PhotonIcs and Electromagnetics Research Symposium, also known as Progress In Electromagnetics Research Symposium

Focus & Special Sessions

Session Title

5_FocusSession.SC5: Machine Learning for Electromagnetic Inverse Problems 1

Session Organizers

  • Zhun Wei


    Zhejiang University

  • Xudong Chen


    National University of Singapore

Session Information

The session welcomes all papers that are related to learning approach to electromagnetic inverse problems. Both types of inverse problems are within the scope of the session, i.e., parameter identification and inverse design. The former usually presents unique ground truth, such as in inverse scattering, localization, and CT imaging. The latter usually admits multiple solutions, such as design of photonic crystal, antenna design, and array synthesis. The session aims at presenting frontier research in the theories, computations, and applications of machine learning for solving electromagnetic inverse problems. All types of learning algorithms are welcomed: supervised and semi-supervised learning, unsupervised learning, and reinforcement learning. Uncertainty quantification (UQ) analysis is also an important topic of this session. Applications include but not limited to microwave imaging, through-wall-imaging, non-line-of-sight imaging, subsurface detection, electric impedance or capacitance tomography, biomedical imaging, near-field optical imaging, non-destructive testing/evaluation, and remote sensing.

Submitted Articles

Note: The following submitted articles are not guaranteed to be scheduled in the final program at this stage. The final presentation type and arranged session will be decided by Technical Program Committee.

Presenting Author

Talk Time | Paper Title | Authors | Abstract

Qi-Jun Zhang


Carleton University

  • 08:00Advances in Artificial Neural Network Techniques for Inverse Modeling of Microwave Components
    KeynoteJing Jin(Tianjin University), Qi-Jun Zhang(Carleton University)

Rui Chen


Sun Yat-Sen University

  • 09:55Focus Shaping Using Untrained Artificial Neural Network
    Ze-Yang Chen(Sun Yat-sen University), Zhun Wei(Zhejiang University), Rui Chen(Sun Yat-Sen University)

Feng Han


Xiamen University

  • 09:40A Tailored Semi-physics-driven Artificial Neural Network for Electromagnetic Full-wave Inversion
    Feng Han(Xiamen University), Yanjin Chen(Xiamen University), Miao Zhong(Xiamen University), Zhen Guan(Xiamen University)

Keeley Edwards


University of Manitoba

Mahta Moghaddam


University of Southern California

  • 09:10Latest Advances in Learning-assisted Information Retrieval from Microwave Observations in Biomedical Inverse Scattering and Environmental Sensing
    KeynoteMahta Moghaddam(University of Southern California)

Jelena Vuckovic


Stanford University

  • 08:40Scalable Semiconductor Classical and Quantum Photonic Systems
    KeynoteJelena Vuckovic(Stanford University)