picture of me taken by Sury.

Daniel Alabi

alabid [at] g [dot] harvard [dot] edu
Harvard University
Advised by Salil Vadhan
Ph.D. student in the Theory of Computation group and the Harvard Privacy Tools group
Photo credit: My neighbor Sury @scrodcity

Primary Research Interests: Algorithms, Learning Theory, Information Theory
Some Application Areas: Privacy, Statistics, Social Sciences, Machine Learning, Quantum Computing

In particular, I'm interested in the tradeoffs in computational and statistical resources that result when we require provable guarantees (e.g., for privacy) on statistical models and machine learning predictors. Example computational resources include time, memory, randomness, communication, and parallelism. Example statistical resources include samples (or labeled examples for classification or regression) drawn from an unknown distribution.

Previous/Current Research Funding: Harvard SEAS and CRCS, Facebook AI, and the Courtlandt S. Gross Memorial Scholarship
Previous/Current Research Internship Experience: Microsoft Research (w/ Adam Kalai), Google Research (w/ Ravi Kumar)

Personal: I am Nigerian and a member of Harvard's competitive Ballroom Dance Team.

Selected Research

Differentially Private Simple Linear Regression
with Audra McMillan, Jayshree Sarathy, Adam Smith, and Salil Vadhan
Learning to Prune: Speeding up Repeated Computations
with Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, and Ellen Vitercik
COLT, 2019  [arxiv]  [PMLR] 
Unleashing Linear Optimizers for Group-Fair Learning and Optimization
with Nicole Immorlica and Adam Tauman Kalai
COLT, 2018  [arxiv]  [PMLR] 
Learning Certifiably Optimal Rule Lists for Categorical Data
with Elaine Angelino, Nicholas Larus-Stone, Margo Seltzer, and Cynthia Rudin
JMLR, 2018  [arxiv]  [JMLR] 

See all papers here.

Selected Code Artifacts

Collaborative LaTeX Editor
CORELS is a custom discrete optimization technique for building rule lists over a categorical feature space.
See my GitHub page for some more code artifacts not listed here.


  • Teaching Fellow, Algorithms at the End of the Wire (CS 222), Harvard, Fall 2020
  • Teaching Fellow, Algorithms & Data Structures (CS 124), Harvard, Spring 2018
  • Teaching Assistant, Data Structures (CS 201), Carleton College, Winter & Spring 2014
  • Teaching Assistant, Intro to Computer Science (CS 111), Carleton College, Fall 2013