Mingjie Lin

Mingjie Lin is a Professor in the Department of Electrical Engineering and Computer Science at the University of Central Florida's College of Engineering. He received his Ph.D. in Electrical Engineering from Stanford University in 2008 and has established himself as a leading researcher in bio-inspired computing and robotic control systems.

Dr. Lin's research interests span multiple cutting-edge domains including:

• Bio-Inspired Logic Design with Graph and Field Theory
• Minimum-Energy Bio-Inspired Computing with Emerging Spintronic Devices
• Hardware-Assisted Large-Scale Neuroevolution for Multiagent Learning and Robotic Control
• Computer Architecture/Compiler, and Reconfigurable Computing

His ongoing research is primarily funded by NSF grants focusing on Bio-Inspired Logic Design, Minimum-Energy Bio-Inspired Analogic Computing Devices, and Metaphysical and Probabilistic-Based Computing Transformation. Dr. Lin leads the Autonomous Computing Laboratory at UCF, where his team develops algorithms for improving dynamic adaptability of robotic agents in high non-stationary environments through the fusion of artificial intelligence techniques and classical robotic control algorithms.

Dr. Lin has received numerous prestigious awards for his work:

• UCF Reach for the Star Award (2017)
• UCF CECS Dean's Advisory Award (2017)
• UCF Teaching Incentive Program Award (2016)
• NSF CAREER AWARD (2016)
• SAIC Faculty Fellowship in Electrical Engineering

At the Autonomous Computing Laboratory, Dr. Lin and his team are engaged in creating innovative approaches to robotic control, particularly focusing on Dynamic Amorphous Obstacle Avoidance (DAO-A) where robotic arms can dexterously avoid dynamically generated obstacles that constantly change their trajectories and 3D forms. Their methodology leverages topological manifold learning and deep learning for dimension reduction, enabling conflict-free human-robot interactions even in dynamically constrained environments.