Prashant Pandey

Assistant Professor

Prashant Pandey

Research interests

  • Data management

Education

  • PhD in Computer Science, Stony Brook University

Biography

Prashant Pandey is an assistant professor in the Khoury College of Computer Sciences at Northeastern University, based in Boston.

With the exponential growth in humanity’s ability to generate, acquire, and store data, Pandey is focused on creating scalable data systems with robust theoretical foundations. His goal is to ensure that the next generation of data analysis systems can meet these evolving demands in an equitable way. His work spans the entire spectrum of this challenge, from exploring the theoretical aspects of data structures to addressing the practical issues of scaling data systems. Efficient data management plays a critical role in advancing research across various scientific fields, and Pandey has contributed to interdisciplinary data systems in areas such as computational biology, cybersecurity, stream processing, and storage systems.

Pandey has received the NSF CAREER Award and the IEEE-CS Early Career Researchers Award for Excellence in High Performance Computing. Prior to joining Khoury College, he spent a year as a research scientist at VMware and held postdoctoral research positions at UC Berkeley and Carnegie Mellon University.

Pandey loves the outdoors and spends his free time running, biking, hiking, skiing, and playing cricket and racket sports.

Recent publications

  • Adaptive Quotient Filters

    Citation: Richard Wen, Hunter McCoy, David Tench, Guido Tagliavini, Michael A. Bender, Alex Conway , Martin Farach-Colton, Rob Johnson , Prashant Pandey . (2024). Adaptive Quotient Filters Proc. ACM Manag. Data, 2, 192:1-192:28. https://doi.org/10.1145/3677128
  • BYO: A Unified Framework for Benchmarking Large-Scale Graph Containers

    Citation: Brian Wheatman, Xiaojun Dong , Zheqi Shen, Laxman Dhulipala, Jakub Lacki, Prashant Pandey , Helen Xu . (2024). BYO: A Unified Framework for Benchmarking Large-Scale Graph Containers Proc. VLDB Endow., 17, 2307-2320. https://www.vldb.org/pvldb/vol17/p2307-wheatman.pdf
  • IONIA: High-Performance Replication for Modern Disk-based KV Stores

    Citation: Yi Xu, Henry Zhu, Prashant Pandey , Alex Conway , Rob Johnson , Aishwarya Ganesan, Ramnatthan Alagappan. (2024). IONIA: High-Performance Replication for Modern Disk-based KV Stores FAST, 225-241. https://www.usenix.org/conference/fast24/presentation/xu

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