Hao Dong

董豪北京大学助理教授博士生导师

hao.dong@pku.edu.cn

Google Scholar / Github: Person / Lab

About Me

I am an assistant professor at Peking University studying AI, robotics and vision. I am also a member of Peng Cheng Laboratory.

I have a broad interest in the generalisation problem using generative models and self-supervised learning.

I lead several open source communities, e.g., TensorLayer and OpenMLsys, and won the Best Open Source Software Award at ACM Multimedia 2017.

Previously, I obtained my Ph.D. degree from Imperial College London under the supervision of Yike Guo in fall 2019. Before Ph.D., I received a MSc specialist degree (visual information processing) with distinction from Imperial, and a first-class BEng degree from the University of Central Lancashire. I founded a startup for brain-computer interface with Yike Guo between 2012 and 2014.

Hyperplane Lab

Our lab is part of the CFCS, School of CS at PKU, and has two openings per year for the PhD program, please contact us at least one year in advance.
Our lab looking for visiting students, research assistants and postdocs, we offer international collaboration and oversea PhD opportunities.

Lab Members

PhD and MSc Students
Ruihai Wu PhD 2020
Mingdong Wu PhD 2021
Tianhao Wu PhD 2021
Yan Zhao PhD 2022
Hongchen Wang PhD 2022
Scholarship Available for International Students
有一个2023级考研名额，欢迎联系

Postdocs
Lin Dong Université Pierre et Marie Curie
(join us)
实验室招收一名CV、Robotics方向博后
鹏城国家实验室招收AI工程师和研究员

Robots
Shadow Hand Plus
Franka Emika Panda Robot Arm x 2

Alumni
Guanqi Zhan BS@PKU -> PhD@Oxford Mingxin Yu BS@PKU -> PhD@MIT Junning Shao BS@PKU -> PhD@THU Zihan Ding MSc@Imperial -> PhD@Princeton
Jiahao Huang BS@BIT -> PhD@Imperial Jialei Huang BS@PKU -> PhD@THU Haoqi Yuan BS@PKU -> PhD@PKU Andrew Zhao BS@UBC -> PhD@THU
Yihao Zhao BS@PKU -> PhD@PKU Bingchan Zhao BS@PKU -> PhD@PKU Lan Lyu BS@PKU -> MSc@CMU Minghang Zheng BS@PKU -> PhD@PKU
Zizheng Guo BS@PKU -> PhD@PKU
招收校内外实习生 (gap year, 研究生等)，对RA和外地访问学生提供充足补贴

Courses

Introduction to Computing (A) (Fall Term 2022)

Deep Generative Models (Spring Term 2020 - 2022)

previous courses

Introduction to Computing (B) (Fall Term 2020 - 2021)

Study and Practice on Topics of Frontier Computing (I) (Autumn Term 2019)

Introduction to Deep Learning (Turing Class) (Summer Term 2019)

Services

Open-Source Organisation: Founder and Organiser of TensorLayer and OpenMLsys communities

Journal Organisation

Associate Editor of Machine Intelligence Research

show more

Conference Organisation

Co-chair of Human in the Loop Learning (HiLL) Workshop @ NeurIPS 2022 NEW
Organiser of International Workshop on Safe Reinforcement Learning Theory and its Applications @ IEEE International Conference on Multi-sensor Fusion and Integration (MFI) 2022
Co-chair of International Workshop on Big Data Analytics for Sustainability @ IEEE International Conference Big Data 2022
Technical Program Committee of IEEE DependSys 2022

Peer-reviewed Journals and Conferences

Senior Program Committee, AAAI (23) NEW
Reviewer, NeurIPS Dataset and Benchmark (22)
Reviewer, NeurIPS (21,22)
Reviewer, CoRL (20,21,22)
Reviewer, IROS (20,21,22)
Reviewer, CVPR (21,22)
Program Committee, AAAI (22)
Reviewer, ICRA (22)
Reviewer, ICCV (21)
Reviewer, SIGGRAPH Asia (20)
Reviewer, MICCAI (20)
Reviewer, China CAD&CG (20)
Reviewer, EuroGRAPHICS (20)
Reviewer, PAMI (19)
Reviewer, SIGGRAPH (19)
Reviewer, TIP (18)
Reviewer, TKDE (18)
Reviewer, PLUS ONE (18)
Reviewer, Neurocomputing (17)

