Daniel G. Alabi
Short Bio
I received my Ph.D. in Computer Science from Harvard University, where I was advised by Salil Vadhan. During my program, I was a research intern at Microsoft Research in New England and the Discrete Algorithms Group at Google Research. In 2019, I received an S.M. from Harvard and before that obtained a B.A. in mathematics and a B.A. in computer science from Carleton College.
Research Overview
In general, through the use of (mostly) mathematical tools, I study the limits and capabilities of statistics for computer science applications. Currently, I am particularly interested in understanding the limits of performing computational social science under different constraints. e.g., for learning with limited resources or with privacy. I am also interested in other areas in the general fields of statistics, probability, information theory, machine learning, and theoretical computer science.
Selected Papers
- Hypothesis Testing for Differentially Private Linear Regression
- with Salil Vadhan
- Proceedings of the Advances in Neural Information Processing Systems (NeurIPS), 2022 [arxiv]
- Learning to Prune: Speeding up Repeated Computations
- with Adam Tauman Kalai, Katrina Ligett, Cameron Musco, Christos Tzamos, and Ellen Vitercik
- Proceedings of the Conference on Learning Theory (COLT), 2019 [arxiv] [PMLR]
- Unleashing Linear Optimizers for Group-Fair Learning and Optimization
- with Nicole Immorlica and Adam Tauman Kalai
- Proceedings of the Conference on Learning Theory (COLT), 2018 [arxiv] [PMLR]
- Learning Certifiably Optimal Rule Lists for Categorical Data
- with Elaine Angelino, Nicholas Larus-Stone, Margo Seltzer, and Cynthia Rudin
- Proceedings of the Journal of Machine Learning Research (JMLR), 2018 [arxiv] [JMLR]
Selected Code Artifacts
- FlyLaTeX
- Collaborative LaTeX Editor
- CORELS
- CORELS is a custom discrete optimization technique for building decision/rule lists over a categorical feature space.
Teaching
- Teaching Fellow, Applied Privacy for Data Science (CS 208), Harvard, Spring 2022
- 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