Harsha Vardhan Simhadri

Partner Researcher, Microsoft Azure

email LinkedIn page Microsoft Research Wegpage GitHub DBLP

I enjoy developing new algorithms motivated by real-world applications and systems. My PhD thesis developed parallel algorithms and run-times with provable guarantees for multi-core processors. Subsequently, I worked with an amazing team at Microsoft Research India and developing new ML operators and architectures for tiny IoT and edge devices (EdgeML).

In 2018, we started the DiskANN project for Approximate Nearest Neighbor Search (ANNS) to address the large gap between research and practice. It achieved many of its goals and has been adopted widely in Microsoft and rest of the industry. See an overview of the project with references, and a talk on some of these ideas from the Northwestern IDEAL workshop (slides).

Publications

Thesis
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)

Earlier
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.