Jeff Zhang
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ISTB4 467 Arizona State University Tempe, AZ 85287
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Mail code: 5706Campus: Tempe
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Jeff (Jun) Zhang is an assistant professor in the School of Electrical, Computer and Energy Engineering at ASU. He obtained his Ph.D. from New York University. From 2020-2022, Zhang was a postdoctoral fellow at Harvard University. Zhang’s general research interests are in deep learning, computer architecture, embedded systems, and EDA, with particular emphasis on energy-efficient and fault-tolerant design for AI/ML systems and hardware accelerators. His work received IEEE Top Picks in Test and Reliability in 2023, IEEE Micro 2022 Best Paper Award, best paper award nominations at DATE 2022 and VTS 2018, and best presentation award nomination at DATE Ph.D. Forum 2020. Jeff serves on the technical program committee of several top conferences in the area of computer engineering and computer hardware, and has served as a reviewer for several IEEE and ACM journals.
Awards and Honors
- IEEE Top Picks in Test and Reliability, IEEE ITC, 2023
- Best Paper Award, IEEE Micro, 2022
- Best Paper Award Candidate, IEEE DATE, 2022
- Best Presentation Award Nomination, ACM SIGDA DATE PhD Forum, 2020
- Best Paper Award Nomination, IEEE VLSI Test Symposium, 2018
- Ernst Weber Ph.D. Fellowship, New York University, 2015, 2016
Experience
Arizona State University, Tempe AZ
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Assistant Professor Jan. 2023 to now
Harvard University, Cambridge MA
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Research Associate Jan. 2023 to Dec. 2023
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Postdoctoral Fellow Aug. 2020 to Dec. 2022
- Teaching Fellow
- - Topics in Mixed Signal Integrated Circuits. (Fall'22, Spring'21)
- - Design of VLSI Circuits and Systems. (Spring'22)
New York University, New York NY
- Research Assistant Sep. 2015 to Aug. 2020
- Teaching Assistant
- - Computer Architecture. (Fall'17, Fall'16)
- - Introduction to VLSI. (Spring'17)
Microsoft Research, Redmond WA
- Research Intern Aug. 2018 to Nov. 2018
Samsung Semiconductor Inc., San Jose CA
- Research Intern May 2018 to Aug. 2018
Ph.D., New York University
M.Eng., B.Eng., Hunan University
News:
-Join us: We’re always looking for curious and enthusiastic researchers (graduate students, postdocs, or undergraduate students) to join the team. If you’re interested in joining, e-mail us with your resume, a transcript, and why you’d like to join our group.
04/2024: Serving as a session chair for "Session II: Performance modeling & analysis" at ISPASS'24.
04/2024: Our student Charan will join the Qualcomm CAD team for a summer internship!
03/2024: Serving as a TPC member for CASES'24.
03/2024: Serving on the program committee for ML and Systems Rising Stars 2024.
03/2024: Organizing a special session on "Gen AI for Chip Design" at IEEE VTS'24.
03/2024: Serving as the Recruitment Chair and Ph.D. forum co-chair for ESWEEK'24.
02/2024: Serving as a TPC member for LAD'24, the first International Workshop on LLM-Aided Design! Please submit your LLM-based design works!
02/2024: Our paper "zeroTT: A Two-Step State Transition Avoidance Scheme for MLC STT-RAM" has been accepted at DAC'24.
02/2024: Serving as a TPC member for DAC 2024 Ph.D. Forum.
02/2024: Our invited paper "Fused Functional Units for Area-Efficient CGRAs" will appear at ISQED'24. Congrats Ron!
01/2024: Organizing a special session on "Algorithms, Architectures, and Circuits for Efficient AI/ML Computing" at ISQED'24.
01/2024: Our paper "Intelligent Networking for Energy Harvesting Powered IoT Systems" has been accepted by ACM Transactions on Sensor Networks.
01/2024: Serving as a Guest Editor for IEEE Journal on Exploratory Solid-State Computational Devices and Circuits (JXCDC) on "3D Logic and Memory for Energy Efficient Computing." Please submit your papers!
01/2024: Our invited paper "Exploiting 2.5D/3D Heterogeneous Integration for AI Computing" will appear at ASP-DAC'24.
12/2023: Our Paper "A 12nm Linux-SMP-Capable RISC-V SoC with 14 accelerator types, distributed hardware power management and flexible NoC-based data orchestration" has been accepted at the ISSCC 2024!
12/2023: Our work on SODA toolchain has been awarded 2022 Best Paper Award from IEEE Micro by the IEEE Computer Society Publications Board!!
11/2023: Serving as a Guest Editor for the Journal of Parallel and Distributed Computing, special issue on "Parallel and Distributed Computing Technique for Multi-modal Artificial Intelligence." Please submit your papers!
10/2023: Our VTS'18 paper "Analyzing and Mitigating the Impact of Permanent Faults on DNN Accelerators" was chosen as the 2023 IEEE Top Picks in Test and Reliability!
10/2023: Serving as a TPC member for DAC'24.
10/2023: Serving as a session chair for "Fast and Trustworthy Embedded Systems" at ICCAD'23.
09/2023: Our special session proposal on "Chiplet based System Design" is accepted at ASP-DAC'24.
09/2023: Serving as the track co-chair on "System-level Design and Methodologies (SDM)" for ISQED'24.
09/2023: We're organizing ACM SIGDA 2nd Job Fair at ICCAD'23; Please submit your CV!
09/2023: Serving as a PC for ISPASS'24.
08/2023: We are organizing ACM CADathlon (“Olympic games of EDA”) again at ICCAD'23;
07/2023: Our paper "VecPAC: A Vectorizable and Precision-Aware CGRA" has been accepted at the ICCAD'23!
