Me

Argyris Mouzakis

IFML Postdoctoral Fellow
Department of Computer Science
The University of Texas at Austin
Office: GDC 4.502
2317 Speedway, Austin, TX 78712
argymouz@cs.utexas.edu

Hello! I am an IFML Postdoctoral Fellow in the Department of Computer Science at the University of Texas at Austin, hosted by Kevin Tian. Prior to that, I was a PhD student at the University of Waterloo's Cheriton School of Computer Science, where I was very fortunate to be advised by Gautam Kamath. My interests broadly lie at the intersection of Computer Science and Statistics, with a particular focus on Machine Learning Theory, Algorithmic Statistics, and Differential Privacy. Even before joining UWaterloo, I did my undergrad in Electrical and Computer Engineering at the National Technical University of Athens, where I was very fortunate to be advised by Dimitris Fotakis. [CV] [Last Updated: Sept. 2026]
Here's a tutorial about how to pronounce my name. If it's hard for you, I'm happy with people calling me Argy (RG). :)

Pronouns: I identify as a cisgender man, but I am fine with anything respectful.


Publications and Manuscripts

For the following list, author names are in alphabetical order, as is customary in TCS (unless clearly stated otherwise). Depending on when you're looking, the list may or may not be up-to-date, so here's my (more likely to be up-to-date) DBLP and Google Scholar profiles.

Robust Statistical Estimators with Bounded Empirical Sensitivity

Manuscript in Submission

Optimal Differentially Private Sampling of Unbounded Gaussians

Valentio Iverson, Gautam Kamath, Argyris Mouzakis
COLT 2025; TPDP 2025

Private Mean Estimation with Person-Level Differential Privacy

SODA 2025; TPDP 2025

Not All Learnable Distribution Classes are Privately Learnable

ALT 2024

A Bias-Variance-Privacy Trilemma for Statistical Estimation

Journal of the American Statistical Association (JASA) 2025; TPDP 2023

New Lower Bounds for Private Estimation and a Generalized Fingerprinting Lemma

Gautam Kamath, Argyris Mouzakis, Vikrant Singhal
NeurIPS 2022; TPDP 2022

A Private and Computationally Efficient Estimator for Unbounded Gaussians

COLT 2022; TPDP 2022