The Grainger College of Engineering
IBM-Illinois Discovery Accelerator Institute

Deming Chen

Deming Chen
Deming Chen
Abel Bliss Professor of Engineering, Electrical & Computer Engineering (ECE), IIDAI Co-Director

Primary Research Area

  • Hardware systems - Computer aided design

Research Areas

  • Algorithms and computational complexity
  • Computer aided design
  • Computer aided design of integrated circuits
  • Digital integrated circuits
  • Fault tolerance and reliability
  • Hardware verification and testing
  • Integrated circuit reliability
  • Logic design and VLSI
  • Nano-electronics and single electronics

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Biography

Deming Chen is the Abel Bliss Professor in the Grainger College of Engineering at the University of Illinois Urbana-Champaign. His research interests include machine learning and AI, system-level design methodologies, hybrid cloud systems, reconfigurable and heterogeneous computing, and security and confidential computing. He has published more than 300 research papers, received 10 Best Paper Awards, 2 ACM/SIGDA TCFPGA Hall-of-Fame Paper Awards, 5 Best Poster Awards, and delivered more than 170 invited talks, including over 20 keynote and distinguished lectures. His research has generated substantial impact, with several open-source solutions adopted by industry (e.g., FCUDA, DNNBuilder, CSRNet, SkyNet, ScaleHLS, Medusa). He also won various awards, including ACM SIGDA Distinguished Service Award, First Place Winner Award for International Hardware/System Design Contest in 2017 and 2019, NSF SBIR Awards, Google Faculty Award, IBM Faculty Award, Arnold O. Beckman Research Award, and NSF Career Award, etc. Dr. Chen is an ACM Fellow, an IEEE Fellow, an ACM Distinguished Speaker, and previously served as Editor-in-Chief of ACM Transactions on Reconfigurable Technology and Systems (TRETS). Under his leadership, the impact factor of ACM TRETS has increased by 3.8 times. He serves as the Illinois Director of the IBM-Illinois Discovery Accelerator Institute and the Director of the AMD Center of Excellence. He is the founding co-chair of the International Conference on LLM-Aided-Design (ICLAD). Additionally, he has been involved in several startup companies, including AutoESL and Inspirit IoT. He received his Ph.D. in Computer Science from UCLA in 2005.

Education

  • Ph.D. in Computer Science, University of California at Los Angeles, 2005
  • B.S. Computer Science, University of Pittsburgh, Pittsburgh, Pennsylvania, 1995

Journal Editorships

  • Editor-in-Chief, ACM Transactions on Reconfigurable Technology and Systems (TRETS), 2019-2025
  • Guest Editor and main contact, Special Issue of IEEE Design & Test Magazine on Machine Intelligence at the Edge, 2018-2019
  • Lead Guest Editor, Special Issue of Integration, the VLSI Journal on Hardware Acceleration for Machine Learning, 2018-2019

Professional Societies

  • Vice President for Awards, IEEE Council on EDA, 2024-present
  • Member and Cohort FEC Representative, CEDA IEEE Fellow Evaluation Committee (FEC), 2024, 2025
  • Member, ACM SIGDA Outstanding New Faculty Award Committee, 2024
  • Chair, IEEE CEDA Fellow Evaluation Committee, 2023
  • Member, ACM SIGDA Outstanding New Faculty Award Committee, 2022
  • Chair, IEEE CEDA Fellow Evaluation Committee, 2022
  • Founding Chair, IEEE CEDA Central Illinois Chapter, 2016-2023

Service on Department Committees

  • ECE Named Appointments Committee, 2022-2024, 2025-2026
  • Chair, ECE Graduate Committee, 2020-2022
  • CE Area Chair, 2015-2017
  • CSL Policy and Planning Committee, 2008-2010, 2011-2012, 2014-2015, 2021

Service on College Committees

  • Co-Director, IBM-Illinois Discovery Accelerator Institute (IIDAI), 2024 - present
  • Hybrid Cloud Thrust Co-lead, IBM-Illinois Discovery Accelerator Institute, 2021 - 2024
  • Chief Scientist, IBM-Illinois Center for Cognitive Computing Systems Research, 2020 - 2021
  • Steering Committee member, C-NICE center, Grainger College of Engineering, 2019 - present
  • Director, AMD/Xilinx Center of Excellence, 2020 - present
  • Representative of CSL on the College Executive Committee, 2016-2019

Service on Campus Committees

  • Senator, Faculty Senate, 2014-2016, 2018-2020, 2022-2024

Research Interests

  • Hardware security
  • GPU optimization and GPU computing
  • IoT and data analytics
  • Hardware/software co-design for SoC
  • System-level and high-level synthesis
  • Cloud computing
  • AI, machine learning and hardware acceleration
  • Reconfigurable computing and FPGAs

