研究领域：人工智能

学科方向：1. 模式识别与智能系统（控制科学与工程）；2. 计算机应用技术（计算机科学与技术）

研究方向：机器学习，因果推理，多模态大模型，人工智能生成内容，具身智能等

研究分享公众号（微信搜一搜）：PRML Research Group

依托科研平台：

1. 系统控制与信息处理教育部重点实验室；

2. 海底科学与划界全国重点实验室；

3. 航空电子综合与体系集成全国重点实验室

博士后招募

拟招募博士后1~2名，从事大数据与人工智能研究。

要求：临近博士毕业或博士毕业两年以内；附两封推荐信（其一来自博士生指导教师）。

欢迎感兴趣的博士毕业生发邮件联系

*士生招募

拟招募202*年9月入学**生*名。

欢迎感兴趣的**生在202*年*月至**月发邮件联系并进行考查

Research Statement

During the past 20 years, I have made systematic contributions on the following areas: 

1. Bayesian Machine Learning (which is uncertainty aware and data efficient): Probabilistic Modeling and Approximate Inference Methods; 

2. Multiview/Multimodal Machine Learning: Theory, Methods and Applications.

For future research, the following areas will be emphasized, which certainly will blend with the above expertise:

1. Causal Inference, Reinforcement Learning, Commonsense Reasoning, Large Multimodal Model;

2. Application: AI Generated Content, Embodied Intelligence, Robotics.

Research Keywords: 

Sequential Data Modeling, Causal Reasoning, Multi-modal Learning,

Multi-view Learning, Reinforcement Learning, Embodied Intelligence.

个人简介/Biography

个人简介：

孙仕亮，上海交通大学教授。担任上海市计算机学会人工智能专委会主任，上海市图像图形学学会机器学习专委会主任。本科毕业于北京航空航天大学，博士毕业于清华大学，曾在University College London，Columbia University等海外高校从事访问研究。2011年至2023年在华东师范大学任职教授，2018年至2023年担任华东师范大学人工智能研究所常务副所长。目前担任上海交通大学大数据与人工智能实验室（PRML Research Group）负责人。入选国家级青年人才支持计划。主要研究方向为机器学习、人工智能。担任JMLR、IEEE TPAMI、自动化学报等国内外著名期刊编委（Associate Editor），国际期刊 Pattern Recognition 副主编（Associate Editor in Chief），国际期刊 Information Fusion 领域编辑（Area Editor）。曾任IEEE TNNLS、IEEE TITS、Pattern Recognition等国际期刊编委（Associate Editor）六年以上。曾获省部级自然科学奖一等奖、科技进步奖一等奖及中国自动化学会自然科学奖一等奖等重要奖项。迄今发表学术论文200多篇，2020年出版中文教材《模式识别与机器学习》（清华大学出版社），2019年、2023年、2026年共出版多源数据融合领域中英文专著三部。近年来带领团队在加强对人工智能基础算法和技术研究的同时，致力于面向国家和社会的核心需求和技术难题开展攻关。

Biography:

Shiliang Sun received the B.E. degree in Automation from Beijing University of Aeronautics and Astronautics, Beijing, China, in 2002 and the Ph.D. degree in Pattern Recognition and Intelligent Systems from Tsinghua University, Beijing, China, in 2007. 

He is a Professor with the School of Automation and Intelligent Sensing and the Head of the Pattern Recognition and Machine Learning Research Group, Shanghai Jiao Tong University, Shanghai, China. In 2004, he was entitled Microsoft Fellow. From 2009 to 2010, he was a Visiting Researcher with the Department of Computer Science, Centre for Computational Statistics and Machine Learning, University College London, London, U.K. In 2014, he was a Visiting Researcher with the Department of Electrical Engineering, Columbia University, New York, NY, USA. From 2011 to 2023, he was a Full Professor at East China Normal University where he founded the Pattern Recognition and Machine Learning Research Group in 2007. His research results have expounded in 200+ publications at peer-reviewed journals and conferences, such as JMLR, IEEE TPAMI, IEEE TNNLS, ICML and NeurIPS, and multiple academic monographs and textbooks, such as Multiview Machine Learning, and Pattern Recognition and Machine Learning. He previously served as Associate Editor of IEEE Transactions on Neural Networks and Learning Systems, IEEE Transactions on Intelligent Transportation Systems, and Pattern Recognition for more than six years. He is currently serving as Associate Editor of IEEE Transactions on Pattern Analysis and Machine Intelligence, and Action Editor of Journal of Machine Learning Research.

1998~2002 北京航空航天大学 学士

2002~2007 清华大学 博士

2009~2010 伦敦大学学院 访问学者

机器学习与知识发现

模式识别导论

教材与专著

1. 孙仕亮，赵静，模式识别与机器学习，北京：清华大学出版社，2020年10月

2. Shiliang Sun et al., Multiview Machine Learning, Springer Singapore, January 2019

3. 张楠，孙仕亮，面向多视图数据融合的表示学习，北京：北京航空航天大学出版社，2023年2月

4. 孙仕亮，刘艳，赵静，续晋华，王峰，石东昱，机器学习方向本硕博培养体系，北京：北京航空航天大学出版社，2021年4月

5. 殷俊，孙仕亮，多视图子空间学习，北京：北京航空航天大学出版社，2026年2月

论文发表情况（实时更新）

https://scholar.google.com/citations?hl=en&user=whZnq5wAAAAJ&view_op=list_works&sortby=pubdate

https://dblp.org/pid/57/231.html

十篇代表性期刊论文

1. Liang Mao, Shiliang Sun. Sparse variational information bottleneck Gaussian processes for uncertainty estimation. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2026.

2. Shaobo Hu, Hui Huang, Nan Zhang, Shiliang Sun. Robust trusted conflictive multiview collaborative contrastive learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2026.

3. Shiliang Sun, Jingjing Fei, Jing Zhao, Liang Mao. Multi-view collaborative Gaussian process dynamical systems. Journal of Machine Learning Research, 2023, 24(258): 1−32.

4. Wenbo Dong, Shiliang Sun. Multi-view deep Gaussian processes for supervised learning. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(12): 15137-15153.

5. Nan Zhang, Shiliang Sun. Multiview unsupervised shapelet learning for multivariate time series clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023, 45(4): 4981-4996.

6. Shiliang Sun, Daoming Zong. LCBM: A multi-view probabilistic model for multi-label classification. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 43(8): 2682-2696.

7. Shiliang Sun, Wenbo Dong, Qiuyang Liu. Multi-view representation learning with deep Gaussian processes. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2021, 43(12): 4453-4468.

8. Jing Zhao, Shiliang Sun. Variational dependent multi-output Gaussian process dynamical systems. Journal of Machine Learning Research, 2016, 17: 1-36. 

9. Emilio Parrado-Hernández, Amiran Ambroladze, John Shawe-Taylor, Shiliang Sun. PAC-Bayes bounds with data dependent priors. Journal of Machine Learning Research, 2012, 13 (Dec): 3507-3531.

10. Shiliang Sun, John Shawe-Taylor. Sparse semi-supervised learning using conjugate functions. Journal of Machine Learning Research, 2010, 11 (Sep): 2423-2455.

Associate Editor, IEEE Transactions on Pattern Analysis and Machine Intelligence

Action Editor, Journal of Machine Learning Research

上海市计算机学会人工智能专委会主任

上海市图像图形学学会机器学习专委会主任

中国中医药信息学会临床智慧医疗分会副会长

中国医药质量管理协会医学人工智能专委会常务委员