Books
	Deep Reinforcement Learning: Fundamentals, Research and Applications Hao Dong, Zihan Ding, Shanghang Zhang Eds. Springer 2020 ISBN 978-981-15-4094-3 Other Versions 深度强化学习：基础、研究与应用董豪、丁子涵、仉尚航等著（简体中文译本 Simplified Chinese）电子工业出版社 2021 ISBN 978-7-121-41188-5 新一代AI霸主 - 深度強化學習董豪、丁子涵、仉尚航等著（繁體中文譯本 Traditional Chinese）深智數位 2022 ISBN 978-986-0776-82-9 [Homepage（及免费中文在线）] [Springer] [Broadview] [繁体版本] [京东]
	机器学习系统：设计与实现（Machine Learning System: Design and Implementation） Luo Mai, Hao Dong et al 清华大学出版社 Tsinghua University Press 2022 ISBN Coming Soon. [免费中文在线] [OpenMLsys Organisation]
	深度学习：一起玩转TensorLayer（Deep Learning using TensorLayer） Hao Dong, Yike Guo, Guang Yang et al 电子工业出版社 Publishing House of Electronics Industry 2018 ISBN: 9787121326226. [Amazon] [京东] [Broadview] [Code] [Organisation] [Documentation]
	Chapter: Survey on Feature Extraction and Applications of Biosignals Akara Supratak, Chao Wu, Hao Dong, Kai Sun, Yike Guo Machine Learning for Health Informatics, Springer, Page 161-182 2016. [Springer]
	[ show more ]
Papers	( show recent selected / show all )
	Towards Human-Level Bimanual Dexterous Manipulation with Reinforcement Learning Yuanpei Chen, Yaodong Yang, Tianhao Wu, Shengjie Wang, Xidong Feng, Jiechuang Jiang, Stephen Marcus McAleer, Hao Dong, Zongqing Lu, Song-Chun Zhu arXiv 2022. [Paper] [Project] [Code]
	GraspARL: Dynamic Grasping via Adversarial Reinforcement Learning Tianhao Wu, Fangwei Zhong, Yiran Geng, Hongchen Wang, Yongjian Zhu, Yizhou Wang, Hao Dong arXiv 2022. [Paper]
	RoboAssembly: Learning Generalizable Furniture Assembly Policy in a Novel Multi-robot Contact-rich Simulation Environment Mingxin Yu, Lin Shao, Zhehuan Chen, Tianhao Wu, Qingnan Fan, Kaichun Mo and Hao Dong arXiv 2022. [Paper] [Project]
	DualAfford: Learning Collaborative Visual Affordance for Dual-gripper Object Manipulation Yan Zhao, Ruihai Wu, Zhehuan Chen, Yourong Zhang, Qingnan Fan, Kaichun Mo, Hao Dong arXiv 2207.01971 2022. [Paper] [Code]
	AdaAfford: Learning to Adapt Manipulation Affordance for 3D Articulated Objects via Few-shot Interactions Yian Wang, Ruihai Wu, Kaichun Mo, Jiaqi Ke, Qingnan Fan, Leonidas Guibas, Hao Dong European Conference on Computer Vision (ECCV) 2022*. [Paper] [Project]
	Model-based Policy Optimization for Networked Systems Yali Du, Chengdong Ma, Yuchen Liu, Runji Lin, Hao Dong, Jun Wang, Yaodong Yang International Conference on Intelligent Robots and Systems (IROS) 2022. [Paper] [Code]
	VAT-Mart: Learning Visual Action Trajectory Proposals for Manipulating 3D ARTiculated Objects Ruihai Wu, Yan Zhao, Kaichun Mo, Zizheng Guo, Yian Wang, Tianhao Wu, Qingnan Fan, Xuelin Chen, Leonidas Guibas, Hao Dong International Conference on Learning Representations (ICLR) 2022. [Paper] [Code] [Project] [Youtube] [Bilibili]
	DMotion: Robotic Visuomotor Control with Unsupervised Forward Model Learned from Videos ---The First Attempt to Learn the Forward Model Unsupervisedly via Motion Disentanglement Haoqi Yuan, Ruihai Wu, Andrew Zhao, Haipeng Zhang, Zihan Ding, Hao Dong International Conference on Intelligent Robots and Systems (IROS) 2021. [Paper] [Project] [Code]
	End-to-End Object Detection with Adaptive Clustering Transformer Minghang Zheng, Peng Gao, Xiaogang Wang, Hongsheng Li, Hao Dong British Machine Vision Conference (BMVC) 2021 Oral. [Paper] [Code]
