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President’s Message

Christophe Fumeaux

Christophe Fumeaux,
2025 President, IEEE Antennas and Propagation Society June 2025

Having completed a third of my term as the 2025 IEEE Antennasand Propagation Society (AP-S) President when writing this message (in mid-April 2025), it is an appropriate time to reflect on how the society can best serve its members and the community. To begin with, it is important to recognize that the dedication of our volunteers is the engine enabling the depth and breadth of the society’s activities. AP-S was founded in 1949 by volunteers and remains driven by a spirit of volunteer service. I experience on a daily basis that enthusiasm thrives at all levels of the organization, from the student branches and chapters, to the Administrative Committee of the society.


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Overview of AP-S in its 75th Year

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IEEE APS Election Results 2025


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Maokun LI

Maokun LI
Department of Electronic Engineering
Tsinghua University, Beijing, China
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Maokun LI is currently an associate professor in the Department of Electronic Engineering at Tsinghua University, Beijing, China. He received his B.S. degree in electronic engineering from Tsinghua University, Beijing, China, in 2002, and his M.S. and Ph.D. degrees in electrical engineering from University of Illinois at Urbana-Champaign in 2004 and 2007, respectively. After graduation, he joined Schlumberger-Doll Research as a research scientist. In June 2014, he joined the department of electronic engineering at Tsinghua University. His research interests include fast algorithms in computational electromagnetics and electromagnetic inverse problems.

He served as an associate editor of IEEE Transactions on Antennas and Propagation and IEEE Transactions on Geoscience and Remote Sensing. He is also a member of the AP-S membership and benefits committee. He received the 2017 IEEE Ulrich L. Rohde Innovative Conference Paper Award, the 2019 PIERS Young Scientist Award, 2021 Instructor Award for Excellent Ph.D. Thesis by China Education Society of Electronics.

Titles of talks:

  • Electromagnetic sensing and imaging (for general audience)
  • Application of deep learning techniques to computational electromagnetics
  • Physics-embedded deep learning techniques for EM modeling and data inversion
  • Multiphysics imaging for human thorax
  • Nonlinear multiphysics joint inversion for geophysical and biomedical imaging
  • A Model-based inversion algorithm for electromagnetic data