Welcome to The Salon!

The Salon is a lab dedicated to the study of Statistics, Algorithms, Learning, and OptimizatioN. It is led by Professor Gautam Kamath at the Cheriton School of Computer Science at the University of Waterloo. Current emphases of the lab include enriching our understanding of data privacy and robustness in statistics and machine learning.

The name of The Salon is in reference to the French practice from the 17th and 18th centuries, a central venue for exchange of some of the most important ideas of the era.


  • July 2020: Discovery Grant with Accelerator Supplement awarded by NSERC.
  • June 2020: New paper on arXiv, code available here.
  • May 2020: Two papers ( 1, 2) accepted to COLT 2020. One paper accepted to ICML 2020.
  • April 2020: Survey of differentially private statistics posted on arXiv.
  • April 2020: New paper on arXiv, code available here.
  • March 2020: Resources for Research Groups Grant awarded by Compute Canada (joint with Xi He).
  • February 2020: Four new papers on arXiv: 1, 2, 3, 4.

Recent Publications

Locally Private Hypothesis Selection

Private Mean Estimation of Heavy-Tailed Distributions

Privately Learning Markov Random Fields

CoinPress: Practical Private Mean and Covariance Estimation

INSPECTRE: Privately Estimating the Unseen


Le Salonneur


Gautam Kamath

Professor of Computer Science

Statistics, Machine Learning, Data Privacy, Robustness

Graduate Researchers


Argyris Mouzakis

PhD Computer Science Student

Machine Learning Theory, Algorithmic Statistics, Privacy, Applied Probability


Christian Covington

MMath Computer Science Student

Statistical Validity, Data Privacy, Robustness


Mahbod Majid

MMath Computer Science Student

Private Statistics, Robust Statistics

Undergraduate Researchers


Sourav Biswas

BCS and BBA Dual Degree Student

Statistics, Machine Learning, Computer Vision, Data Privacy


Xingtu Liu

BMath Student

Deep Learning Theory, Machine Learning, Statistics, Optimization

Affiliated Researchers


Pranav Subramani

Research Associate

Probabilistic Programming, Bayesian Inference, Differential Privacy, Adversarial Robustness


Shubhankar Mohapatra

Research Associate

Data Privacy, Machine Learning, Federated Learning, Data Cleaning