	Contrastive Multimodal Fusion with TupleInfoNCE Yunze Liu, Qingnan Fan, Shanghang Zhang, Hao Dong, Thomas Funkhouser, Li Yi International Conference on Computer Vision (ICCV) 2021. [Paper] [Code]
	P4Contrast: Contrastive Learning with Pairs of Point-Pixel Pairs for RGB-D Scene Understanding Yunze Liu, Li Yi, Shanghang Zhang, Qingnan Fan, Thomas Funkhouser, Hao Dong arXiv 2012.13089. [Paper] [Code]
	Tensorlayer 3.0: A Deep Learning Library Compatible with Multiple Backends Cheng Lai, Jiarong Han, Hao Dong International Conference on Multimedia & Expo Workshops (ICMEW) 2021.
	Fast and Flexible Human Pose Estimation with HyperPose Yixiao Guo, Jialei Liu, Guo Li, Luo Mai, Hao Dong ACM Multimedia (MM) Open Source 2021*. [Paper] [Code]
	Bilateral Asymmetry Guided Counterfactual Generating Network for Mammogram Classification Chu-ran Wang, Jing Li, Fandong Zhang, Xinwei Sun􏰀, Hao Dong, Yizhou Yu, and Yizhou Wang IEEE Trans. Image Processing (TIP) 2021. [Paper]
	Efficient Reinforcement Learning Development with RLzoo Zihan Ding, Tianyang Yu, Yanhua Huang, Hongming Zhang, Luo Mai, Hao Dong ACM Multimedia (MM) Open Source 2021. [Paper] [Code]
	Edge-Enhanced Dual Discriminator Generative Adversarial Network for Fast MRI with Parallel Imaging Using Multi-view Information Jiahao Huang, Weiping Ding, Jun Lv, Jingwen Yang, Hao Dong, Javier Del Ser, Jun Xia, Tiaojuan Ren, Stephen Wong, Guang Yang Applied Intelligence 2021. [Paper]
	Generative 3D Part Assembly via Dynamic Graph Learning ---The First Attempt to Assemble 3D Part without External Guidance Jialei Huang, Guanqi Zhan, Qingnan Fan, Kaichun Mo, Lin Shao, Baoquan Chen, Leonidas Guibas, Hao Dong Neural Information Processing Systems (NeurIPS) 2020. [Paper] [Code] [Project]
	ACL-GAN: Unpaired Image-to-Image Translation using Adversarial Consistency Loss Yihao Zhao, Ruihai Wu, Hao Dong European Conference on Computer Vision (ECCV) 2020. [Paper] [Code] [Project]
	Lyapunov-Based Reinforcement Learning for Decentralized Multi-Agent Control Qingrui Zhang, Hao Dong and Wei Pan International Conference on Distributed Artificial Intelligence (DAI) 2020 (Oral). [Paper]
	Role-Wise Data Augmentation for Knowledge Distillation Jie Fu, Xue Geng, Zhijian Duan, Bohan Zhuang, Xingdi Yuan, Adam Trischler, Jie Lin, Chris Pal, Hao Dong arXiv-2004.08861 2020. [Paper] [Code]
	DLGAN: Disentangling Label-Specific Fine-Grained Features for Image Manipulation Guanqi Zhan, Yihao Zhao, Bingchan Zhao, Haoqi Yuan, Baoquan Chen, Hao Dong arXiv:1911.09943 2019. [Paper]
	An Artificial Intelligence Based Data-driven Approach for Design Ideation Liuqing Chen, Pan Wang, Hao Dong, Feng Shi, Ji Han, Yike Guo, Peter RN Childs, Jun Xiao, Chao Wu Journal of Visual Communication and Image Representation 2019. [Paper]
	SIMGAN: Photo-Realistic Semantic Image Manipulation Using Generative Adversarial Networks Simiao Yu, Hao Dong, Felix Liang, Yuanhan Mo, Chao Wu, Yike Guo International Conference on Image Processing (ICIP) 2019 (Oral). [Paper]
	Conditional Image Synthesis Using Stacked Auxiliary Classifier Generative Adversarial Networks Zhongwei Yao, Hao Dong, Pan Wang, Chao Wu, Yike Guo Future of Information and Communications Conference (FICC) 2018. [Paper]
