Hai Li

Employment

• Duke University Marie Foote Reel E’46 Distinguished Professor
  2024 - Present
• Duke University Clare Boothe Luce Professor
  2017 - 2024
• University of Pittsburgh Associate Professor
  2012 - 2016
• New York University Polytechnic School of Engineering Assistant Professor
  2009 - 2012
• Seagate Technology LLC Senior Staff Engineer
  2007 - 2009
• Intel Corp Senior Design Engineer
  2005 - 2007
• QUALCOMM Inc Senior Design Engineer
  2004 - 2005

Education

• Purdue University Ph.D.
  2000 - 2004
• Tsinghua University M.S.
  1998 - 2000
• Tsinghua University Electronic Engineering
  1994 - 1998

Projects & Funding

Projects & funding information is unavailable.

Publications (471)

• Generative AI at the Edge: A Comprehensive Survey of Architectures, Hardware and Applications
  ACM Computing Surveys 2026 DOI: 10.1145/3829079
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• AutoEDA: Enabling EDA Flow Automation through Microservice-Based LLM Agents
  ACM Transactions on Design Automation of Electronic Systems 2026 DOI: 10.1145/3842675
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• Device-Algorithm Co-Design with FeFETs for On-device Continual Learning
  2026 DOI: 10.1145/3787109.3815275
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• Frame Skipping Architecture for Video-Language Model Acceleration
  2026 DOI: 10.1145/3787109.3816385
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• Skilled AI Agents for Embedded and IoT Systems Development
  2026 DOI: 10.1145/3786335.3813205
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• CAMformer: Binary Associative Memory Is All You Need
  IEEE Transactions on Circuits and Systems I: Regular Papers 2026 DOI: 10.1109/TCSI.2026.3692014
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• Circuits to Systems: Codesigning Efficient AI Hardware
  IEEE Design & Test 2025 DOI: 10.1109/MDAT.2025.3600328
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• Recap of the 62nd ACM/IEEE Design Automation Conference (DAC62): The “Chips to Systems Conference”
  IEEE Design & Test 2025 DOI: 10.1109/MDAT.2025.3605046
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• MulPi: A Multi-class and Patient-Independent Epileptic Seizure Classifier With Co-Designed Input-stationary Computing-in-SRAM
  IEEE Transactions on Biomedical Circuits and Systems 2025 DOI: 10.1109/TBCAS.2025.3579273
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• AutoRAC: Automated Processing-in-Memory Accelerator Design for Recommender Systems
  2025 DOI: 10.1145/3716368.3735229
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