the primary empirical setting for both areas, the foundational challenges I study extend far beyond it. This is particularly true for my work on algorithmic decision-making, which addresses universal problems of learning under limited data and constrained expert bandwidth.

Before CMU, I earned an M.Sc. in Operations Research from IIT Bombay and worked as a Data Scientist on the optimization team at Delhivery, India's largest fully integrated logistics company, building large-scale optimization models for network operations across assignment, routing, and facility location problems.

I will be on the academic job market in Fall 2026, seeking faculty positions beginning Fall 2027 in Operations Management, Business Analytics, and Healthcare Operations.

Research

Working Papers

GenEx: Generative Augmentation of Scarce Data through Expert Guidance for Personalized Dosing [SSRN]

H. S. Verma, H. Wiberg, S. (Woody) Zhu, and S. R. Tayur

Manufacturing & Service Operations Management (M&SOM) · Major Revision

Runner-Up, INFORMS Health Applications Society Best Student Paper Competition (2025)

Transparency Without Parity

H. S. Verma, D. Agrawal, A. Hosseininasab, and S. R. Tayur

Working Paper

Published Journal & Conference Articles

Multi-page Menu Recommendation in Cascade Model with Externalities [DOI]

R. Dhingra, H. S. Verma, A. Reiffers-Masson, and V. Kavitha

60th IEEE Conference on Decision and Control (CDC) · 2021

Scalable Multi-Product Inventory Control with Lead Time Constraints Using Reinforcement Learning [DOI]

H. Meisheri et al., including H. S. Verma

Neural Computing and Applications · 2022

Presentations

  • GenEx: Generative Augmentation of Scarce Data through Expert Guidance for Personalized Dosing
    INFORMS Annual Meeting, San Francisco (2026) · INFORMS Healthcare Conference (2026) · NeurIPS ML × OR Workshop, poster (2025) · INFORMS Annual Meeting, Atlanta (2025) · INFORMS Workshop on Data Science (2025) · Cornell ORIE Young Researchers Workshop (2025) · POMS Conference (2025)
    Earlier versions of this work were presented in 2025 under the titles “Data to Dose” and “Improved Personalized Drug Dosing through Data Generation and Expert Feedback.”
  • Transparency Without Parity
    Midwest Healthcare Management Conference (2026) · INFORMS Healthcare Conference (2026) · POMS Conference (2026)
  • Multi-page Menu Recommendation in Cascade Model with Externalities
    IEEE Conference on Decision and Control, CDC (2021)

Teaching

Instructor

  • TA Training Course Teaching Assistants, Tepper Undergraduate Economics
    Carnegie Mellon University · Fall 2026

Teaching Assistant

  • Operations Management MBA & Undergraduate Core
    Carnegie Mellon University · Fall 2024, Spring 2025, Fall 2025
  • Operations and Supply Chain Analytics MBA & Undergraduate Elective
    Carnegie Mellon University · Spring 2024, Spring 2026
  • Supply Chain Management MBA & Undergraduate Elective
    Carnegie Mellon University · Spring 2026
  • Service Management: Go-to-Market Strategy MBA Elective
    Carnegie Mellon University · Fall 2025
  • Probability and Stochastic Models I & Stochastic Processes II M.Sc. Operations Research Core
    IIT Bombay · Fall 2020, Spring 2021

Teaching Interests

Operations Management · Healthcare Operations · Stochastic Models · Machine Learning for Business · Data Analytics & Optimization

Honors & Awards

  • 2025 Runner-Up, INFORMS Health Applications Society Best Student Paper Competition
  • 2024 Generative AI Fellowship, Center for Intelligent Business, Tepper School of Business
  • 2022 William Larimer Mellon Fellowship, Tepper School of Business
  • 2018 All-India Rank 8, Joint Admission to M.Sc. (JAM) Mathematics

Service

Contact

Outside of research, I play guitar, piano, and drums, and I write and compose music.