Jun Wang Photo 

Jun Wang

Professor, Computer Science, University College London

UCL Centre for Artificial Intelligence

Email: jun.wang (at) cs.ucl.ac.uk

Office: 3.08 66-72 Gower Street, London

Turing Fellow, the Alan Turing Institute

Co-founder, MediaGamma Ltd.

I am looking for a few postdoctoral researchers on Reinforcement Learning, Multiagent Learning and their applications on search and recommendation. If interested, please contact me.

Research Interests

  • AI and Machine Learning, (Multi-agent) Reinforcement Learning and Control, and Neural Generative Models;

  • Statistical Modeling of Information Retrieval, and Dynamic Information Retrieval;

  • Data Mining, Personalization, and Collaborative Filtering (Recommender Systems);

  • Computational Advertising and Real-time Bidding.

Selected Recent Papers

Explainable AI


Explanation Mining: Post Hoc Interpretability of Latent Factor Models for Recommendation Systems
Georgina Peake and Jun Wang
KDD 2018

Bayesian Learning


Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning
Rui Luo and Yaodong Yang and Jianhong Wang and Zhanxing Zhu and Jun Wang
arXiv:1711.11511v3, NIPS 2018

Multi-agent AI


Probabilistic Recursive Reasoning for Multi-Agent Reinforcement Learning
Ying Wen, Yaodong Yang, Rui Luo, Jun Wang, and Wei Pan
ICLR 2019


Mean Field Multi-Agent Reinforcement Learning
Yaodong Yang, Rui Luo, Minne Li, Ming Zhou, Weinan Zhang, and Jun Wang
arXiv:1802.05438, ICML 2018


Learning to Design Games: Strategic Environments in Deep Reinforcement Learning
Haifeng Zhang, Jun Wang, Zhiming Zhou, Weinan Zhang, Ying Wen, Yong Yu, Wenxin Li
arXiv:1707.01310v3, IJCAI 2018


An Empirical Study of AI Population Dynamics with Million-agent Reinforcement Learning
Lianmin Zheng, Jiacheng Yang, Han Cai, Weinan Zhang, Jun Wang, and Yong Yu
arXiv:1709.04511v3, AAMAS 18

Text/Discrete GANs


Long Text Generation via Adversarial Training with Leaked Information
Jiaxian Guo, Sidi Lu, Han Cai, Weinan Zhang, Yong Yu, and Jun Wang
arXiv:1709.08624v1, AAAI 2018


IRGAN: A Minimax Game for Unifying Generative and Discriminative Information Retrieval Models
Wang, Jun, Lantao Yu, Weinan Zhang, Yu Gong, Yinghui Xu, Benyou Wang, Peng Zhang, and Dell Zhang
SIGIR (Best Paper Award Honorable Mention), 2017


SeqGAN: Sequence Generative Adversarial Nets with Policy Gradient
Lantao Yu, Weinan Zhang, Jun Wang, Yong Yu
arXiv:1609.05473v6, AAAI, 2017

Neural Generative Models


Activation Maximization Generative Adversarial Nets
Zhiming Zhou, Han Cai, Shu Rong, Yuxuan Song, Kan Ren, Weinan Zhang, Yong Yu, and Jun Wang
arXiv:1703.02000v7, ICLR 2018


A Neural Stochastic Volatility Model
Rui Luo, Jun Wang, Weinan Zhang and Xiaojun Xu
arXiv:1712.00504, AAAI 2018


Adversarial Variational Inference for Tweedie Compound Poisson Models
Yaodong Yang, Sergey Demyanov, Yunayuan Liu, Jun Wang
arXiv:1706.05446v3, ICML Workshop on Implicit Models, 2017



Reinforcement Learning for Architecture Search by Network Transformation
Han Cai, Tianyao Chen, Weinan Zhang, Yong Yu, and Jun Wang
arXiv:1707.04873v1, AAAI 2018

For a full list, see my Google Scholar page.


Explanation Mining: Post Hoc Interpretability of Latent Factor Models for Recommendation Systems
MAgent: A Many-Agent Reinforcement Learning Research Platform for Artificial Collective Intelligence
Lianmin Zheng, Jiacheng Yang, Han Cai, Weinan Zhang, Jun Wang, and Yong Yu
NIPS17 demo
arXiv:1712.00600, 2017
Multiagent Bidirectionally-Coordinated Nets: Emergence of Human-level Coordination in Learning to Play StarCraft Combat Games
Peng Peng, Ying Wen, Yaodong Yang, Quan Yuan, Zhenkun Tang, Haitao Long, Jun Wang
arXiv:1703.10069v4, 2017
City Traffic Simulator/Optimizer
Each moving dot is driven by a neural network-based reinforcement learning agent
Collaborative Bots Sorting Parcels



Display Advertising with Real-Time Bidding (RTB) and Behavioural Targeting
Jun Wang, Weinan Zhang and Shuai Yuan (2017)
Foundations and TrendsĀ® in Information Retrieval: Vol. 11: No. 4-5, pp 297-435.


Dynamic Information Retrieval Modeling
Grace Hui Yang, Marc Sloan, and Jun Wang (2016)
Synthesis Lectures on Information Concepts, Retrieval, and Services, 2016.

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