CURRENT
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Chaired Professor
College of Smart Engineering
Youngsan University, Yangsan, South Korea -
Affiliate
Dept. of Electrical and Computer Engineering
Univ. of Maryland -
Professor Emeritus
POSTECH, South Korea
PREVIOUS
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Associate Professor / Full Professor
Dept of Electrical Engineering/ Dept. of Creative IT Engineering
Pohang Univ. of Science & Tech. (POSTECH), Pohang, South Korea -
Assistant Professor 1985.1 – 1988.4
Dept. EE, University of Florida, Gainesville, FL, USA -
Assistant Professor 1981.9 – 1984.12
Dept. EECS, University of Illinois at Chicago, IL, USA
EDUCATION
- B.S. in Electronics Eng., Seoul National University
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M.S. in Robotics, EE Dept
Case Western Reserve University, Cleveland, Ohio USA -
Ph.D. in Pattern Recognition and Associative Memory
Neural Networks, Case Western Reserve University
Key Applications:
- Intelligent Vehicles, Autonomous Driving, ADAS (Advanced Driver Assistance System)
- Robotic Unmanned Aerial Vehicles (UAV) and Drones
- Mobile and Service Robots
- Human Robot Interaction, 3D Facial Modeling and Recognition
Key Enabling Technology:
- Machine Intelligence and Machine Learning
- Neural Networks including Deep Learning Neural Network (DNN)
- Nature-Inspired Optimization
- Swarm Intelligence – Particle Swarm Optimization (PSO)
Evolutionary Optimization – Genetic Algorithm (GA)
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Mobile Robot Navigation
Localization, Mapping, and Simultaneous Localization and Mapping (SLAM)
Some Unique Aspects of Research Achievement
- Graduate study on both the Robot (MS) and the Robot Brain (Neural Network, PhD) – Ideal Combination for Intelligent Robots
- Have done some Pioneering work in the field of Neural networks for Robotics
- Developed a profound expertise in Low-cost SLAM (Simultaneous Localization and Mapping) for Robots utilizing sonar and infrared sensors which is essential for Cleaning robots – helped LG Electronics to develop their successful line of Roboking cleaning robots.
- Have demonstrated for the first time in Korea a 4-vehicle platooning Demo (where 4 vehicles are autonomously/simultaneously driven like one vehicle from commands from a control center) that took place at the World Congress on Intelligent Transportation Systems (1998).
- Proposed a new direction to SLAM which utilizes the learning power of neural networks to model both the robot kinematics/dynamics/sensors and the robot environment – completely bypassing the difficult analytic modeling process.