Cyrus Cousins

The Life and Times of Cyrus Cousins

Finitely Wise, Infinitely Curious

About Me

Abridged Biography

I am Cyrus Cousins, a recent Ph.D. graduate of Brown University in the BIGDATA group, under the tutelage of the great Eli Upfal. Before coming to Brown, I earned my undergraduate degree in computer science, mathematics, and biology from Tufts University. My research interests lie primarily in showing novel techniques to bound uniform convergence rates and generalization error in exotic settings, and applying these bounds to tasks of real-world interest, most notably in data science, empirical game theory, and fair machine learning.

My favorite theorem is the Dvoretzky-Kiefer-Wolfowitz Inequality, and my favorite algorithm is simulated annealing.

Research Overview

The best (mostly current) overview of my research is given in my thesis summary (4 pages). The piece is a non-mathematical, but still somewhat technical, overview of my dissertation.

The best mathematical overview of my research for general audiences is given in this piece. Here the focus is less on applications and implications, and more on intuition for the deeper mathematical connections between my various areas of study. Results are selected for elegance and simplicity, and the piece should be broadly accessible to all audiences with a basic grounding in probability and statistics.

Cyrus Cousins

News

2021

2020

  • I survived an apocalyptic event, largely by staying inside, writing my dissertation, and publishing many papers.

2019

  • I will be returning to Two Sigma Investments to work with Larry Rudolph.

2018

  • I have accepted a summer internship offer with Two Sigma Investments working with Matteo Riondato in the Labs group.


Major Projects

  1. Making mean-estimation more efficient using an MCMC trace variance approach: DynaMITE
  2. An Axiomatic Theory of Provably-Fair Welfare-Centric Machine Learning
  3. Adversarial Multi Class Learning under Weak Supervision with Performance Guarantees
  4. Sharp Uniform Convergence Bounds through Empirical Centralization
  5. CADET: Interpretable Parametric Conditional Density Estimation with Decision Trees and Forests
  6. Empirical Game Theoretic Analysis

My dissertation: Bounds and Applications of Concentration of Measure in Fair Machine Learning and Data Science




A Complete List of Publications

Find My Work

  1. DBLP
  2. Google Scholar
  3. ArXiv
  4. ResearchGate
  5. Scopus





Teaching

Professor

Graduate TA



Curriculum Vitae