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

My primary research interests lie at the intersection of algorithms and information security (e.g., data privacy, security).

Currently, my focus is on the design, analysis, and limitations of algorithms in settings where we need to ensure individual data privacy guarantees. In particular, I'm interested in the tradeoffs in computational and statistical resources that result when we require individual privacy guarantees and, as a consequence, the robustness of 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.

Funding Acknowledgements: My research was/is supported by Harvard SEAS, Harvard CRCS, Facebook, and the Courtlandt S. Gross Memorial Scholarship.

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

See all papers here.

Selected Code Artifacts

FlyLaTeX
Collaborative LaTeX Editor
CORELS
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

  • 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