Tushar Krishna

Associate Professor

Contact

  • Office: Klaus Advanced Computing Center, Room 2318
  • Mailing Address: 266 Ferst Drive, Atlanta, GA 30332
  • Email: tushar <at> ece <dot> gatech <dot> edu

Education

  • PhD in Electrical Engineering and Computer Science, MIT, 2014
  • MSE in Electrical Engineering, Princeton University, 2009
  • B.Tech in Electrical Engineering, IIT Delhi, 2007

Brief Bio

Tushar Krishna is an Associate Professor in the School of Electrical and Computer Engineering at Georgia Tech. He also serves as an Associate Director for the Center for Research into Novel Computing Hierarchies (CRNCH). He held the ON Semiconductor (Endowed) Junior Professorship from 2019-2021. He has a Ph.D. in Electrical Engineering and Computer Science from MIT (2014), a M.S.E in Electrical Engineering from Princeton University (2009), and a B.Tech in Electrical Engineering from the Indian Institute of Technology (IIT) Delhi (2007). Before joining Georgia Tech in 2015, Dr. Krishna spent a year as a researcher at the VSSAD group at Intel, Massachusetts.

Dr. Krishna’s research spans computer architecture, interconnection networks, networks-on-chip (NoC), and deep learning accelerators – with a focus on optimizing data movement in modern computing systems. His research is funded via multiple awards from NSF, DARPA, IARPA, Department of Energy, Intel, Google, Facebook, Qualcomm and TSMC. His papers have been cited over 11,000 times. Three of his papers have been selected for IEEE Micro’s Top Picks from Computer Architecture, one more received an honorable mention, and four have won best paper awards. He was inducted into the HPCA Hall of Fame in 2022. He received the “Class of 1940 Course Survey Teaching Effectiveness” Award from Georgia Tech in 2018 and the “Roger P. Webb Outstanding Junior Faculty Award” from the School of ECE in Georgia Tech in 2021.


Research Interests

  • Computer System Architecture
  • Interconnection Networks and On-Chip Networks
  • Reconfigurable Computing
  • Deep Learning Accelerators
  • ML-assisted System Design
  • Edge/Fog Computing

 Quick Links


Teaching


Professional Service

  • Conference Organization 
  • Technical Program Committee
    • IEEE Micro Top Picks 2023
    • MLSys 2023
    • ASPLOS 2023
    • DATE 2023
      • TPC topic co-chair for “Design Methodologies for Machine Learning Architectures”
    • MICRO 2022
    • SC 2022
    • MLSys 2022
    • IEEE Micro Top Picks 2022
    • HPCA 2022
    • DATE 2022
      • TPC topic co-chair for “Design Methodologies for Machine Learning Architectures”
    • MICRO 2021
    • ISCA 2021
    • ISCAS 2021
    • DATE 2021
      • TPC topic co-chair for “Design Methodologies for Machine Learning Architectures”
    • HPCA 2021
    • MICRO 2020
    • ISCA 2020
    • IEEE Micro Top Picks 2020
    • DATE 2020
    • Hot Interconnects 2019
    • MICRO 2019
    • PACT 2019
    • ISCA 2019
    • DAC 2019
      • TPC track chair for “In-Package and On-Chip Communication and Networks-on-Chip”
    • DATE 2019
    • AISTECS 2019
    • MICRO 2018
    • DAC 2018
    • IPDPS 2018
    • ISPASS 2018
    • DATE 2018
    • DAC 2017
    • DATE 2017
    • MICRO 2016
    • Hot Interconnects 2016
    • DAC 2016
  • Extended Review Committee (ERC)
    • HPCA 2023
    • ASPLOS 2019
    • HPCA 2019
    • MICRO 2017
    • ISCA 2017
    • PACT 2016


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