	Generative Creativity: Adversarial Learning for Bionic Design Simiao Yu, Hao Dong, Pan Wang, Chao Wu, Yike Guo International Conference on Artificial Neural Networks (ICANN) Munich, Germany, 2019. [Paper]
	Text-to-Image Synthesis via Visual-Memory Creative Adversarial Network Shengyu Zhang, Hao Dong, Wei Hu, Yike Guo, Chao Wu, Di Xie, Fei Wu Pacific Rim Conference on Multimedia (PCM) 2018. [Paper]
	Dropping Activation Outputs with Localized First-layer Deep Network for Enhancing User Privacy and Data Security Hao Dong, Chao Wu, Wei Zhen, Yike Guo IEEE Trans. on Inform. Forensics and Security (TIFS) 2018. [Paper]
	Towards Desynchronisation Detection in Biosignals Akara Supratak, Steffen Schneider, Hao Dong, Ling Li, Yike Guo Neural Inform. Process. Systems (NeurIPS) Time Series Workshop 2017. [Paper] [Project]
	SisGAN: Semantic Image Synthesis via Adversarial Learning ---The First Attempt to Manipulate Image using Natural Language (Text-Guided Image Manipulation) Hao Dong, Simiao Yu, Chao Wu, Yike Guo International Conference on Computer Vision (ICCV) 2017. [Paper]
	TensorLayer: A Versatile Library for Efficient Deep Learning Development ---Winner of the Best Open Source Software Award Hao Dong, Akara Supratak, Luo Mai, Fangde Liu, Axel Oehmichen, Simiao Yu, Yike Guo ACM Multimedia (MM) Open Source 2017. [Paper] [Code] [Organisation] [Documentation]
	DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction Guang Yang, Simiao Yu, Hao Dong, Greg Slabaugh, Pier Luigi Dragotti, Xujiong Ye, Fangde Liu, Simon Arridge, Jennifer Keegan, Yike Guo, David Firmin IEEE Trans. Med. Imag. (TMI) 2017. [Paper] [Code]
	Deep De-Aliasing for Fast Compressive Sensing MRI Simiao Yu, Hao Dong, Guang Yang, Greg Slabaugh, Pier Luigi Dragotti, Xujiong Ye, Fangde Liu, Simon Arridge, Jennifer Keegan, David Firmin, Yike Guo arXiv:1705.07137 2017. [Paper]
	I2T2I: Learning Text to Image Synthesis with Textual Data Augmentation Hao Dong, Jingqing Zhang, Douglas McIlwraith, Yike Guo International Conference on Image Processing (ICIP) 2017 (Oral). [Paper] [Code]
	Unsupervised Image-to-Image Translation with Generative Adversarial Networks Hao Dong, Paarth Neekhara, Chao Wu, Yike Guo arXiv:1701.02676 2017. [Paper] [Code]
	DeepSleepNet: a Model for Automatic Sleep Stage Scoring based on Raw Single-Channel EEG Akara Supratak, Hao Dong, Chao Wu, Yike Guo IEEE Trans. on Neural Systems and Rehabilitation Eng. (TNSRE) 2017. [Paper] [Code]
	Mixed Neural Network Approach for Temporal Sleep Stage Classification Hao Dong, Akara Supratak, Wei Pan, Chao Wu, Paul M Matthews, Yike Guo IEEE Trans. on Neural Systems and Rehabilitation Eng. (TNSRE) 2017. [Paper]
	Automatic Brain Tumor Detection and Segmentation Using U-Net Based Fully Convolutional Networks Hao Dong, Guang Yang, Fangde Liu, Yuanhan Mo, Yike Guo Medical Image Understanding and Analysis (MIUA) 2017 (Oral). [Paper]
	TensorDB: Database Infrastructure for Continuous Machine Learning Fangde Liu, Axel Oehmichen, Jingqing Zhang, Kai Sun, Hao Dong, Yuanman Mo, Yike Guo International Conference Artificial Intelligence (ICAI) 2017. [Paper]
	A New Soft Material based In-the-Ear EEG Recording Technique Hao Dong, Paul M Matthews, Yike Guo Int. Eng. in Medicine and Biology Conf. (EMBC) 2016 (Oral). [Paper]
	DropNeuron: Simplifying the Structure of Deep Neural Networks Wei Pan, Hao Dong, Yike Guo arXiv:1606.07326 2016. [Paper] [Code]