Milind Prabhu

PhD Candidate @UMich, advised by Nikhil Bansal.

I design algorithms for big data.

Recently, I have also been thinking about AI alignment and am currently attending the ILIAD Intensive in the Bay Area.

Portrait of Milind Prabhu

What I work on

Data Compression

Compress large datasets to speed up computation

Load Balancing

Use parallel processors to speed up computation

Selected research

View all publications

Data compression

  1. Coresets for Capacitated Clustering via Dual Concentration SODA 2027 with Chris Schwiegelshohn, Sudarshan Shyam, and Erik Waingarten
  2. Fault Tolerant Coresets NeurIPS 2026 with Chris Schwiegelshohn and Sudarshan Shyam
  3. Sensitivity Sampling for k-Means: Worst Case and Stability Optimal Coreset Bounds FOCS 2024 with Nikhil Bansal, Vincent Cohen-Addad, David Saulpic, and Chris Schwiegelshohn

Load balancing

  1. Online Graph Balancing and the Power of Two Choices FOCS 2026 with Nikhil Bansal, Sahil Singla, and Siddharth M. Sundaram
  2. The Cube-Root Phenomenon in Online Carpooling Preprint 2026 with Nikhil Bansal, Sahil Singla, and Siddharth M. Sundaram
  3. Non-Clairvoyant Scheduling is Hard Even for Trees Preprint 2026 with Kunal Agrawal, Owen Druzgal, and Jinhao Zhao