Huazhe(Harry) Xu
How to pronounce my name?
In the Wade-Giles system of romanization, it is rendered as Huache Tsu.
In Chinese characters, it is 许华哲.
About Me
I am a 4th 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 Dr. Roberto Calandra, Prof. Tengyu Ma, Dr. Yuandong Tian, Prof. Jiashi Feng, Prof. Sergey Levine, Prof. Sanja Fidler and Prof. Raquel Urtasun.
My research focuses on modeling the dynamics of the world, leveraging/finding 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 also 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, the violin or the cello, etc, feel free to contact me for some potential projects or some fun!
I support Slow Science.
Education
Aug. 2012 - Jul. 2016 , Department of Electronic Engineering, Tsinghua University,
Balchlor of Engineering, GPA: 93/100, ranking: 5/238. 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.
Selected Research Projects
Modeling Visual Dynamics
Hierarchical Style-based Networks for Motion Synthesis,
Joint work w/ J. Xu, X. Wang, T. Darrell
published in ECCV'20 [pdf] [code]
Video Prediction via Example Guidance,
Joint work w/ J. Xu, T. Darrell
Published in ICML'20 [pdf] [code]
Disentangling Propagation and Generation for Video Prediction,
Joint work w/ H. Gao, Q. Cai, R. Wang, F. Yu, T. Darrell
Published in ICCV'19 [pdf] code available upon request.Human priors and dynamics models for efficient policy learning
Scoring-Aggregatin-Planning: framework for learning task-agnostic priors from interactions and rewards for zero-shot generalization,
Joint work w/ B. Chen, Y. Gao, T. Darrell
AAAI'20 Genplan Workshop (spotlight) [pdf] [code]
Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling,
Joint work w/ Y. Luo and T. Ma
Published in ICLR 2020, also published 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. Darrell
Appeared in Neurips Deep RL Symposium [pdf] [code]Learning policies for Real-world Applications
Modular Architecture for StarCraft II with Deep Reinforcement Learning,
Joint work w/ D. Lee, H. Tang, J. Zhang, T. Darrell and P. Abbeel
published in AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment 2018 [pdf] [code]Past Projects
Automobile Visual Taste Ranking,
Joint work w/ S. Fidler, R. Urtasun,
2015 Fall , University of Toronto,
Publications and Manuscripts
J. Xu，H. Xu, B. Ni, X. Yang, X. Wang, T. Darrell, Hierarchical Style-based Networks for Motion Synthesis, ECCV 2020, . [pdf][code]
J. Xu*，H. Xu*, T. Darrell, Video Prediction via Demonstration Guidance, ICML 2020, . [pdf][code]
R. Yang，H. Xu, Y. Wu, X. Wang, Multi-Task Reinforcement Learning with Soft Modularization, ICLR 2020 workshop (oral), . [pdf]
H. Xu*， B. Chen*, Y. Gao, T. Darrell, Scoring-Aggregating-Planning: Learning task-agnostic priors from interactions and sparse rewards for zero-shot generalization, AAAI workshop (spotlight), . [pdf]
Y. Luo, H. Xu, T. Ma, Learning Self-Correctable Policies and Value Functions from Demonstrations with Negative Sampling,, ICLR 2020, . [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]
Honors and Awards
EECS Excellence Award, UC Berkeley, 2016
Comprehensive Excellent Scholarship, Tsinghua Univ, 2013
Academic Excellent Scholarship, Tsinghua, Univ, 2014
Academic Excellent Scholarship, Tsinghua, Univ, 2015
News!
July, 2020: One paper accepted by ECCV'20.
June, 2020: One paper accepted by ICML'20.
Dec, 2019: One paper accepted by ICLR'20.
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.
Service
Committee member of Deep RL workshop at Neurips 2019
Reviewer of ICLR, Neurips, CVPR, ICML, ACCV, ICCV
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.
Miscellaneous
Alain De Botton: The Art of Travel (I traveled less often after reading this :p)
Introduction to Image Understanding (A lovely Course from Prof. Sanja Fidler)
Hilary Hahn's performance of Chaconne (The piece that moves me. I am waiting for Hilary's next record of this piece years later.)
Franz Schubert Sonata D960 (Kafka on The Shore novel by Murakami brought Schubert's D850 to me when I was 16. Then there started my love for Schubert's music.)
Attempts
Here is a partial catalog of my attempts at becoming more than what I am today. I doubt I will ever succeed totally but I hope I will never stop trying.Clarinet Project
Due to COVID-19, I don't have access to a piano. I started polishing my rusty clarinet skills.Piano Project
I am now learning to play the piano(again!) with pianist Anne Rainwater. Here are some pieces I enjoy playing recently:Sonata no.3, Sergei Prokoviev
Prelude op. 23 no. 5 in g minor, Sergei Rachmaninov
Etude op. 10 No. 12 in C minor "Revolutionary", Frédéric Chopin
Piano Sonata No. 15 in D major, Op. 28, Ludwig van Beethoven
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