06/2023: Serving as a TPC member for ICCD'23.
05/2023: Our paper "COFFEE: Cross-Layer Optimization for Fast and Efficient Executions of Sinkhorn-Knopp Algorithm on HPC Systems" has been published at IEEE Transactions on Parallel and Distributed Systems.
04/2023: We are organizing ACM SIGDA/IEEE CEDA Early Career Workshop at DAC 2023!
03/2023: Serving on the program committee of "Machine Learning and Systems Rising Stars 2023".
03/2023: Serving as the Recruitment Chair and Ph.D. forum co-chair for ESWEEK'23.
02/2023: Serving as a TPC member for ISLVSI'23.
01/2023: Joined ASU as an assistant professor of ECEE!
01/2023: Our paper "Path Planning Under Uncertainty to Localize mmWave Sources" has been accepted at the ICRA 2023!
10/2022: Serving as a TPC member for DAC'23.
10/2022: Our paper "A 12nm 18.1TFLOPs/W Sparse Transformer Processor with Entropy-Based Early Exit, Mixed-Precision Predication, and Fine-Grained Power Management" has been accepted at the ISSCC 2023!
09/2022: Serving as a session chair for "Performance, Power and Temperature Aspects in Deep Learning" at ICCAD'22. Join us at San Diego!
09/2022: Our paper "End-to-end Synthesis of Dynamically Scheduled Machine Learning Accelerators” has been accepted at IEEE Transactions on Computers.
08/2022: Our invited paper "A Scalable Methodology for Agile Chip Development with Open-Source Hardware Components" will appear at ICCAD'22.
07/2022: Presented an invited talk at DACPS 2022.
06/2022: Our paper "Bridging Python to Silicon: The SODA Toolchain" has been accepted at IEEE Micro 2022!
06/2022: Our paper "A 12nm Agile-Designed SoC for Swarm-Based Perception with Heterogeneous IP Blocks, a Reconfigurable Memory Hierarchy, and an 800MHz Multi-Plane NoC" has been accepted at ESSDERC/ESSCIRC 2022!
05/2022: Serving as an Artifact Evaluation co-chair for HPCA'23. Please submit your best work!
05/2022: We're organizing ACM SIGDA 1st Job Fair at ICCAD'22; Please submit your CV!
04/2022: Serving as a session chair for "Accelerating the Inference: Transformers, Graphs and Others" at DAC'22. Find me in San Francisco!
04/2022: We're organizing ACM CADathlon (“Olympic games of EDA”) at ICCAD'22; Please join the competition!
04/2022: Our paper "ASAP: Automatic Synthesis of Area-efficient and Precision-aware CGRA" (Collaborated with PNNL) has been accepted at ICS'22!
04/2022: Serving as a TPC member for ICCD'22.
03/2022: Two papers got accepted at DATE'22; one of them is nominated for Best Paper Award!
02/2022: We're organizing the NOPE workshop at ASPLOS 2022. Please consider submitting your NOPE papers!
02/2022: Our paper on "Millimeter Wave Wireless-assisted Robobic Navigation" has been accepted at IEEE Open Journal of the Communications Society!
12/2021: Serving as an External Reviewer for MLSys'22.
10/2021: We successfully taped out our second 12nm Domain-specific SoC for autonomous driving (in collaboration with IBM, Columbia, and UIUC)!
10/2021: Serving as a TPC member for the AI/ML Design: Circuits and Architecture track of DAC'22.
09/2021: Our RecPipe work passed the MICRO 2021 Artifact Evaluation process and received all 3 badges (Artifact Available, Functional, Reproduced)!! Please try them here!
07/2021: Presented our work "Towards automatic and agile ML/AI accelerator design with end-to-end synthesis" (Collaborated with PNNL) at ASAP'21! [Paper] [Slides]
07/2021: Our paper "RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance" has been accepted at MICRO'21!
07/2021: Serving as a TPC member on Test, security, and verficiation track of ICCD'21.
06/2021: Serving as a TPC member for IISWC'21.
11/2020: Presented two posters at NSF Workshop on Machine Learning Hardware. [Poster1][Poster 2]
10/2020: Serving as a TPC member for the AI/ML system design track of DAC'21.
10/2020: Serving as a TPC member for the architecture track of IPDPS'21.
08/2020: Two U.S. Patents on data compression for AI Hardware are published with Microsoft Research and HoloLens Team.
08/2020: Selected as a member of the Artifact Evaluation Committee for USENIX OSDI'20.
08/2020: Became an alumnus of NYU EuSuRe research group and joined the Harvard Architecture, Circuits, and Compilers Group as a Postdoctoral Fellow!
07/2020: Presented thesis work at ACM SIGDA 2020 57th Design Automation Conference (DAC) Ph.D. Forum.
07/2020: Successfully defended my Ph.D. thesis: Towards Energy Efficient and Reliable Deep Learning Inference. Thesis committee members: Prof. Siddharth Garg, Prof. Ramesh Karri, Prof. Tushar Krishna, Prof. Sundeep Rangan, and Prof. Brandon Reagen. [Slides][Video]
07/2020: Presented our "Model-Switching: Dealing with Fluctuating Workloads in MLaaS Systems" work (collaborated with Microsoft Research and Microsoft Advertising) at USENIX HotCloud'20! [Paper][Slides][Video]
06/2020: Contributed proposal on “Resource Constrained Mobile Data Analytics Assisted by the Wireless Edge” got funded by NSF and Intel!
03/2020: Participated in the semifinals for TTTC’s E. J. McCluskey Best Doctoral Thesis 2020 at IEEE VLSI Test Symposium.
03/2020: Attended and got nominated for Best Presentation Award at ACM SIGDA 2020 DATE Ph.D. Forum.
