Christopher Bejger
Education
- Ph.D., Chemistry, The University of Texas at Austin, 2012
- B.S., Chemistry, University of Oregon, 2006
Research Interests
- Redox flow batteries
- Redox active metal organic frameworks
- Transition metal chalcogenide clusters
Ran Zhang
Education
- Ph.D., University of Waterloo, Ontario, Canada, 2016
- B. Eng., Tsinghua University, Beijing, China, 2010
Research
- Wireless communications and networking
- Unmanned Aerial Vehicle (UAV) communication networks
- Artificial Intelligence and Machine Learning
- 5G and Beyond 5G communications
- Radio resource management
Selected Publications
- L. Wang, S. Tripathi, R. Zhang, N. Cheng, and M. Wang, “Optimal Charging Profile Design for Solar-Powered Sustainable UAV Communication Networks,” IEEE ICC 2023, Rome, Italy, May 28 – June 21, 2023
- R. Zhang, D. M. Nguyen, Miao Wang, Lin X. Cai and X. Shen,”Responsive Regulation of Dynamic UAV Communication Networks Based on Deep Reinforcement Learning,” Broadband Communications, Computing and Control for Ubiquitous Intelligence, Wireless Network Book Series, Springer, pp. 35-63, 2022
- L. Liu, B. Lin, R. Zhang, Y. Che, and C. Zhang, “Joint Beamforming and Deployment Optimization for UAV-Assisted Maritime Monitoring Networks”, International Conference on Wireless Algorithms, Systems, and Applications (WASA), 2022 (Best Paper Award).
- Z. Chen, R. Zhang, L. X. Cai, Y. Chen, and Y. Liu, “A Deep Reinforcement Learning based Approach for NOMA-based Random Access Network with Truncated Channel Inversion Power Control“, IEEE ICC 2022, Seoul, Korea, May 16-20, 2022
- R. Zhang, M. Wang, L. X. Cai, and X. Shen, “Learning to be Proactive: Self-Regulation of UAV Based Networks with UAV and User Dynamics“, IEEE Transactions on Wireless Communications,vol. 20, no. 7, pp. 4406-4419, 2021
- Z, Chen, R. Zhang, Y. Liu, L. X. Cai, and Q. Chen, “Performance Study of Cybertwin-assisted Random Access NOMA,” IEEE Internet of Things Journal, vol. 8, no. 22, pp. 16279-16289, 2021
- R. Zhang, M. Wang, and L. X. Cai, “SREC: Proactive Self-REmedy of Energy-Constrained UAV-Based Networks via Deep Reinforcement Learning,” IEEE GlobeCom2020, Taipei, Taiwan, Dec. 7-11, 2020
Artur Wolek
Education
- Postdoctoral Fellow, University of Maryland, 2018-2020
- Postdoctoral Fellow, U.S. Naval Research Laboratory, 2015-2018
- Ph.D., Virginia Tech, Aerospace Engineering, 2015
- B.S., Virginia Tech, Aerospace Engineering, 2010
Research Interests
- Optimal motion planning
- Vehicle dynamics, estimation, and control
- Multi-robot coordination and cooperative sensing
- Marine robotics and unmanned aircraft
Tao Hong
Education
- Ph.D., (co-majors) Electrical Engineering and Operations Research, North Carolina State University, 2010
- M.S., (co-majors) Operations Research and Industrial Engineering, North Carolina State University, 2008
- M.S., Electrical Engineering, North Carolina State University, 2008
- B.Eng., Automation, Tsinghua University, 2005
Research
- Energy forecasting
- Power systems operations and planning
- Renewable integration
- Risk management
- Energy trading
- Retail forecasting
- Revenue optimization
- Forecasting in healthcare, transportation, and sports
Shen-En Chen
Education
- Ph.D., West Virginia University, 1996
- M.S.C.E., West Virginia University, 1992
- B.S.C.E., West Virginia University, 1989
Research
- Power transmission structures
- Carbon storage in geological formations
- Remote sensing for bridge monitoring
- Forensic investigation
Youxing Chen
Education
- Ph.D., Materials Science and Engineering, Texas A&M University, 2015
- M.S., Materials Science and Engineering, Shanghai Jiaotong University, China, 2010
- B.S., Materials Science and Engineering, Chongqing University, China, 2006
Research
Dr. Chen’s research focuses on the materials’ response under extreme environments, such as radiation, load, strain rate and temperature. His group is interested in exploring the fundamental relationship between materials structure and property across multiple length scales: from atomic to macroscopic scale.
James Conrad
Education
- Ph.D., North Carolina State University, 1992
- M.S., North Carolina State University, 1987
- B.S.C.S., University of Illinois, Urbana/Champaign, 1984
Research
- Computer Engineering
- Embedded Systems
- Robotics
Amir Ghasemi
Education
Ph.D., Mechanical Engineering, University of Kentucky, 2012
M.S., Mechanical Engineering , Amirkabir University of Technology, 2008
B.S., Mechanical Engineering, Ferdowsi University of Mashhad, 2005
Research
- Control Theory and Applications
- Autonomous Vehicles
- Robotics
- Human-Machine Interaction
- Haptics
- Human Model Control
- Cube Satellites
- Intelligent Structures
Lin Ma
Education
- Postdoc, US Army Research Laboratory/University of Maryland, 2019-2022
- Ph.D., Dalhousie University, Canada, 2019
- M.S., Dalhousie University, Canada, 2014
- B.S., Xiamen University, China, 2012
Research
- Materials science
- Electrochemical engineering
- Rechargeable battery technology
Dipankar Maity
Education
- Ph.D., University of Maryland-College Park, 2018
- B.E., Jadavpur University, India, 2013
Research
General area:
- Control & System Theory
- Robotics
Recent Focus:
- Communication constrained control
- Motion planning for autonomous robots
- Information theoretic control and decision making
- Game theory