Prashant Pandey

Assistant Professor

Northeastern University

Biography

I am an Assistant Professor in the Khoury College of Computer Sciences Northeastern University, Boston. I co-direct the Data Lab. I am also an Affiliate Faculty in the Performance and Algorithms Research Group at Berkeley Lab.

My goal as a researcher is to build scalable data systems with strong theoretical guarantees and employ them to democratize next-generation data analyses. My work applies to high-performance computing, computational biology, stream processing, and storage.

Previously, I was a Research Scientist at VMware Research for a year. Prior to that, I did postdocs at UC Berkeley/LBL and Carnegie Mellon University. I obtained my PhD in Computer Science at Stony Brook University in 2018.

I love outdoors and occasionally like to scribble my experience in a blog.

Interests

Large-Scale Data Systems
Graphs Processing
Computational Biology

Education

PhD in Computer Science, 2018

Stony Brook University

Media and Awards

Awards

NSF CAREER: FACULTY EARLY CAREER DEVELOPMENT AWARD 2024
IEEE-CS Early Career Researchers Award for Excellence in High Performance Computing 2023
Catacosinos Fellowship for Excellence in Computer Science Research 2018
Best paper award at FAST 2016
Runners-Up to the best paper award at FAST 2015

Grants

NSF CAREER Award (2024)
One Utah Data Science Hub Seed Grant (2024)
DOE Exascale Computing Project (ECP) Award (2022)

Media

Projects

A Compact, Dynamic, and Distributed GPU Data Structure Library

Fast and Space-Efficient In-Memory Indexes (Hash Tables, B-trees)

Scalable and Real-Time Stream Monitoring using External Memnory

A Comprehensive Dynamic-Graph System for Modern Applications

Scalable, Real-Time, and Information-Rich Sequence Search Over SRA

Adaptive and High-performance Filters for Modern Workloads

Recent & Upcoming Talks

From Hash Tables to B-trees: Rethinking Core Data Structures for Scalable Performance

May 2, 2025 10:19 AM — 10:19 AM Banglore India

Dynamic Graphs: Containers, Frameworks, and Benchmarks

Mar 2, 2025 4:10 PM — 4:10 PM Las Vegas, Nevada US

Data Systems at Scale

Nov 1, 2024 4:06 PM — 4:06 PM Merced, California US

Adaptive Quotient Filters: How to Learn from Your Mistakes

Jul 3, 2024 3:58 PM — 3:58 PM Shonan, Japan

Beyond Bloom: A Tutorial on Future Feature-Rich Filters

Jun 14, 2024 3:50 PM — 3:50 PM Santiago, Chile

See all events

All Publications

Yuvaraj Chesetti, Prashant Pandey (2025). Evaluating Learned Indexes for External-Memory Joins. ACDA 2025.

PDF Code Project

Yuvaraj Chesetti, Benwei Shi, Jeff M. Phillips, Prashant Pandey (2025). Zombie Hashing: Reanimating Tombstones in a Graveyard. SIGMOD 2025.

PDF Code Project

Richard Wen, Hunter McCoy, David Tench, Guido Tagliavini, Michael Bender, Alex Conway, Martin Farach-Colton, Rob Johnson, Prashant Pandey (2025). Adaptive Quotient Filters. SIGMOD 2025.

PDF Cite Code Project

Brian Wheatman, Xiaojun Dong, Zheqi Shen, Laxman Dhulipala, Jakub Łącki, Prashant Pandey, Helen Xu (2024). BYO: A Unified Framework for Benchmarking Large-Scale Graph Containers. VLDB 2024.

Code Project

Prashant Pandey, Martin Farach-Colton, Niv Dayan, Huanchen Zhang (2024). Beyond Bloom: A Tutorial on Future Feature-Rich Filters. SIGMOD 2024.

PDF Cite Project

See all publications