Dr. Zhao (Joy) Sun

Associate Professor in the Electrical and Computer Engineering

Location: Olin 318G

Phone: (757) 637 – 2338

Email: zhao.sun@hamptonu.edu

Expertise: Data-driven Modeling and Learning based Control; Computational Intelligence; Autonomous System; Sensor Network Optimization; Quantum Computing and Communication; Human Machine Teaming; Quantum-enhanced Machine Learning

Education: Ph.D. Electrical and Computer Engineering, North Carolina A&T State University, 2006




Dr. Zhao (Joy) Sun is an associate professor in the Electrical and Computer Engineering Department at Hampton University. Before joining Hampton University, she was a research scientist at the National Institute of Aerospace working on intelligent methods and adaptive fault tolerant control strategies. She also has worked as a Summer Visiting Faculty at National Lawrence Berkeley Laboratory on Quantum Computing and Quantum Control and at Stanford University on Safe/Tactical Autonomy. She received a Ph. D. degree in Electrical Engineering in 2006 from North Carolina A&T State University. Her current research includes serving as PI for NSF EIR grant “ Integrated Sensor-Robot Networks for Real-time Environmental Monitoring and Marine Ecosystem Restoration in the Hampton River” and IBM-HBCU Quantum Center project “Machine Learning Methodology for Robust Control Design of Quantum Systems”; serving as Co-PI for the NASA ULI project “Safe Aviation Autonomy with Learning-enabled Components in the Loop: from Formal Assurances to Trusted Recovery Methods”, which is led by Stanford University. She is also serving as a Subject Matter Expert for NSF project “Convergent Undergraduate Education in Quantum Science, Technology, Engineering, Arts and Mathematics (QuSTEAM)”, which is led by the Ohio State University.  Dr. Sun is a senior member of IEEE and AIAA, and a member of ASEE.

Selected Publications:  

Journal Papers

  1. S. Li, S. Chen, Y. Z. Cao and Z. Sun,A Neural Network Approach to Sampling Based Learning Control for Quantum System with Uncertainty,Commun. Comput. Phys. doi: 10.4208/cicp.OA-2020-0182
  2. Sun, Xi. Chen, and Z. H. He, “Adaptive Critic Design for Energy Minimization of Portable Video Communication Devices,” IEEE Transactions on Circuits and System for Video Technology, 2010, Vol. 20, Issue 1, pp. 27-37.
  3. Sun, W. C. Cai, L. G. Weng, and Y. D. Song, “Nonlinear Pitch Control of Wind Turbines,” International Journal of Factory Automation, Robotics and Soft Computing, Issue 4, ISSN 1828-6984, pp. 57-62.
  4. H. Liao, Z. Sun, Y. D. Song, B. Li, and X. Y. Mei, “Variable Speed Control of Wind Turbines via Memory-based Firing Angle Sequences Adjustment,” Journal of Solar Energy, Volume 130, Issue 3, pp. 166-173.
  5. Sun, X. H. Liao, F. Stewart, B. Li, and Y. D. Song, “Neuro-Robust Reentry Path Control of Reusable Launch Vehicles,” International Journal of Computational Intelligence Research. Vol. 2, No. 1, pp.76-80.

 Book Chapters

  1. Sun, W. C. Cai, L. G. Weng, and Y. D. Song, “Nonlinear Pitch Control of Wind Turbines,” Recent Advances in Control Systems, Robotics and Automation, Third Edition, Volume 1, pp.104-109.
  2. Sun, R. Zhang, T. Dong, X. H. Liao and Y. D. Song “Fuzzy Logic Approach to Path Tracking and Obstacles Avoidance of UAVs,” Advanced Fuzzy Logic Technologies in Industrial Applications, published by Springer, Chapter 15, pp. 212-223.
  3. Li, Z. Sun, R. Zhang, B. Li, L. G. Weng and Y. D. Song, “Close Formation Flight Control of Multi-UAVs via Fuzzy Logic Technique,” Advanced Fuzzy Logic Technologies in Industrial Applications, published by Springer, Chapter 21, pp. 298-308.

Conference Papers/Presentations

  1. Zhang, S. Q. Wu, Z. H. He; Z. Sun, “Critical Sampling for Data-Driven Modeling of Unknown Dynamical Systems,” 2023 CoRL conference, OOD workshop, Atlanta, USA.
  2. Sun, L. C. Peralta, M. A. Ragins, N. R. Chaney “Development of a Research-based Course On Machine Learning and Robotics for Undergraduate Engineering Students,” 2023 ASEE Annual Conference, Baltimore, MD.
  3. Sun, “An Improved QPSO based Algorithm for USV Path Planning”, NUMTA2023 Conference, Calabria Italy, 2023.
  4. Sun, “A Review on Quantum-like Approach to Human Cognition and Decision Making,” NUMTA2023 Conference, Calabria Italy, 2023.
  5. Nare, Q. Le, N. Halyo, Z. Hayes, and Z. Sun, “Assessing Potential Impacts an Experimental Centric Approach Can Have in an Introduction to Digital Electronics Course,” ASEE-SE Conference, Chicago, IL ,2016.
  6. Sun, “Vision-assisted Adaptive Target Tracking of Unmanned Ground Vehicles,” 33rd Chinese Control conference, Nanjing, China, 2014.
  7. Sun, and Suresh M. Joshi, “An Indirect Adaptive Control Scheme in the Presence of Actuator and Sensor Failures,” 2009 AIAA GNC Conference, Chicago, IL.
  8. Sun, W. C. Cai, X. H. Liao and Y. D. Song, “Virtual Leader Based Robust Adaptive Formation Control of Multi-Unmanned Ground Vehicles (UGVs),” American Control Conference, New York city, 2007.
  9. Sun, W. C. Cai, X. H. Liao and Y. D. Song, “Neuro-Adaptive Formation Control of Mobile Vehicles: Virtual Leader Based Path Planning and Tracking,” International Symposium on Neural Networks, Nanjing, China, 2007.