Yeganeh Alimohammadi

Yeganeh
Alimohammadi

Assistant Professor of Data Sciences & Operations
USC Marshall School of Business

I design principled methods for learning and decision-making in complex systems where data is incomplete, costly to collect, or shaped by strategic behavior. Drawing on tools from applied probability, optimization, and algorithm design, my work builds robust, data-efficient algorithms for reliable inference and intervention.

Previously: UC President's Postdoctoral Fellow at Berkeley, Ph.D. in Operations Research at Stanford, research fellow at the Simons Institute, B.Sc. from Sharif University of Technology.

If you've ever stumbled over my name (Yeganeh /jeɡɒnɛ/), click here.

It's pronounced "Yeah Gone Eh" — say it swiftly, letting the second syllable blend in. To break it down: start with "Yeah!" like you just got something right, follow with "gone" like something mysteriously disappeared, and end with "eh" like you're asking a thoughtful question. Thanks for taking the time to get it right.

— RECENT NEWS

2026 "Epidemic Forecasting on Networks" accepted at Operations Research.
2026 Amer Goel (PhD advisee) awarded the NSF Graduate Research Fellowship.
May 2026 Organizing SoCal OR/OM Day at USC Marshall, May 29.
2026 Serving as Senior PC member for ACM EC 2026.
Fall 2025 Teaching DSO 576: Algorithmic Thinking with Python (190 students, MSBA core).
Sep 2025 Joined USC Marshall as Assistant Professor of Data Sciences & Operations.

— RESEARCH

Working papers

Y. Alimohammadi, R. Galgana, N. Golrezaei. “The Value of User Expressiveness with a Strategic Recommender.”
arXivslidesvideo
abstract

Abstract coming soon.

Y. Alimohammadi, G. Mantegazza. “Information Sharing in Conversational Ad Auctions.”
arXivslidesvideo
abstract

Abstract coming soon.

Y. Alimohammadi, C. Borgs, J. Chayes, K. Huang. “Auditing the Auditors: Does Community-based Moderation Get It Right?.”
arXivslidesvideo
abstract

Abstract coming soon.

Y. Alimohammadi, K. Asgari. “How to Measure Differences in Ranking Models? Maximum Likelihood Estimation and Sampling from Mallows Model with Learned Metric.”
arXivslidesvideo
abstract

Abstract coming soon.

Y. Alimohammadi, S. Isik, A. Saberi. “Local Limits of Small-World Networks.”
arXivslidesvideo
abstract

Abstract coming soon.

Refereed journal publications

Y. Alimohammadi, C. Borgs, R. van der Hofstad, A. Saberi. “Epidemic Forecasting on Networks: Bridging Local Samples with Global Outcomes.” Operations Research, 2026.
arXivslidesvideo
abstract

Abstract coming soon.

Y. Alimohammadi, C. Borgs, A. Saberi. “Locality of Random Digraphs on Expanders.” Annals of Probability, 2023.
arXivslidesvideo
abstract

Abstract coming soon.

Y. Alimohammadi, P. Diaconis, M. Roghani, A. Saberi. “Sequential Importance Sampling for Estimating Expectations over the Space of Perfect Matchings.” Annals of Applied Probability, 2023.
arXivslidesvideo
abstract

Abstract coming soon.

Y. Alimohammadi, K. Shiragur, R. Johari, D. Scheinker, K. Schulman, K. Staudenmayer. “Relative-Risk and the Assessment of School Safety in the COVID-19 Pandemic: Schools May Offer Students Shelter from the Storm.” Health Management, Policy, and Innovation, 2021.
arXivslidesvideo
abstract

Abstract coming soon.

Refereed conference proceedings

Y. Alimohammadi, L. Ruiz, A. Saberi. “A Local Graph Limits Perspective on Sampling-Based Graph Neural Networks.” ISIT, 2025.
arXivslidesvideo
abstract

Abstract coming soon.

Y. Alimohammadi, A. Mehta, A. Perlroth. “Incentive Compatibility in the Auto-bidding World.” EC, 2023.
arXivslidesvideo
abstract

Abstract coming soon.

Y. Alimohammadi, C. Borgs, A. Saberi. “Algorithms Using Local Graph Features to Predict Epidemics.” SODA, 2022.
arXivslidesvideo
abstract

Abstract coming soon.

M. Akbarpour, Y. Alimohammadi, S. Li, A. Saberi. “The Value of Excess Supply in Spatial Matching Markets.” EC, 2022.
arXivslidesvideo
abstract

Abstract coming soon.

Y. Alimohammadi, N. Anari, K. Shiragur, T.-D. Vuong. “Fractionally Log-Concave and Sector-Stable Polynomials: Counting Planar Matchings and More.” STOC, 2021.
arXivslidesvideo
abstract

Abstract coming soon.

— TEACHING

USC Marshall (instructor)

DSO 576: Algorithmic Thinking with Python · Fall 2025
Core course for the MS in Business Analytics. Class size 190.

Stanford (teaching assistant)

CS 265: Randomized Algorithms and Probability Methods · Winter 2022
MS&E 235/337: Network Structure and Epidemics · Fall 2020
CS 161: Design and Analysis of Algorithms · Summer 2019

— SERVICE

Conference program committees

Senior PC, ACM Conference on Economics and Computation (EC) 2026
PC: EC 2023 & 2025 · WINE 2024 · ML×OR Workshop, NeurIPS 2025

Journal reviewing

Annals of Probability · Annals of Applied Probability · Operations Research · Management Science · Review of Economic Studies · Mathematics of Operations Research · Computational Statistics and Data Analysis · Computational and Applied Mathematics

Seminar organization

USC Operations Management Seminar · 2025–present
Operations Research Student Seminar, Stanford (co-founded) · 2021–2023

Students & mentoring

Amer Goel (USC, co-advised with Andrew Daw) · NSF Graduate Research Fellowship, 2026
Kiana Asgari (Stanford) · Senem Isik (Stanford) — mentees

— HONORS & CONTACT

Selected honors

2024 · UC President's Postdoctoral Fellowship (2.6% acceptance in Engineering)
2022 · Simons Institute Research Fellowship, UC Berkeley
2021–22 · Myron J. Stolaroff Fellowship, Stanford
2019–23 · Dantzig–Lieberman Operations Research Funds, Stanford
2014 · Bronze Medal, International Mathematical Olympiad
2013 · Gold Medal, Iranian National Mathematical Olympiad

Contact

Download CV · Google Scholar · GitHub · LinkedIn