I am a third year Ph.D student in Berkeley AI Research (BAIR) advised by Prof. Trevor Darrell. I received my bachelor degree from Tsinghua University. I have also spent wonderful time at research labs of Facebook AI, University of Toronto and International Computer Science Institute enjoying the collaboration with Prof. Tengyu Ma, Dr. Yuandong Tian, Prof. Jiashi Feng, Prof. Sergey Levine, Prof. Sanja Fidler and Prof. Raquel Urtasun.
My research focuses on modelling th dynamics of the world, leveraging human priors for policy learning, and further enabling learning algorithms to learn in a sample-efficient manner. I am also interestded in solving complex video games/real applications with deep learning and reinforcement learning.
I am an amateur pianist and actively looking for potential collaborations (both music-wise or research-wise!). If you do reinforcement learning or computer vision projects or you play the piano, violin or cello, etc, feel free to contact me for some potential projects or some fun!
Aug. 2012 - Jul. 2016 , Department of Electronic Engineering, Tsinghua University,
Balchlor of Engineering, GPA: 93/100, ranking: 5/238. br> Average of Math and Math-Related Courses: 95.4/100.
Aug. 2014 - Dec. 2014, School of Electrical and Computer Engineering, University of Toronto,
Exchange Student, GPA: 4.0/4.0.
July. 2015 - Sept. 2015, Aug. 2016 - now , Department of Electrical and Computer Engineering, University of California, Berkeley,
Visiting Researcher, PhD Student.
Learning Diverse and Natural Behaviors from Only Observations,
Joint work w/ J. Xu T. DarrellOngoing project [pdf] [code]
Object-Centric Video Prediction,
Joint work w/ B. Chen, M. Yang, Y. Gao, T. DarrellOngoing project [pdf] [code]
Disentangling Propagation and Generation for Video Prediction,
Joint work w/ H. Gao, Q. Cai, R. Wang, F. Yu, T. DarrellTo appear in ICCV'19 [pdf] [code]
Model-based Multiagent Reinforcement Learning for Fast Adaptation,
Joint work w/ Y. Luo, B. Chen, T. DarrellOngoing Project [pdf] [code]
Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling,
Joint work w/ Y. Luo and T. Mapublished at Neurips 2019 Deep Reinforcement Learning Workshop [pdf] [code]
Reinforcement Learning from Imperfect Demonstrations,
Joint work w/ Y. Gao, J. Lin, F. Yu, S. Levine and T. DarrellNeurips Deep RL Symposium [pdf] [code]
Modular Architecture for StarCraft II with Deep Reinforcement Learning,
Joint work w/ D. Lee, H. Tang, J. Zhang, T. Darrell and P. Abbeelpublished at AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 2018 [pdf] [code]
Automobile Visual Taste Ranking,
Joint work w/ S. Fidler, R. Urtasun,
2015 Fall , University of Toronto,
Y. Luo, H. Xu, T. Ma, Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling,, Arxiv Preprint, . [pdf]
H. Gao*, H. Xu*, Q. Cai, R. Wang, F. Yu, T. Darrell, Disentangling Propagation and Generation for Video Prediction, To Appear in ICCV'19, . [pdf]
H. Tang*, D. Lee*, J. Zhang, H. Xu, T. Darrell, P. Abbeel, Modular Architecture for StarCraft II with Deep Reinforcement Learning. The 14th AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment (AIIDE'18). [pdf]
Y. Luo*, H. Xu*, Y. Li, Y. Tian, T. Darrell, T. Ma, Algorithmic Framework for Model-based Reinforcement Learning with Theoretical Guarantees .ICLR'19 (also appeared as ICMLW'18, NeurIPSW'18). [pdf]
Y. Gao*, H. Xu*, F. Yu, S. Levine, T. Darrell, Reinforcement Learning from Imperfect Demonstrations. in NIPS Deep RL Syposium. [pdf]
H. Xu*, Y. Gao*, F. Yu, T. Darrell, End-to-end Learning of Driving Models from Large-scale Video Datasets. in CVPR 2017 (oral). [pdf]
R. Hu, H. Xu, M. Rohrbach, J. Feng, K. Saenko, T. Darrell, Natural Language Object Retrieval. in CVPR 2016 (oral). [pdf]
Tian Xie, Qian Han, Huazhe Xu, Zihao Qi, Wenqian Shen. A Low-Complexity Linear Precoding Scheme Based on SOR Method for Massive MIMO Systems. Vehicular Technology Conference (VTC Spring), 2015 IEEE 81st , vol., no., pp.1-5, 11-14 May 2015. [pdf]
EECS Excellence Award, UC Berkeley, 2016
Comprehensive Excellent Scholarship, Tsinghua Univ, 2013
Academic Excellent Scholarship, Tsinghua, Univ, 2014
Academic Excellent Scholarship, Tsinghua, Univ, 2015
July, 2019: One paper accepted by ICCV'19.
May, 2019: One paper accepted by ICLR'19.
Nov 19, 2018, Our Starcraft 2 Project is covered by Synced (机器之心) and Import AI.
Dec 18, 2017: Giving a talk at Berkeley DeepDrive Workshop.
Oct 31, 2017: Giving a talk at MIT vision seminar in Boston.
June 1, 2017: Giving a talk in at Tsinghua University in Beijing.
Our paper 'End-to-end Learning of Driving Model from Largescale Dataset' appeared at 'New_era' Wechat Media.
Interviewed by a 'Leiphone' reporter about BAIR Blog.
Reviewer of ICLR, Neurips, CVPR, ICML’19
Reviewer of ACCV, Neurips, ICML, CVPR’18
Reviewer of NIPS'17 Intelligent Transportation Workshop
Reviewer of IEEE Transactions on Multimedia’ 16, 17
Editor in BAIR Blog Editorial Board, manager of BAIR facebook handle.
Three Romances for Violin and Piano Op. 22, Clara Schumann
Phatasiestucke, Robert Schumann
Piano Sonata No. 3 in C major, Op. 2, No. 3, Ludwig van Beethoven
Impromptu in B-flat Major D. 935, No. 3 (Op. 142), Franz Schubert
French Suites, BWV 817, Johann Sebastian Bach
Prelude and Fugue No.2, Johann Sebastian Bach
4 Improptus, D899, Franz Schubert
kinderszenen op. 15, Robert Schumann
Waltz in D-flat major, Op. 64, No. 1, Valse du petit chien, Frédéric Chopin
Grande valse brillante in E-flat major, Op. 18, Frédéric Chopin
Tempest Sonata, Ludwig van Beethoven