feixia at stanford.edu
I'm a Research Scientist with Google Research where I work on the Robotics
team. I received my PhD degree from the Department of Electrical Engineering, Stanford University. I was co-advised by Silvio Savarese
and Leo Guibas
. I was supported by Stanford Graduate Fellowship
and Qualcomm Innovation Fellowship
. During my PhD, I have done research internships with Dieter Fox
at Nvidia, and Alexander Toshev
and Brian Ichter
at Google. I obtained my bachelor's degree from Tsinghua University in 2016.
My mission is to build intelligent embodied agents that can interact with complex and unstructured real-world environments, with applications to home robotics. I approach this problem from 3 aspects: 1) Large scale and transferrable simulation for Robotics. 2) Learning algorithms for long-horizon tasks. 3) Combining geometric and semantic representation for environments.
On weekends, depending on availability, I voluntarily host office hours for students (especially underrepresented groups and junior students) who want to get into the field of and develop a career on Machine Learning, Computer Vision, and Robotics. Each slot is 20-minute long. If you want to get advice from me, please fill out this questionnaire.
2021.9 2 papers accepted to CoRL 2021
2021.7 2 papers accepted to IROS 2021
2021.5 I defended my PhD Thesis titled "Large Scale Simulation for Embodied Perception and Robot Learning".
2021.3 I will join Robotics at Google as a Research Scientist in the Fall.
2021.3 ReLMoGen accepted to ICRA2021.
2020.12 The wait is over! iGibson v1.0 was released! It comes with many new features and fully interactive environments, checkout the website for more details.
2020.4 iGibson was released! It is a large scale interactive environment for robot learning.
2020.3 I am co-hosting CVPR Challenge "Sim2Real Challenge with Gibson". It is the first Sim2Real challenge in CVPR.
2019.7 AdaFDR was accepted to Nature Communications.
2019.5 Will Shen and I won Qualcomm Innovation Fellowship as a team. Thank you Qualcomm!
2019.5 AdaFDR won best paper award at RECOMB2019.
2018.4 We will host a demo for Gibson Env at CVPR'18. Come and check it out!
2018.2 One paper accepted to CVPR'18 (spotlight).
Selected Publications [full list]
Sanjana Srivastava*, Chengshu Li*, Michael Lingelbach*, Roberto Martín-Martín, Fei Xia, Kent Vainio, Zheng Lian, Cem Gokmen, Shyamal Buch, C. Karen Liu, Silvio Savarese, Hyowon Gweon, Jiajun Wu, Li Fei-Fei. BEHAVIOR: Benchmark for Everyday Household Activities in Virtual, Interactive, and Ecological Environments. Conference on Robot Learning (CoRL) 2021
Chengshu Li*, Fei Xia*, Roberto Martín-Martín*, Michael Lingelbach, Sanjana Srivastava, Bokui Shen, Kent Vainio, Cem Gokmen, Gokul Dharan, Tanish Jain, Andrey Kurenkov, C. Karen Liu, Hyowon Gweon, Jiajun Wu, Li Fei-Fei, Silvio Savarese
iGibson 2.0: Object-Centric Simulation for Robot Learning of Everyday Household Tasks.
Conference on Robot Learning (CoRL) 2021
Fei Xia*, Chengshu Li*, Roberto Martín-Martín, Or Litany, Alexander Toshev, Silvio Savarese. ReLMoGen: Leveraging Motion Generation in Reinforcement Learning for Mobile Manipulation. ICRA2021.
Bokui Shen*, Fei Xia*, Chengshu Li*, Roberto Martín-Martín*, Linxi Fan, Guanzhi Wang, Shyamal Buch, Claudia D'Arpino, Sanjana Srivastava, Lyne P. Tchapmi, Micael E. Tchapmi, Kent Vainio, Li Fei-Fei, Silvio Savarese. iGibson 1.0: A Simulation Environment for Interactive Tasks in Large Realistic Scenes. IROS 2021.
Fei Xia, William B Shen, Chengshu Li, Priya Kasimbeg, Micael Edmond Tchapmi, Alexander Toshev, Roberto Martín-Martín, Silvio Savarese. Interactive Gibson Benchmark: A Benchmark for Interactive Navigation in Cluttered Environments. ICRA20 + RAL.
Noriaki Hirose, Fei Xia, Roberto Martín-Martín, Amir Sadeghian,
Silvio Savarese (2019). Deep Visual MPC-Policy Learning for Navigation. IEEE Robotics and Automation Letters .
Noriaki Hirose,Amir Sadeghian, Fei Xia, Roberto Martín-Martín, Silvio Savarese. (2019). VUNet: Dynamic Scene View Synthesis for Traversability Estimation using an RGB Camera. IEEE Robotics and Automation Letters.
Fei Xia*, Amir R. Zamir*, Zhiyang He*, Alexander Sax, Jitendra Malik, Silvio Savarese. Gibson Env: Real-World Perception for Embodied Agents.
CVPR 2018 (spotlight, Nvidia Pioneer Research Award). [pdf] [code] [project]
Fei Xia*, Martin Zhang*, James Zou, David Tse. NeuralFDR: learning decision threshold from hypothesis features.
NIPS 2017. [pdf] [code]
(* Equally contributed to the project.)
Previous Computational Biology papers
Martin J. Zhang, Fei Xia, James Zou, "AdaFDR: a Fast, Powerful and Covariate-Adaptive Approach to Multiple Hypothesis Testing", Preliminary version selected as Best Paper Award of RECOMB 2019, also in Nature Communications, 2019. [pdf] [software] [code to reproduce the paper]
Qiao Liu, Fei Xia, Qijin Yin, Rui Jiang. Chromatin accessibility prediction via a hybrid deep convolutional neural network
Bioinformatics. [pdf] [code]
Govinda M Kamath*, Ilan Shomorony*, Fei Xia*, Thomas A Courtade, David Tse. HINGE: long-read assembly achieves optimal repeat resolution.
Genome Research Vol 27 2017.
Ilan Shomorony, Govinda M Kamath, Fei Xia, Thomas A Courtade, David Tse. Partial DNA assembly: a rate-distortion perspective.
Honors and Awards
- 2019 Qualcomm Innovation Fellowship
- 2019 RECOMB Best Paper Award
- 2018 Nvidia Pioneer Research Award at CVPR
- 2016 Stanford Graduate Fellowship (Michael J. Flynn Fellow), Stanford University
- 2015 Chang Jiong Scholarship (Highest honor in Dept. of Automation, 1/560)
- 2014 Fang Chongzhi Scholarship (Highest honor in Dept. of Automation, 1/560)
- 2014 China Scholarship Council Excellent Undergraduate Fellowship