吴巍炜

发布者:吴巍炜发布时间:2019-01-03浏览次数:35965

Dr. Weiwei Wu 

Professor 


School of Computer Science and Engineering, Southeast University 

Room 216, Building of Computer Science 

Tel: 86-025-52091021 Email:weiweiwu at seu dot edu dot cn


Bio

Dr. Weiwei Wu is currently a professor in the School of Computer Science and Engineering, Southeast University, P.R. China. He has published over 60 peer-reviewed papers in international conferences/journals and serves as TPCs and reviewers for several top international journals and conferences. His research interest covers the applications of optimization methods in a wide range of topics, including combinatorial optimization and algorithms, game theory, reinforcement learning, multi-agent systems, swarm system, real-time scheduling. 

large language models (LLMs) have shown poten- tial in human-level intelligence, leading to a surge in research on LLM-based autonomous agents


吴巍炜   教授、博导,入选国家级青年人才计划江苏省杰出青年基金获得者,东南大学计算机科学拔尖基地负责人2011年分别获得香港城市大学和中国科技大学博士学位,2011-2012年新加坡南洋理工大学博士后,2012年起加入东南大学计算机、人工智能、软件学院。研究方向包括智能无人系统、大模型智能决策、强化学习、智能物联网、大数据、深度学习等主持国家重点研发项目课题、国家自然科学基金面上/青年项目、省部级和企业合作项目十余项,在相关研究领域国际会议和期刊上发表学术论文90余篇,发表CCF A+IEEE/ACM Trans. 40余篇担任多个国际著名期刊会议的程序委员会共同主席、委员等。曾先后获得“ACM新星奖”、微软亚洲研究院“微软学者”称号、中国科学院“院长奖”等。

* 我们希望通过研究智能计算方法赋予计算机/机器智能决策能力并优化决策过程,与此相关的理论与应用研究是我们的关注点。

* 我们每周定期举行一次优化方法研讨会“Weekly seminar on optimizations”,分享计算机科学应用研究中广泛涉及的算法设计和优化方法,面向全院学生开放,欢迎有兴趣的同学参加。

* 我们在吴健雄学院建设有智能无人系统兴趣小组。


我们正在招收博士生、硕士生,希望报考的学生有较强的求知欲和驱动力,欢迎有意深造的同学报考,也欢迎有意向参与科研的优秀本科生加入实验室和无人系统兴趣小组有意申请者发送简历至:weiweiwu@seu.edu.cn。想了解我们培养思路的同学可移步阅读我们的招生说明>>

* 历届毕业生主要就职于腾讯、阿里、字节、华为等互联网大厂,研究所、银行等国企以及高校等。


Research/Projects (Examples but not limited)

1. Autonomous Robot/Vehicles

Study the self-driving, autonomous tracking, and searching problem on a real-implemented robots, autonomous cars or UAVs, which is highly related to CV, deep learning, reinforcement learning and autonomous system. 




2. LLM-based intelligent decision

Study the research porblems arised in LLM-based autonomous agents, which leverages the potential of large language model (LLMs) in human-level intelligence.  Several types of automonous agents are concerned.


3.Realtime Strategy AI

Study the intelligent decision problem in real-time strategic game scenarios based on machine learning and deep reinforcement learning. E.g., tested in uRTS where multiple units are controlled to compete against the opponent AI. See the DEMO>>  

  


4. Big Data Analysis

Study the prediction problem from multi-source data via deep learning and big data analysis. Examples include for instance the crowdness prediction in the metro environment.  See the DEMO>>


Research Interests

I have wide research interests, including big data, autonomous system, reinforcement learningswarm intelligence, multi-agent systems, and real-time scheduling. In particular, we hope to enable computing machines to make intelligent decisions and optimize the decision process, which is mainly related to intelligent perception and intelligent computing

Related to this goal,  I am currently interested in the following topics

* Autonomous agents 

* Autonomous UAV/robot systems

* Reinforcement learning in sequential decision making

* Intelligent perception from multi-source data

* Deep learning and big data analysis

* Multi-agent coordination and cooperation

* Game theory and incentive mechanism design

* Multi-UAV/Swarm system

* Real-time computing and scheduling

For applications, I am mainly interested in the following topics

* Computer-vision based UAV/Robot planning

* AI-aided networking 

* Object detection, tracking, and ReID

* AI-aided gaming and multi-agent competition

* Multi-UAV monitoring in unknown environments

  

News!

* Our new papers on AoI are accepted in INFOCOM 2023, TMC 2023, CCF A

* Our new papers on game theory are accepted in TMC 2022, AIJ 2023, CCF A

* Our one new paper on scheduling is accepted in TCAD 2022, CCF A

* Our one new paper on freshness data retrieval is accepted in RTSS 2022, CCF A

* Our one new paper on truthful diffusion mechanisms is accepted in AAAI 2021, CCF A
 (congratulations to Xiang!)

* Our one new paper on proportional representation mechanisms is accepted in IJCAI 2021, CCF A
 (congratulations to Xiang!)

* Our one new paper on link prediction is accepted in CIKM, CCF B. 


Academic Positions

Professor, Southeast University, China, 2019-Now.

Associate Professor, Southeast University, China, 2012.11-2019.

Postdoc/Research Fellow, Nanyang Technological University, Singapore, 2011-2012.

  

Education

Ph.D. in Computer Science, City Univertiy of Hong Kong, Hong Kong, CityU, 2007-2011.

Ph.D. in Computer Science, University of Science and Technology of China, China, USTC, 2006-2011.

B.S. in Computer Science and Engineering, South China University of Technology, SCUT, 2002-2006.

  

Awards and Honors

* ACM China, “Rising Star”, 2017.

* Microsoft Research Asia, “MSRA Fellowship”, 2010.

* Chinese Academy of Sciences, “Dean's Scholarship”, 2011.

* City University of Hong Kong, Peter-Ho Scholarship, 2008.

  

Grants (selected)

国家、省部级重点研发、自然基金项目:

面向城市精准管理的新型群智感知技术及应用,国家重点研发项目课题;

不完全信息环境下的众包质量优化机制研究,国家自然基金面上项目;

群智感知中绿色可信的数据收集调度算法研究,国家自然基金面上项目;

面向智能移动出行的网约车个性化引导式调度算法研究,江苏省自然科学青年基金;

带能量供给与变速延迟约束的电压调整节能调度算法研究,国家自然科学基金青年项目;

面向移动物联网中数据检索的优化技术研究,国家自然科学青年基金项目;

面向移动设备在无线供电工业物联网中的关键技术研究,江苏省自然科学青年基金项目;

  

企业合作、军工项目:

多无人机环境快速构建方法,中国XX集团;

基于AI的网络动态切片方法研究,中兴通讯;

无人机智能避障路径规划算法研究,之江实验室课题;

低倍缺陷智能判级算法研究,江苏南钢

道路救援识别算法研究,江苏亿科达;

基于AI的日内交易员策略研究,上海时来;


学术职务

IEEE Transactions on Consumer Electronics (TCE) 特邀编辑
International Conference on Neural Computing for Advanced Applications (NCAA 2021)共同主席

东南大学无人系统与人工智能联合研发中心主任

2011协同创新中心骨干成员

中国计算机学会网络与数据通信专委会委员
ACM SIGCOMM China委员
江苏省计算机学会网络与分布计算专委会委员
机械工业出版社智能物联网系列教材编审委员会委员




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