I am a final-year Ph.D. candidate at Stanford University in the Operations Research group within the department of Management Science & Engineering, where I am advised by Amin Saberi. Before coming to Stanford, I received my B.Sc. in Computer Engineering with a minor in Mathematics from the Sharif University of Technology. In 2022, I was a research fellow at the Simons Institute Theory for Computing, and I interned at Google Research, hosted by Aranyak Mehta.

My research centers on learning and decision-making using network data. From a theoretical perspective, I integrate tools from applied probability, algorithms, and the theory of graph limits. On the practical front, I am inspired by addressing tangible real-world challenges in business operations, such as healthcare and online markets, that can be modeled and analyzed using network data.

I’m on the 2023-2024 job market.

Email: [my first name]@stanford.edu.

If you’ve ever stumbled over my name (Yeganeh /jegɒnɛ/), click to learn more. It’s pronounced ‘Yeay gone eh’—- say it swiftly, allowing the second ‘y’ to gracefully blend. To break it down, start with ‘Yeay!’ as if you just cracked a challenging problem, followed by ‘gone’ as in something mysteriously disappeared, and end with ‘eh’ like you’re asking a thoughtful question. Thanks for taking the time to get it right!

Upcoming talks at INFORMS 2023

Epidemic Prediction and Control, Learning from Network Data
Session: Data, Learning, and Decision-Making (TC45)
Date & Time: Tuesday, Oct. 17, 12:45-­2 pm

Incentive Compatibility in the Auto-Bidding World
Session: Economics and Computation I (SA74)
Date & Time: Sunday, Oct. 15, 8-9:15 am

Selected Publications

Epidemic Forecasting on Networks: Bridging Local Samples to with Global Outcomes, with Christian Borgs, Remco van der Hofstad and Amin Saberi,
Submitted. [paper]

Sequential Importance Sampling for Estimating Expectations over the Space of Perfect Matchings, with Persi Diaconis, Mohammad Roghani and Amin Saberi,
Annals of Applied Probability. [paper]

Locality of Random Digraphs on Expanders, with Christian Borgs and Amin Saberi,
Annals of Probability. [paper]

For the full list of my publications, click here.


  • Sep. 2023: New paper is out: "Epidemic Forecasting on Networks: Bridging Local Samples to with Global Outcomes" with Christian Borgs, Remco van der Hofstad, Amin Saberi, [paper].
  • Jul. 2023: New paper "Locality of random digraphs on expanders" with Christian Borgs, Amin Saberi published in [Annals of Probability].
  • May. 2023: New paper "Incentive Compatibility in the Auto-bidding World" with Aranyak Mehta and Andres Perlroth accepted in [ACM EC'23].
  • Apr. 2023: New paper "Sequential Importance Sampling for Estimating Expectations over the Space of Perfect Matchings" with Persi Diaconis, Mohammad Roghani, Amin Saberi published in [Annals of Applied Probability].
  • Fall 2022: [Research fellow] at Simons Institute for the Theory of Computing at UC Berkeley.

Selected talks

  • Epidemic Prediction and Control: Insights from Network Analysis
    • INFORMS Annual Meeting (Oct. 2023) - Invited Speaker
    • ACM Economics and Computation (Jul. 2023) - Rising Star
    • University of Chicago Booth, Brown Bag Seminar (May 2023) - Invited Speaker
    • The Fields Institute for Research in Mathematical Sciences, Workshop on Algorithms and Models for the Web Graph (May 2023) - Plenary Speaker

  • A Few Local Samples to Predict Epidemics on Networks
    • London School of Economics, Statistics Seminar (Mar. 2023) - Invited Speaker
    • Duke Fuqua, Workshop on Operations Research and Data Structures (Nov. 2022) - Invited Speaker
    • Cornell University ORIE Young Researcher Workshop (Oct. 2022) - Invited Speaker
    • Simons Institute at UC Berkeley (Sept 2022) - Invited Speaker

  • Network models for school reopening during COVID-19
    • INFORMS Healthcare Meeting (Jul. 2023) - Invited Speaker
    • Brin Mathematics Research Center, University of Maryland (Apr. 2023) - Invited Speaker
    • INFORMS Healthcare Meeting (Jul. 2021) - Invited Speaker

For the full list of talks, click here.


During 2019-2021, I was a mentor and an organizing board member for Stanford Women in Math Mentoring (SWIMM), a program supporting undergraduates from diverse backgrounds with a passion for math and computational sciences. I also mentored undergraduates in Stanford’s Math Directed Reading Program and MS&E Undergraduate Diversity in Research.


  • Program Committee ACM Conference on Economics and Computation (EC 2023)
  • Journal Reviewer Management Science, Annals of Applied Probability, Review of Economics Studies, Computational and Applied Mathematics
  • Conference Reviewer ACM Conference on Economics and Computation (EC), ACM Symposium on Theory of Computing (STOC), Symposium on Discrete Algorithms (SODA), Innovations in Theoretical Computer Science (ITCS), World Wide Web (WWW), European Symposium on Algorithms (ESA)