Research Statement

The spectacular CMOS technology scaling has created a large design productivity gap due to inherent design complexities and deep submicron issues. Development cost, including both the design cost and manufacturing cost, of integrated circuits has grown significantly given the increasing size of the design team and the lengthy design cycles. Meanwhile, intensive computational demands arising from emerging workloads, such as those in various IoT and deep-learning related domains, require new architecture and hardware designs, novel automated design flows, and efficient accelerator deployments both at the edge and in the cloud. In this context, the research group led by Prof. Chen mainly pursues the following research directions: system-level and high-level design automation, machine learning and cognitive computing, hybrid cloud, hardware/software co-design, and FPGA and GPU computing. The group recently is also pursuing several other research directions, such as computational genomics and hardware system security.

Undergraduate Research Opportunities

We are looking for committed and mature undergrad researchers for the following topics: FPGA and GPU computing, machine learning and hardware acceleration, high-level and system-level synthesis, and security in IoT and smart grid.

Graduate Research Opportunities

We are recruiting. If you are passionate about research, inspired for innovation and impact, determined to pursue a Ph.D. in Computer Engineering, and your research interests match one or more topics as listed in the "RESEARCH INTERESTS" section below, please contact Prof. Chen directly through email and attach your detailed CV.

Primary Research Area

  • Hardware systems - Computer aided design

Research Areas

  • Algorithms and computational complexity
  • Computer aided design
  • Computer aided design of integrated circuits
  • Digital integrated circuits
  • Fault tolerance and reliability
  • Hardware verification and testing
  • Integrated circuit reliability
  • Logic design and VLSI
  • Nano-electronics and single electronics

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Patents

  • U.S. Patent Application No.: 18/328,716. Filing date: June 2023. Co-inventors: Bharat Sukhwani, Martin Ohmacht, Hubertus Franke, Sameh Asaad, Scott Smith, Deming Chen. Title: Dynamic Assignment of Device Queues to Virtual Functions to Provide to Virtual Machines.
  • U.S. Patent No.: 11,706,163. Issue date: July 2023. Co-inventors: Jian Huang, Deming Chen, Alexander Gerhard Schwing, Youjie Li. Title: Accelerating Distributed Reinforcement Learning with In-switch Computing.
  • Technology license: a company licensed the "Low Loss DNN Quantization Software" out of ADSC/UIUC in 2021. Co-inventors: Yao Chen, Deming Chen, Cong Hao.
  • Technology license: a company licensed the RASP technology out of UCLA, 2017. Co-inventors: Deming Chen, Jason Cong, Eugene Ding, Zhijun Huang, Yeanyow Hwang, Chang Wu, Sarah Xu. Title: RASP: FPGA/CPLD Technology Mapping and Synthesis Package.
  • Technology license: Inspirit IoT, Inc. licensed the VAST HLS technology out of ADSC/UIUC, 2016. Co-inventors: Deming Chen, Hongbin Zheng, Kyle Rupnow, Swathi Gurumani. Title: VAST: High-level Synthesis Tool.
  • Technology license: AutoESL Inc. licensed the xPilot technology out of UCLA, 2006. Co-inventors: Deming Chen, Jason Cong, Yiping Fan, Guoling Han, Wei Jiang, and Zhiru Zhang. Title: xPilot: A Platform-Based Behavioral Synthesis System. This technology eventually led to the acquisition of AutoESL by Xilinx. xPilot became the high-level synthesis engine of Xilinx Vivado HLS (high-level synthesis).
  • Patent No. 3304111. Issue date: Mar 11, 2020. Title: System-Level Validation of Systems-On-A-Chip (SOC). Co-inventors: Keith A. Campbell, Hai Lin, Deming Chen, and Subhasish Mitra.

