Portrait of Zheng Dong

Zheng Dong

Associate Professor of Computer Science, Wayne State University

I am an Associate Professor in the Department of Computer Science and an Adjunct Associate Professor at the Institute for AI and Data Science (Division of Research and Innovation) at Wayne State University, where I serve as the Director of the Real-Time Embedded AI SYstems Lab (RT-EASY Lab) and the WSU site co-Director of the NSF IUCRC eCAT Center. I am also privileged to serve as a co-Director of The CAR Lab, collaborating with a team of talented students and utilizing state-of-the-art facilities to advance research in autonomous driving systems.

I hold a Ph.D. in Computer Science from the University of Texas at Dallas, a Master’s degree in Computer Software Engineering from the University of Science and Technology of China, and a Bachelor’s degree in Computer Science from Wuhan University.

Office: Maccabees Building, Suite 14101.2, 5057 Woodward Avenue, Detroit, MI 48202

Phone: +1 (313) 577-1648

Department of Computer Science, Wayne State University

Recent Updates

  1. Grant Excited to share that our MAVERICKS project has been funded by the National Science Foundation (FutureCoRe)—a three-year, $1M collaboration among the University of Delaware (Lead PI: Weisong Shi), Brown University (PI: Peipei Zhou), and Wayne State University (PI: Zheng Dong). We’re grateful for the NSF’s support and excited to build the next generation of mobility-centric autonomous systems through full-stack software/hardware co-design—Go MAVERICKS!
  2. Paper As AI continues to evolve, physical intelligence is becoming a reality. But where do physical intelligence systems live? And how should computer systems research support this new class of intelligence? We believe the answer lies at the edge. We outline how edge computing will serve as the foundation for physical intelligence over the coming decade – enabling real-time perception, decision-making, and actuation in the physical world. Read the full article, a joint work with Profs. Weisong Shi and Peipei Zhou.
  3. Paper Two of our papers on customized DNN accelerator design have been accepted by the Design Automation Conference (DAC) 2026.
  4. Paper Our paper on Human-Robot collaboration has been accepted by IEEE International Conference on Robotics and Automation (ICRA) 2026.
  5. Service The First IEEE Workshop on Physical Intelligence: Systems and Applications (PISA) invites high-quality submissions that explore physical intelligence as an emerging paradigm, where embodied learning, perception, control, and real-world interaction are intrinsically intertwined within intelligent physical systems.
  6. Service I am delighted to be part of the new WSU Grand Challenges Development Grant Program and eager to see the creative ideas from colleagues across the university.
  7. Service I am honored to serve as a Program Co-Chair for IEEE MOST 2026. We welcome your cutting-edge research on mobility and related topics; submissions are due by the end of 2025!
  8. Grant I am thrilled to share that my NSF CAREER proposal “CAREER: ChronosDrive: Ensuring Timing Correctness in DNN-Driven Autonomous Vehicles with Accelerator-Enhanced Real-Time SoC Integration” has been officially selected for funding! A big thank you to the NSF for their generous support!
  9. Special Issue ACM Transactions on Internet of Things (TIOT) Special Issue on Autonomous Driving is now open for submissions! We invite you to submit your best research.
  10. Special Issue ACM Journal on Autonomous Transportation Systems: Special Issue on Mobility is online.
  11. News Wayne State University continues to excel in embedded and real-time systems, maintaining its position in the top 10 nationwide in the latest CS Rankings. As of January 2024, Wayne State University holds the 5th spot in this category.
  12. Paper Our paper on nondeterministic offline reinforcement learning for large-scale online order dispatching has been accepted by AAAI 2024.
  13. Paper Our paper, “Hopscotch: A Hardware-Software Co-design for Efficient Cache Resizing on Multi-core SoCs”, has been accepted by IEEE Transactions on Parallel and Distributed Systems.
  14. Special Issue The next leap in mobile computing could be Vehicle Computing, as advancements in semiconductors and automotive tech continue.
  15. News The kickoff meeting of NSF eCAT IUCRC was successfully completed on 09/15/2023. Go eCAT!!!
  16. Paper Our paper on ROS message synchronization has been accepted to RTSS 2023.
  17. Service Serve as a publicity co-chair at the 30th IEEE Real-Time and Embedded Technology and Applications Symposium, held in Hong Kong, May 13–16, 2024.
  19. Grant NSF IUCRC for eCAT has been funded.
  20. Service Appointed Associate Editor of Multimedia Tools and Applications (Springer).
  21. News The program of WMC 2022 has been published. Welcome to join us on December 5th.
  22. Service Guest Editor (with Dr. Shi) of IEEE Internet Computing: Special Issue on Vehicle Computing.
  23. Paper Our recent work on real-time cause-effect chain scheduling in autonomous machines has been accepted by DATE 2023.
  24. Service Serve on the TPC of DAC 2023, RTCSA 2023, and ICCCN 2023; serve as the publication chair for ACM/IEEE Symposium on Edge Computing 2023.
  25. Paper Our recent work on real-time and accessible shared autonomous mobility services has been accepted by IEEE Transactions on Mobile Computing.
  26. Service Serve on the judging panel of ACM SIGBED Student Research Competition (SRC) 2022.
  27. Paper Our paper, “Towards Hard Real-Time and Energy-Efficient Virtualization for Many-core Embedded Systems”, has been accepted to IEEE Transactions on Computers.
  28. Talk Delivered a talk on real-time VoI detection at the 28th ACM SIGKDD conference on knowledge discovery and data mining (SIGKDD 2022).
  29. Paper Our papers are accepted to RTSS 2022. The 9th International Workshop on Mixed Criticality (WMC) Systems will be held in Houston on Dec. 5th. WMC 2022 website is live!
  30. Service Serve as a TPC member for RTAS 2023.

Research

Our lab pursues foundational real-time embedded AI systems research to enable predictable and safety-critical AI execution for autonomous driving, edge intelligence, and cyber-physical intelligent systems. We study the core systems, architectural, and algorithmic principles needed to run high-throughput yet time-bounded AI workloads on resource-constrained platforms, spanning hardware–software co-design, domain-specific accelerator architectures, and trustworthy runtime mechanisms. By jointly optimizing timing predictability, resource efficiency, and safety assurance, our work aims to build the next generation of embedded AI systems that operate reliably and certifiably in complex, heterogeneous, and mission-critical environments. [Index of my papers]

A short video introducing our vision for Physical Intelligence on the Edge (PIE)

Current projects

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Teaching

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Honors and Awards