Harsha Vardhan Simhadri

Senior Principal Researcher, Microsoft

email LinkedIn page Microsoft Research Wegpage GitHub DBLP

I develop new algorithms with a view towards future platforms and practical systems. A few examples:

  • Efficient algorithms for web-scale nearest-neighbor search deployed widely in Microsoft and elsewhere (DiskANN)
  • New ML operators and architectures for tiny IoT and edge devices (EdgeML)
  • Parallel algorithms and run-times with provable guarantees for multi-core processors (PhD thesis)

I lead the organization of the 2023 Big ANN NeurIPS challenge on Approximate Nearest Neighbor Search. If you have a strong ANNS algorithm, please submit your idea through this evaluation framework.

Slides on DiskANN from recent seminars and a recording from Northwestern IDEAL workshop.


Program-Centric Cost Models for Locality and Parallelism

Students I have worked with
Grace Dinh, Chirag Gupta, Srajan Garg, Don Dennis, Shishir Patil, Suhas Jayaram Subramanya, Abhishek Panigrahi, Saching Goyal, Moksh Jain, Oindrila Saha, Aditi Singh

Teaching Assistant

  • 15-750: Graduate Algorithms (Spring 2011)
  • 15-499: Parallel Algorithms (Spring 2009)

2013-2016: Postdoctoral Fellow, CS Department, Lawrence Berkeley National Lab.
2007-2013: Ph.D., CS Department, Carnegie Mellon University, Advisor: Guy Blelloch
2003-2007: B.Tech, IIT Madras, Major: CS, Minor: Physics.