Honors

  • ACM Distinguished Speaker, 2019 – 2022 and 2026 – 2029
  • Induction of the “DAOmap: A Depth-Optimal Area Optimization Mapping Algorithm for FPGA Designs” paper into the TCFPGA Hall of Fame, 2026
  • Keynote Speaker, International Workshop on Logic and Synthesis, 2026
  • Distinguished Lecture Speaker, Villanova University, 2026
  • Keynote Speaker, IBM Workshop on Algorithms-to-Silicon-to-Systems, 2026
  • Keynote Speaker, NOBE (National Organization for Business and Engineering), 2026
  • Keynote Speaker, High Performance, Edge And Cloud computing (HiPEAC - one of the largest conferences in Europe), Krakow, Poland, 2026
  • ACM Fellow, 2025
  • Fellow, Asia-Pacific Artificial Intelligence Association (AAIA), 2025
  • Member, National Academy of Artificial Intelligence (NAAI), 2025
  • Distinguished Speaker, Institute for Artificial Intelligence and Data Science Distinguished Speaker Series, University of Buffalo, 2025
  • Keynote Speaker, Workshop on Reconfigurable Computing (WRC), 2025
  • Co-Director, IBM-Illinois Discovery Accelerator Institute, 2024 - present
  • Keynote Speaker, 31st Reconfigurable Architectures Workshop (RAW), 2024
  • Vice President for Awards, IEEE Council on EDA, 2024-present
  • Best Poster Award, ASPDAC, 2024
  • Best Poster and First Place Winner Award, DAC Ph.D. Forum, 2023
  • Chair, IEEE CEDA Fellow Evaluation Committee, 2022 & 2023
  • Distinguished Speaker, Distinguished Speaker Series, ECE, Northwestern University, 2022
  • Induction of the "FCUDA: Enabling efficient compilation of CUDA kernels onto FPGAs" paper into the TCFPGA Hall of Fame for FPGAs, 2022
  • Second Place Winner, System Design Contest at IEEE/ACM Design Automation Conference, 2021
  • Best Paper Award, International Conference on Intelligent Data Engineering and Automated Learning, 2021
  • ACM SIGDA Distinguished Service Award, 2021
  • Keynote Speaker, International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), 2021
  • Distinguished Speaker, Distinguished Speaker Series, Universidad Catolica San Pablo, 2021
  • Google Faculty Award, for supporting machine learning courses, diversity and inclusion, 2020.
  • Keynote Speaker, IEEE International Conference on Field-Programmable Technology, 2020
  • Distinguished Speaker, Distinguished Speaker Series, ECE, Rice University, 2020
  • Keynote Speaker, ACM Great Lakes Symposium on VLSI, 2020
  • Distinguished Speaker, Distinguished Speaker Series, ACM Sacramento Chapter, 2020
  • Keynote Speaker, ROAD4NN: Research Open Automatic Design for Neural Networks, 2020
  • Best Paper Award, IEEE International Conference on VLSI Design, 2020
  • Abel Bliss Professor of Engineering, 2020 - present
  • Keynote Speaker, Computing Conference, 2019
  • Editor-in-Chief, ACM Transactions on Reconfigurable Technology and Systems, 2019-2025
  • IEEE Fellow, 2019
  • First Place Winner, both the FPGA and the GPU categories, System Design Contest at IEEE/ACM Design Automation Conference, 2019
  • Best Poster Award, Joint Workshop on On-Device Machine Learning & Compact Deep Neural Network Representations (ODML-CDNNR), 2019
  • Invited Distinguished Speaker, COOL Chips, 2019
  • Best Paper Award, IEEE/ACM Intl Conf on Computer-Aided Design, 2018
  • Keynote Speaker, International Conference on Big Data Analytics & Data Mining, 2018
  • Best Paper Award, IEEE/ACM Intl Workshop on System-Level Interconnect Prediction, 2018
  • Plenary Speech, IEEE Computer Society Annual Symposium on VLSI, 2018
  • First Place Winner, Intl Hardware Design Contest, Design Automation Conf, 2017
  • Keynote paper, Integration, the VLSI Journal, 2017
  • Best Paper Award, IEEE/ACM Intl Conf on Computer-Aided Design, 2015
  • Keynote speech, IEEE International Conference on ASIC, 2015
  • Keynote speech, IEEE International Conference on Anti-counterfeiting, Security, and Identification, 2014
  • IBM Faculty Award, 2014 and 2015
  • Best Paper Award, IEEE Intl Conf on Hardware/Software Codesign and System Synthesis, 2013
  • Best Paper Award, Symp on Application Accelerators in High Performance Computing, 2011
  • Best Paper Award, IEEE Intl Symp on Field-Programmable Custom Computing Machines, 2011
  • ACM SIGDA Outstanding New Faculty Award, 2010
  • Best Paper Award, IEEE Symp on Application Specific Processors, 2009
  • Best Paper Award, IEEE/ACM Asia and South Pacific Design Automation Conf, 2009
  • CAREER Award, National Science Foundation, 2008
  • Arnold O. Beckman Research Award, UIUC, 2007
  • Achievement Award for Excellent Teamwork, Aplus Design Technologies, Inc, 2001

Teaching Honors

  • On the List of Teachers Ranked as Excellent by Students, Spring 2008, Fall 2017

Public Service Honors

  • Founding Chair of IEEE CEDA chapter for Central Illinois (12/1/2016)

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