Zhang-Wei Hong

In Fall 2020, I will be a 1st-year Ph.D. student in Computer Science at Massachusetts Institute of Technology, advised by Prof. Pulkit Agrawal. The ultimate goal of my research is to create an autonomous robot that can survive in unknown environments and learn necessary knowledge without any human intervention. To this end, I'm studying Reinforcement Learning with an emphasis on intrinsically motivated exploration in continual learning scenarios.

I finish my B.S. degree and M.S. degree at National Tsing Hua University in close colloaboration with Prof. Chun-Yi Lee and Prof. Min Sun. Previously, I was fortunate to work with Prof. Jan Peters at TU Darmstadt in Germany. Also, I was working at Preferred Networks with Dr. Guilherme Maeda and Prabhat Nagarajan.



Research Intern Jun. 2019 - Oct. 2019
Preferred Networks
Advisor: Prabhat Nagarajan and Dr. Guilherme Maeda.

Research intern Feb. 2019 - Jun. 2019
Advisor: Prof. Min Sun

Visiting researcher Jul. 2018 - Oct. 2018
Intelligent Autonomous System (IAS) group at TU Darmstadt
Advisor: Prof. Jan Peters

Research Assistant 2017 Jul. - 2020 Mar.
ELSA Lab at National Tsing Hua University
Advisor: Prof. Chun-Yi Lee

Research Collaboration 2016 Oct. - 2017 Mar.
Vision Science Lab at National Tsing Hua University
Advisor: Prof. Min Sun

Teaching Assistant 2017 - 2018
Taiwan NVIDIA Deep Learning Institute
Advisor: Prof. Chun-Yi Lee

Software Engineering Intern Jul. 2016 - Nov. 2016
Advisor: Anthony Liu

Contract Software Engineer Oct. 2015 - Dec. 2015
Industrial Technology Research Institute (ITRI)


Adversarial Active Exploration for Inverse Dynamics Model Learning
Zhang-Wei Hong, Tsu-Jui Fu, Tzu-Yun Shann, Yi-Hsiang Chang, and Chun-Yi Lee
Conference on Robot Learning (CoRL) 2019 - Oral
Paper | Project

Diversity-Driven Exploration Strategy for Deep Reinforcement Learning
Zhang-Wei Hong, Tzu-Yun Shann, Shih-Yang Su, Yi-Hsiang Chang, Tsu-Jui Fu, and Chun-Yi Lee
Neural Information Processing Systems (NeurIPS) 2018 - Poster
International Conference on Representation Learning (ICLR) Workshop 2018
Paper | Project

Virtual-to-Real: Learning to Control in Visual Semantic Segmentation
Zhang-Wei Hong, Chen Yu-Ming, Shih-Yang Su, Tzu-Yun Shann, Yi-Hsiang Chang, Hsuan-Kung Yang, Brian Hsi-Lin Ho, Chih-Chieh Tu, Yueh-Chuan Chang, Tsu-Ching Hsiao, Hsin-Wei Hsiao, Sih-Pin Lai, and Chun-Yi Lee
International Joint Conference on Artificial Intelligence (IJCAI) 2018 - Oral
Paper | Project

Deep Policy Inference Q-Network for Multi-Agent Systems
Zhang-Wei Hong, Shih-Yang Su, Tzu-Yun Shann, Yi-Hsiang Chang, and Chun-Yi Lee
International Conference On Autonomous Agents and Multi-Agent Systems (AAMAS) 2018 - Oral

Tactics of adversarial attack on deep reinforcement learning agents
Yen-Chen Lin, Zhang-Wei Hong, Yuan-Hong Liao, Meng-Li Shih, Ming-Yu Liu, and Min Sun
International Joint Conference on Artificial Intelligence (IJCAI) 2018 - Poster
Paper | Project


Teacher Assistant, Deep Learning Institute, NVIDIA Taiwan Spring 2018

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