Chengguang Xu
PhD Student
Education
- MS Control Theory and Engineering, Nankai University, China
- BEng in Automation, Nankai University, China
Biography
Chengguang Xu is a PhD student at Northeastern University in the Khoury College of Computer Sciences, co-advised by Professor Chris Amato and Professor Lawson Wong. He earned his Bachelor of Engineering and Master of Science from Nankai University in China. His main fields of research are Reinforcement Learning and Computer Vision. Specifically, he is interested in learning and planning under uncertainty by leveraging model-free deep reinforcement learning algorithms and model-based planning methods.
What are the specifics of your graduate education (thus far)?
I work on designing deep learning based algorithms with a special focus on robot navigation in unseen environments.
What are your research interests?
I have broad interests in deep reinforcement learning, computer vision, and learning-based navigation algorithms.
What aspect of what you do is most interesting?
Designing navigation algorithms that can leverage the state-of-the-art deep learning advances is appealing and challenging. In particular, I am interested in developing navigation algorithms that can allow the robot to perform fast adaption in unseen environments.
What are your research or career goals, going forward?
Being a faculty or a research scientist is always my goal.
Recent Publications
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Deep Supervised Summarization: Algorithm and Application to Learning Instructions
Citation: Deep Supervised Summarization: Algorithm and Application to Learning Instructions C. Xu and E. Elhamifar, Neural Information Processing Systems (NeurIPS), 2019. -
Hierarchical Robot Navigation in Novel Environments Using Rough 2-D Maps
Citation: Xu, Chengguang, Chris Amato and Lawson L. S. Wong. “Hierarchical Robot Navigation in Novel Environments using Rough 2-D Maps.” ArXiv abs/2106.03665 (2021): n. pag.