CV

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JIAQI GU

Assistant Professor, School of Electrical, Computer and Energy Engineering

Arizona State University, Tempe, AZ 85287

Education

• Ph.D. in University of Texas at Austin (GPA: 4.00/4.00), Austin, TX, USA, 2023
• B.E. in Fudan University (Elite Engineering Program, GPA: 3.91/4.00, Rank: 2/71), Shanghai, China, 2018

Work experience

• NVIDIA Research (Jun 2022 - Oct 2022)
  • Internship
  • ASIC/VLSI Team, Austin, TX
• Meta Reality Labs (May 2021 - Dec 2021)
  • Internship
  • FAST AI Team, Menlo Park, CA
• The University of Texas at Austin (Aug 2018 - Present)
  • ECE Department, University of Texas at Austin, Austin, TX
  • Advisors: David Z. Pan; Co-advisor: Ray T. Chen

Skills

• Programming languages
  • Python
  • PyTorch \& Tensorflow
  • C/C++
  • CUDA
  • Verilog \& Chisel

Awards and Honors

• UT Austin Graduate School Outstanding Dissertation Award, April 2024
• Third Place, 60th IEEE/ACM Design Automation Conference (DAC) Ph.D. Forum, Jul 2023
• MLSys Student Travel Award, May 2023
• Margarida Jacome Dissertation Prize, Apr 2023
• Winner at Robert S. Hilbert Memorial Optical Design Competition, Jul 2022
• Best Paper Award, IEEE Transaction on Computer-Aided Design of Integrated Circuits and Systems (TCAD), Oct 2021
• Young Student Fellow, 58th IEEE/ACM Design Automation Conference (DAC), Oct 2021
• Cockrell School Graduate Student Fellowship, University of Texas at Austin, Jun 2021
• First Place, ACM Student Research Competition Grand Finals, May 2021
• Best Poster Award, NSF Workshop on Machine Learning Hardware, Dec 2020
• 1st Place, ACM/SIGDA Student Research Competition, Nov 2020
• 7th Place, IWLS Programming Contest: Machine Learning + Logic Synthesis, Aug 2020
• Young Student Fellow, 57th IEEE/ACM Design Automation Conference (DAC)
• Best Paper Award, 25th ACM/IEEE Asian and South Pacific Design Automation Conference (ASP-DAC)
• 4th Place, 2019 DAC System Design Contest on Low Power Object Detection
• First Prize Scholarship, Fudan University
• Top 11%, 2017 IEEEXtreme Global Programming Competition (out of 3,350 teams worldwide)
• 2nd & 3rd Prize, National Mathematical Contest in Modeling

Related Courses

• EE382N-1: Computer Architecture
  • Dr. Dam Sunwoo
• EE382N-14 High-Speed Computer Arithmetic I:
  • Dr. Earl Swartzlander
• EE382N-20: Computer Architecture: Parallism/Locality
  • Dr. Mattan Erez
• CS395T: Parallel Algorithm Scientific Computing
  • Dr. George Biros
• CS394R: Reinforcement Learning: Theory and Practice
  • Dr. Peter Stone and Dr. Scott Niekum
• EE382M: VLSI I
  • Dr. Jacob A. Abraham
• EE382M: VLSI Physical Design Automation
  • Dr. David Z. Pan
• EE382V: Cross-layer Machine Learning Algorithm/Hardware Co-design
  • Dr. Mattan Erez and Dr. Michael Orshansky
• EE382M-26: VLSI CAD and Optimization
  • Dr. David Z. Pan
• EE381V: Combinatorial Optimization
  • Dr. Constantine Caramanis
• EE381V: Advanced Topics in Computer Vision (in progress)
  • Dr. Zhangyang (Atlas) Wang