Prashant Pandey

Prashant Pandey

Assistant Professor

University of Utah


I am an Assistant Professor in the School of computing at the University of Utah. I co-direct UtahDB Lab. I am also a core member of Utah Center For Data Science.

My goal as a researcher is to advance the theory and practice of resource-efficient data structures and employ them to democratize complex and large-scale data analyses. I work on building tools for large-scale data management problems across computational biology, stream processing, and storage.

Previously, I did a postdoc at UC Berkeley working with Prof. Aydin Buluc and Prof. Katherine Yelick. Prior to that, I spent one year as a Postdoc at Carnegie Mellon University working with Prof. Carl Kingsford. I obtained my Ph.D. in Computer Science at Stony Brook University, and defended my dissertation, Fast and Space-Efficient Maps: Shrinking Big Data Down to Size. At Stony brook University, I was co-advised by Prof. Michael Bender and Prof. Rob Johnson. (Dissertation committee: Mike Ferdman, Rob Patro, Guy Blelloch.)

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

I’m looking for self-motivated students. Drop me a note if you want to do cool research, run/hike in the mountains, and enjoy the world famous ski in Salt Lake City.

  • Data Structures for Big Data
  • Graphs Processing
  • Computational Biology
  • Scalable Graph Neural Networks
  • PhD in Computer Science, 2018

    Stony Brook University

Recent & Upcoming Talks

Scalability Challenges in Large-Scale Sequence Search
Data Systems at Scale: Scaling Up by Scaling Down and Out
Time to Change Your Filter

Recent Publications

(2022). Communication Optimization for Distributed Execution of Graph Neural Networks. IPDPS 23.

(2022). High-Performance Filters for GPUs. PPOPP 23.

(2022). Distance and Time Sensitive Filters for Similarity Search in Trajectory Datasets. APOCS 23.

(2022). IcebergHT: High Performance PMEM Hash Tables Through Stability and Low Associativity. SIGMOD 2023.

(2022). Using Advanced Data Structures to Enable Responsive Security Monitoring. Cluster Computing 2022.

PDF Cite Project


  • Hunter McCoy PhD (Started Fall 2022)
  • Manoj Marneni MS (Started Fall 2022)
  • Alex Tokita BS (Started Fall 2022)
  • Richard Lettich BS UC Berkeley (Started Fall 2022)

Academic Service


  • PC: SIGMOD 2024


  • PC: VLDB 2023, SIGMOD ARC 2023, SPAA 2023, IPDPS 2023
  • External Reviewer: SODA 2023
  • Journal of Computational Biology (2023)


  • PC: IEEE BigData 2022, ACM BCB 2022, APOCS 2022, IPDPS 2022
  • External Reviewer: FAST 2022
  • Oxford BIOINFORMATICS (2022)
  • Journal of Computational Biology (2022)
  • Transactions on Knowledge and Data Engineering (TKDE) (2022)


  • PC: ACDA 2021, RECOMB-Seq 2021, IPDPS 2021, ALENEX 2021
  • Subreviewer: ISMB 2021, STACS 2021, HPEC 2021
  • Session Chair: ALENEX 2021
  • Journal of Computational Biology (2021)
  • Transactions on Knowledge and Data Engineering (TKDE) (2021)
  • IEEE Access (2021)


  • PC: EUROPAR 2020, RECOMB-Seq 2020
  • Subreviewer: RECOMB 2020
  • Oxford BIOINFORMATICS (2020)
  • Transactions on Parallel and Distributed Systems (TPDS) (2020)


  • PC: ESA 2019
  • Subreviewer: WABI 2019, CIAC 2019
  • IEEE Access (2019)
  • Oxford BIOINFORMATICS (2019)
  • Journal of Experimental Algorithms (JEA) (2019)


  • Oxford BIOINFORMATICS (2018)
  • Transactions on Databases (TODS) (2018)