Moeen Nehzati

Office 630

19 West 4th Street

New York, NY 10003

I'm a Ph.D. student in the NYU Department of Economics. My interests are primarily methodological: I like playing with mathematical and computational ideas, and right now I'm applying them to problems in economics.

My current work draws on geometric and measure-theoretic ideas in high- and infinite-dimensional spaces. I study genericity and prevalence, optimal transport, and nonconvex optimization, mostly with applications to economic and statistical models.

I'm bad at bookkeeping, but fairly crafty about getting computers to compensate for it. Over the years, that has meant simulation, symbolic computation, and all sorts of computational sanity checks. These days, the new toy is AI. I'm particularly interested in AI for science and agentic programming, and Famulus is my main experiment in getting more leverage out of these tools for research and programming.

More broadly, my theoretical interests range across analysis, algorithms and complexity, mathematical logic, optimization, and related areas of mathematics and theoretical computer science. Before NYU, I worked on large-scale statistical genetics at UCLA and as an auction design consultant at Cafe Bazaar, optimizing online ad auctions. A while before all that, I earned my B.Sc. in Computer Engineering from Sharif University of Technology.

Outside of work, I get overly excited by cats, cooking and baking, fantasy (unfortunately not LOTR), modern history—especially the Middle East—foundations of mathematics, and getting out into nature for backpacking.

news

Apr 30, 2026	My paper Universal Representation of Generalized Convex Functions and their Gradients was accepted to ICML.

selected publications

ICML

Universal Representation of Generalized Convex Functions and their Gradients

Moeen Nehzati

ICML, 2026

Bib Link

@article{nehzati2025universal,
  title = {Universal Representation of Generalized Convex Functions and their Gradients},
  author = {Nehzati, Moeen},
  year = {2026},
  eprint = {2509.04477},
  archiveprefix = {arXiv},
  primaryclass = {math.OC},
  url = {https://arxiv.org/abs/2509.04477},
  keywords = {published},
  publisher = {ICML}
}

Nat. Genet.

Family-based genome-wide association study designs for increased power and robustness

Junming Guan, Tammy Tan, Seyed Moeen Nehzati , and 4 more authors

Nature Genetics, 2025

Bib Link

@article{guan2025family,
  title = {Family-based genome-wide association study designs for increased power and robustness},
  author = {Guan, Junming and Tan, Tammy and Nehzati, Seyed Moeen and Bennett, Michael and Turley, Patrick and Benjamin, Daniel J and Young, Alexander Strudwick},
  journal = {Nature Genetics},
  pages = {1--9},
  year = {2025},
  publisher = {Nature Publishing Group US New York},
  url = {https://www.nature.com/articles/s41588-025-02118-0},
  keywords = {published}
}

Nat. Genet.

Mendelian imputation of parental genotypes improves estimates of direct genetic effects

Alexander Young, Moeen Nehzati, Stefania Benonisdottir , and 7 more authors

Nature Genetics, 2022

Bib Link

@article{young2022mendelian,
  title = {Mendelian imputation of parental genotypes improves estimates of direct genetic effects},
  author = {Young, Alexander and Nehzati, Moeen and Benonisdottir, Stefania and Okbay, Aysu and Jayashankar, Hariharan and Lee, Chanwook and Cesarini, David and Benjamin, Daniel J and Turley, Patrick and Kong, Augustine},
  journal = {Nature Genetics},
  volume = {54},
  number = {6},
  pages = {897--905},
  year = {2022},
  publisher = {Nature Publishing Group US New York},
  url = {https://www.nature.com/articles/s41588-022-01085-0},
  keywords = {published}
}