Fen Wu. Professor. Phone: (919) 515-5268; Email: [email protected]; Office: Engineering Building III (EB3) 3254; Website: http://fwu.wordpress.ncsu.edu/

Fen Wu. Professor, Mechanical and Aerospace Engineering, North Carolina State University. Verified email at ncsu.edu - Homepage. ... F Wu, XH Yang, A Packard, G Becker. International Journal of Robust and Nonlinear Control 6 (9‐10), 983-998, 1996. 913: 1996:

Mar 30, 2025 · Professor Fen Wu Homepage. Contact Info Room # 3254 EBIII Office # (919) 515-5268 Fax # (919) 515-7968 Email fwu AT ncsu.edu: Mailing Address North Carolina State University Mechanical & Aerospace Engineering Box 7910 Raleigh, NC 27695: Google Scholar. Researchgate. Education:

吴枫，男，中国科学技术大学电子工程与信息科学系教授、博士生导师，IEEE Fellow。 在加入中国科学技术大学之前，曾历任微软亚洲研究院研究员、主任研究员、首席研究员。 主要研究方向包括：视频编码与通信、多媒体内容分析、计算机视觉等。 已发表IEEE TCSVT、IEEE...

Proceedings of the 15th annual international conference on Mobile computing … Proceedings of the IEEE/CVF conference on computer vision and pattern … IEEE Transactions on Circuits and Systems for...

Jun 12, 2020 · 报告人简介： Dr. Fen Wu received the B.S. and M.S. degrees in automatic control from the Beijing University of Aeronautics and Astronautics, Beijing, China, in 1985 and 1988, respectively, and the...

Fen Wu The problem of designing a globally optimal robust output feedback controller for time-varying polytopic uncertain systems is a well-known non-convex optimization problem.

Fen Wu’s long-term goal is to play an essential role in developing robust and nonlinear control theory. A significant roadblock in the development of robust and nonlinear control theory is solvability (computation), and so his work focuses mainly on solvability. Wu teaches Nonlinear System Analysis and Control (MAE 522).

Fen Wu (Senior Member, IEEE) received the B.S. and M.S. degrees in automatic control from the Beijing University of Aeronautics and Astronautics, Beijing, China, in 1985 and 1988, respectively, and the Ph.D. degree in mechanical engineering from the University of California at Berkeley, Berkeley, CA, USA, in 1995.

Bridging over adaptive and gain-scheduling control techniques, the PI will establish a switching control design framework for nonlinear systems, with ultimate goal of developing efficient control design algorithms.