Hyeonwoo Yu

Hyeonwoo Yu (유현우)

Assistant Professor

Department of Electrical Engineering & AI Graduate School (Affiliated)
Ulsan National Institute of Science and Technology (UNIST), South Korea

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About Hyeonwoo Yu

Hyeonwoo Yu is an assistant professor of the Department of Electrical Engineering and Graduate School of AI at Ulsan National Institute of Science and Technology (UNIST), South Korea from Feb. 2022.

He received Ph.D and B.S from Electrical and Computer Engineering at Seoul National University, Korea in Feb. 2021 and Feb. 2014, respectively (advisor: Prof. Beomhee Lee). Before joining UNIST, he was a postdoctoral research fellow at Robotics Institute, Carnegie Mellon University from Mar. 2020 to Dec. 2021 (PI: Prof. Jean Oh).

His research focuses on how to bridge the gap between the artificial intelligence (AI) and the robotics. By exploiting robot perception and navigation, he contributes to make AI and robotics mutually beneficial. The ultimate goal is to develop adaptive robots that can automatically explore unknown environments and learn for their own purposes. To achieve this goal, he pursues the fusion of robot navigation and probabilistic perception model. The specific research areas involve multi-object and semantic scene understanding, deep generative model for probabilistic observation, visual navigation and exploration, zero-shot learning and continual learning.

Work Experience

Assistant Professor - UNIST, Ulsan, South Korea (2022 - Present)

Department of Electrical Engineering & AI Graduate School (Affiliated)

Postdoctoral Research Fellow - Carnegie Mellon University, Pittsburgh PA, US (2020 - 2021)

Bot Intelligence Group, Robotics Institute

Graduate Research Assistant - Seoul National University, Seoul, South Korea (2014 - 2020)

Robotics and Intelligent System Laboratory, Electrical and Computer Engineering


Leveraging Advanced Algorithms, Autonomy, and Artificial Intelligence (A4I) to enhance National Security and Defense

Funded by AI Assisted Detection and Threat Recognition Program through the US ARMY ACC APG RTP (2020~2021)

Semantic Image Composition Based on Deep Generative Model

Funded by Samsung DS (2018~2020)

3D Semantic Reconstruction for Human Perception Imitation Based on Deep Generative Model

Funded by National Research Foundation of Korea (NRF) grant funded by the Korea government (2017~2020)

Development and Test Disaster Countermeasure for narrow dwelling space

Funded by Fire Fighting Technology Research and Development Program, funded by the Ministry of Public Safety and Security (2017~2018)

Biomimetic Robot Research

Funded by Agency for Defense Development (ADD) (2016~2020)

Multi agent SLAM, environment recognition and implementation

Funded by Ministry of Science, ICT and Future Planning (2014~2015)


2023, Fall @UNIST

• EE586 Pattern Recognition and Machine Learning

2023, Spring @UNIST

• UNI11001 Understanding Electrical Engineering

• EEE353 Convex Optimization

2022, Fall @UNIST

• LG DX Intensive Course (Computer Vision)

• EE586 Pattern Recognition and Machine Learning

2022, Spring @UNIST

• ITP11701 Introduction to AI Programming II

• AI50101 Introduction to AI

• UNI11001 understanding Electrical Engineering