picture of me in Milan, Italy

Daniel Alabi

alabid [at] g [dot] harvard [dot] edu
G1 Ph.D. student at Harvard University.

Currently, my research interests (still nascent) are in data systems, graph theory and analytics, algorithms for massive datasets, and large-scale inference.

Previously, I spent a year as a graduate research assistant at Columbia University, working with Prof. Chris Wiggins and Prof. Eugene Wu. Before coming back to academia, I was a Software Engineer on the distributed systems team at MongoDB. I obtained my bachelor's degrees in Mathematics and Computer Science from Carleton College where I was a Kellogg International Scholar.

Selected Projects

See my GitHub page for projects not listed here.
My research was on the use of human perceptual models to make interactive visualizations faster by leveraging approximation (with formal guarantees).
MongoDB-related Projects
While at MongoDB, I made significant contributions to the MongoDB main server, server tools, Rust driver, and hadoop connector.
Collaborative LaTeX editor.


PFunk-H: Approximate Query Processing using Perceptual Models
Daniel Alabi and Eugene Wu.
In Proceedings of the International Workshop on Human-in-the-Loop Data Analytics (HILDA), 2016  [pdf]  [bib]
Selected for full oral presentation
Exploiting Visual Perception for Sampling-Based Approximation on Aggregate Queries
Daniel Alabi.
Columbia University Technical Report No. cucs-019-15


Check out some of my instructional worksheets.