[2004 - Till date]
Currently working for the Electronics and Telecommunications Research Institute, Daejeon, South Korea.
[2005 - till date]
Professor at the Department of Artificial Intelligence, University of Science and Technology (UST), Daejeon, South Korea.
[1993 - 2001]
BS, MS and PhD in Computer Sciences from Yonsei University, Seoul, South Korea.
My research interests include computer vision, anomaly detection, open-set learning, out of data detection, domain adaptation, learning with limited data, deep learning, and reinforcement learning.
Positions
2004 – Professor of University of Science and Technology (UST) of Korea, Giving lectures on deep present learning and reinforcement learning every semester to UST students.
2004 – Principal Researcher, Artificial Intelligence Laboratory of Electronics and Communications present Research Institute (ETRI), Mainly focusing deep learning and reinforcement learning as well as related national projects.
2020 – AI Academy Professor of Electronics and Communications Research Institute (ETRI), Actively present giving lectures for ETRI members on Deep Learning and Reinforcement Learning.
2005 – Leader of Computer Vision and Machine Learning Lab (CVML) of University and Science present Technology (UST), We are actively doing researches on deep learning and reinforcement learning. Recent focus has been anomaly detection, weakly supervised learning, self supervised learning as well as computer vision in general. See My web page for details.
Education
1997 – 2002 : PhD, Computer Science, Yonsei University, Seoul, Korea.
Evolutionary computation, Genetic algorithms, Emergence, Evolvability, Neural networks, Machine learning
1995 – 1997 : Master of Engineering, Computer Science, Yonsei University, Seoul, Korea.
Evolutionary computation, Genetic algorithms, Neural networks, Machine learning
1989 – 1995 : Bachelor of Science, Computer Science, Yonsei University, Seoul, Korea.
Awards
2024.04.05 Excellent Professor Award at Electronics and Telecommunications Research Institute (ETRI) for his excellency and contribution to ETRI AI Academy
2022 Best Paper Award in 2022 KICS Winter Conference.
2021 Best Poster Presentation Award in The 27th International Workshop on Frontiers of Computer Vision.
2021 Excellent Professor Award from University of Science and Technology, Korea.
2018 Best Presentation Award in Korea Computer Congress 2018 (KCC2018).
2016 Excellent Lecture Award from University of Science and Technology on "Artificial Neural Networks and Deep Learning" Lecture.
Academic Achievements & Recognitions
2023 Published a paper titled "Clustering Aided Weakly Supervised Training to Detect Anomalous Events in Surveillance Video
" in EEE Transactions on Neural Networks and Learning Systems (Accepted)
2022 Published a paper titled "Stabilizing Adversarially Learned One-Class Novelty Detection Using Pseudo Anomalies" in EEE Transactions on Image Processing, vol. 31, doi: 10.1109/TIP.2022.3204217
2022 Published a paper titled "Generative cooperative learning for unsupervised video anomaly detection" in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2022), Louisiana, USA.
2021 Published a paper titled "Learning Not to Reconstruct Anomalies" in British Machine Vision Conference 2022(BMVC 2022), Virtual.
2020 Published a paper titled "Old is Gold: Redefining the Adversarially Learned One-Class Classifier Training Paradigm" in IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2020), Online.
2020 Translated the book titled "Deep Reinforcement Learning Hands-On" into Korean. ISBN: 979-11-5600-740-1.
2006.04 – Work Group Co-Chair of Object Management Group (OMG) Standardization Work Group, 2007.09 Leading Hardware Abstraction Layer WG (Robotics).
Lectures & Tutorials
2022.09-12 Invited talk at 3rd Korea Artificial Intelligence conference, Video Anomaly Detection with Pseudo Data Augmentation. see https://koreaai.org/
2022.09-12 Lectures on Advanced Deep Learning at University of Science and Technology
2020.07-current Lectures on Advanced Deep Learning at ETRI AI Academy. Twice a year
2020.08 Lectures on Advanced Deep Learning at Hallym University Medical Center
2015-present Lectures on Deep Learning at University of Science and Technology of KOREA
2015-present Lectures on Reinforcement Learning at University of Science and Technology of KOREA
2021.04: Lectures on Advanced Deep Learning at AI Academy of ETRI for two months
2020.12: Lectures titled as Deep Learning Trivia (딥러닝 잡학사전) at KSC 2020(정보과학회) conference
2020.12: Lectures on Deep Reinforcement Learning at ChungBuk University
2020.08: Lectures on Advanced Deep Learning at AI Academy of ETRI for two months
2018.10: Tutorial on Deep Reinforcement Learning, at Kyungil University, KOREA
2018.06: Tutorial on Deep Reinforcement Learning, at The Institute of Electronics and Information Engineers, KOREA
2021.04: Tutorial on Deep Learning, at International Intellectual Property Training Institute, KOREA
2017.11: Lectures on Advanced Deep Learning at AI Academy of ETRI for two months
2017.07: Tutorial on Deep Reinforcement Learning, ETRI Intelligent Robotics Division Techday, KOREA
2017.11: Tutorial on Deep Learning, at a conference organized by The Society for Computational Design and Engineering (CDE), KOREA
2017.11: Tutorial on Deep Reinforcement Learning, at a conference organized by The Institute of Positioning, Navigation, and Timing, KOREA
2017.04: Tutorial on Deep Learning at DRB Fatec, KOREA
Projects Experience (Ongoings Only)
Electronics and Telecommunications Research Institute, http://www.etri.re.kr
2023 – present Guide Dog: Development of Navigation AI Technology of a Guidance Robot for the Visually Impaired Person. Developing technology that allow the robot to recognize the structure of the road on its own without a map and move according to the instructions of the user (the visually impaired).
2020 – 2022 Development of AI Technology for Guidance of a Mobile Robot to its Goal with Uncertain Maps in Indoor/Outdoor Environments. Developing a deep learning based road junction classification, Setting & Collecting data set for junction classification both in outdoors and indoors.
2019 – present Development of multimodal sensor-based intelligent systems for outdoor surveillance robots. Detecting anomalies in images or videos obtained from surveillance robots by using deep generative models such as Autoencoders.