Changan Chen

Changan Chen 陈昌安

I am a Ph.D. student in Computer Science at UT Austin advised by Prof. Kristen Grauman. I am broadly interested at building machine learning models that perceive the world with multi-modalities and interact with the world. Currently, I work on embodied AI, audio-visual learning and acoustics modeling.

Previously, I spent five months working with Prof. Andrea Vedaldi and Dr. Natalia Neverova at FAIR, London. I was a visiting researcher at FAIR working with Prof. Kristen Grauman for two years. In my undergrad, I spent a wonderful year working with Prof. Greg Mori on sports video analysis and efficient deep learning, eight months working with Prof. Alexandre Alahi on social navigation in crowds, and eight months working with Prof. Manolis Savva on relational graph reasoning for navigation.

My first name is pronounced as /tʃæn'æn/ with the g being silent.

Research opportunities: I am happy to collaborate with motivated undergrad and master students at UT Austin. I am also happy to answer questions about my research. If you are interested, please send me an email.

CV | E-Mail | Google Scholar | Github | Twitter

News

July 2022	Joining FAIR London for summer internship!
July 2022	Receiving Professional Development Awards from UT Austin!
March 2022	We are organizing the first AV4D: Visual Learning of Sounds in Spaces workshop at ECCV 2022!
March 2022	I am very honored to receive the 2022 Adobe Research Fellowship!
Feb 2022	Organizing the second SoundSpaces Challenge at the Embodied AI Workshop, CVPR 2022!
Feb 2021	Organizing the first SoundSpaces Challenge at the Embodied AI Workshop, CVPR 2021!
July 2020	Released a curated reading list for embodied vision: awesome-embodied-vision
May 2020	Joining Facebook AI Research as a visiting researcher

Publications

	Retrospectives on the Embodied AI Workshop Matt Deitke, Dhruv Batra, Yonatan Bisk, Tommaso Campari, Angel X. Chang, Devendra Singh Chaplot, Changan Chen, Claudia Pérez D'Arpino, Kiana Ehsani, Ali Farhadi, Li Fei-Fei, Anthony Francis, Chuang Gan, Kristen Grauman, David Hall, Winson Han, Unnat Jain, Aniruddha Kembhavi, Jacob Krantz, Stefan Lee, Chengshu Li, Sagnik Majumder, Oleksandr Maksymets, Roberto Martín-Martín, Roozbeh Mottaghi, Sonia Raychaudhuri, Mike Roberts, Silvio Savarese, Manolis Savva, Mohit Shridhar, Niko Sünderhauf, Andrew Szot, Ben Talbot, Joshua B. Tenenbaum, Jesse Thomason, Alexander Toshev, Joanne Truong, Luca Weihs, Jiajun Wu arXiv 2022 paper \| website
	SoundSpaces 2.0: A Simulation Platform for Visual-Acoustic Learning Changan Chen, Carl Schissler, Sanchit Garg, Philip Kobernik, Alexander Clegg, Paul Calamia, Dhruv Batra, Philip W Robinson, Kristen Grauman NeurIPS 2022* paper \| project\| website \| code
	Few-Shot Audio-Visual Learning of Environment Acoustics Sagnik Majumder, Changan Chen, Ziad Al-Halah, Kristen Grauman NeurIPS 2022 paper \| project
	Visual Acoustic Matching Changan Chen, Ruohan Gao, Paul Calamia, Kristen Grauman CVPR 2022 (ORAL) paper \| video \| project \| code Media coverage:

Learning Audio-Visual Dereverberation
Changan Chen, Wei Sun, David Harwath, Kristen Grauman
arXiv 2022
paper | project | code

Sound Adversarial Audio-Visual Navigation
Yinfeng Yu, Wenbing Huang, Fuchun Sun, Changan Chen, Yikai Wang, Xiaohong Liu
ICLR 2022
paper | project | code

Semantic Audio-Visual Navigation
Changan Chen, Ziad Al-Halah, Kristen Grauman
CVPR 2021
paper | project | code

	Learning to Set Waypoints for Audio-Visual Navigation Changan Chen, Sagnik Majumder, Ziad Al-Halah, Ruohan Gao, Santhosh K. Ramakrishnan, Kristen Grauman ICLR 2021 paper \| project \| code
	VisualEchoes: Spatial Image Representation Learning through Echolocation Ruohan Gao, Changan Chen, Carl Schissler, Ziad Al-Halah, Kristen Grauman ECCV 2020 paper \| project \| code
	SoundSpaces: Audio-Visual Navigation in 3D Environments Changan Chen, Unnat Jain, Carl Schissler, Sebastia Vicenc Amengual Gari, Ziad Al-Halah, Vamsi Krishna Ithapu, Philip Robinson, Kristen Grauman ECCV 2020 (SPOTLIGHT) paper \| project \| code \| website Media coverage:
	Relational Graph Learning for Crowd Navigation Changan Chen, Sha Hu, Payam Nikdel, Greg Mori, Manolis Savva IROS 2020 paper \| code
	Crowd-Robot Interaction: Crowd-aware Robot Navigation with Attention-based Deep Reinforcement Learning Changan Chen, Yuejinag Liu, Sven Kreiss, Alexandre Alahi ICRA 2019 paper \| code
	Constraint-Aware Deep Neural Network Compression Changan Chen, Frederick Tung, Naveen Vedula, and Greg Mori ECCV 2018 paper \| code

Presentations & Talks

June 2022	Oral presentation at CVPR 2022, "Visual Acoustic Matching" (Slides)
June 2021	Invited talk at Facebook Reality Labs, "Learning Audio-Visual Dereverberation" (Slides)
June 2021	Invited talk at EPIC Workshop, CVPR 2021, "Semantic Audio-Visual Navigation" (Slides)
Sept. 2020	Invited talk at CS391R: Robot Learning at UT Austin, ""Audio-Visual Navigation" (Slides)
Dec. 2018	Invited talk at SwissAI Meetup, "Navigation in Crowds: From 2D Navigation to Visual Navigation"
Nov. 2018	Invited talk at Swiss Machine Learning Day, "Crowd-aware Robot Navigation with Attention-based DRL"
May 2018	Poster presentation at SFU-ZJU Joint Symposium, "Constraint-aware Deep Neural Network Compression"

Affiliations


ZJU 2014-2016	SFU 2016-2019	EPFL 2018	UT AUSTIN 2019 - present	FAIR 2020 - 2022

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