Home

Welcome to Vijay Gadepally's Webpage.

Dr. Vijay Gadepally is a senior scientist and principal investigator at the Massachusetts Institute of Technology (MIT) Lincoln Laboratory, a Visiting Scientist with MIT Connection Science, and works closely with the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL). At Lincoln Laboratory, Vijay leads the research efforts of the Lincoln Laboratory Supercomputing Center. Vijay’s research interests include high performance computing, artificial intelligence, high performance databases and environmentally-friendly computing. Vijay is also the Chief Technology Officer of Radium Cloud - a company focused on providing high performance cloud computing for AI workloads.
 
Vijay holds a M.Sc. and PhD in Electrical and Computer Engineering from The Ohio State University and a B.Tech degree in Electrical Engineering from the Indian Institute of Technology, Kanpur.  Vijay’s research in high performance computing, artificial intelligence and environmentally-friendly computing has been featured in numerous articles in the popular press and has received numerous scholarly awards at various conferences.  In 2017, Vijay was named to AFCEA’s inaugural 40 under 40 list and was awarded MIT Lincoln Laboratory’s Early Career Technical Achievement Award. In 2011, Vijay received an Outstanding Graduate Student Award at The Ohio State University.

[Google Scholar]

[CV]

Honors & Awards:

  • Outstanding Student Paper Award, Serving Machine Learning Inference Using Heterogeneous Hardware, IEEE HPEC, 2021
  • Outstanding Paper Award, Layer-Parallel Training with GPU Concurrency of Deep Residual Neural Networks Via Nonlinear Multigrid, IEEE HPEC, 2020
  • Outstanding Student Paper Award (finalist), A Survey of Attacks and Defenses of Edge-Deployed Neural Networks, IEEE HPEC, 2019
  • Senior Member, IEEE, 2019
  • Outstanding Paper Award (finalist), Measuring the Impact of Spectre and Meltdown, IEEE HPEC, 2018
  • AFCEA  "40 Under 40 List", AFCEA International, 2017
  • R&D 100 Award Finalist, BigDAWG Polystore System, 2017
  • Early Career Technical Excellence Award, MIT Lincoln Laboratory, 2017
  • MIT Lincoln Laboratory Team Award, 2017
  • Outstanding Student Paper Award (finalist), Cloud-based Large-scale Brain Connectivity Analysis Using Accumulo and D4M, IEEE HPEC, 2017
  • Outstanding Student Paper Award (finalist), Cross-Engine Query Execution in Federated Database Systems, IEEE HPEC, 2016
  • Best Paper Award, Julia Implementation of the Dynamic Distributed Dimensional Data Model, IEEE HPEC, 2016
  • Outstanding Student Paper Award, From NoSQL Accumulo to NewSQL Graphulo: Design and Utility of Graph Algorithms inside a BigTable Database, IEEE HPEC, 2016
  • Best Paper Award (finalist), Benchmarking SciDB Data Import on HPC Systems, IEEE HPEC, 2016
  • Outstanding Student Paper Award (finalist), Improving Big Data Visual Analytics with Interactive Virtual Reality, IEEE HPEC, 2015
  • Outstanding Graduate Student Award, The Ohio State University, 2011

Recent News/Talks:

  • November 2020: AI Challenges Presentation at RAAINS [Slides]
  • August 2020: Poly'20@VLDB Workshop will be held online
  • July 2020: Congratulations to Andew Kirby on an Outstanding Paper Award for his work on "Layer-Parallel Training with GPU Concurrency of Deep Residual Neural Networks Via Nonlinear Multigrid"
  • July 2020: OCW Course online [Video - Introduction to AI] 
  • June 2020: Technical Report on Data Integration and Knowledge Graphs [Report]
  • June 2020: Congratulations to Matthew Hutchinson for winning the J. Francis Reintjes Excellence in 6-A Industrial Practice Award!
  • May 2020: IEEE ICASSP (virtual) conference
  • May 2020: Report on "Building a Working Data Hub" [Report]
  • April 2020: Speaking at ODSC East Conference
  • February 2020: Looking for multiple postdoctoral associates [Link]
  • February 2020: Poly'20 workshop will be held in conjunction with VLDB 2020 [Link]
  • January 2020: Emily's work on Cyber Network Analysis accepted to IEEE ICASSP 2020
  • October 2019: Jeremy's work on network background modeling featured on MIT News [Link]
  • September 2019: White paper on AI Model & Data Sharing [White Paper]
  • September 2019: Course on Networks: Cyber, Social and Neural at MIT
  • July 2019: FastAI Seminar at Wright Brothers Institute
  • June 2019: Congratulations to Mihailo for a Best Student Paper nomination at IEEE HPEC 2019!
  • May 2019: Short white paper on Getting Data Ready for AI [White Paper]
  • April 2019: Technical report on AI Enabling Technologies [Technical Report]