07/13/2021
By Sokny Long
The Francis College of Science, Department of Electrical & Computer Engineering, invites you to attend a doctoral dissertation defense by Sensong An on “Machine Learning Aided High Performance Metasurfaces and Microwave Components Design.”
Ph.D. Candidate: Sensong An
Defense Date: Monday, July 26, 2021
Time: 1:30 to 3:30 p.m. EST
Location: This will be a virtual defense via Zoom. Those interested in attending should contact Sensong_An@student.uml.edu and Hualiang_Zhang@uml.edu at least 24 hours prior to the defense to request access to the meeting.
Committee Chair (Advisor): Hualiang Zhang, Ph.D, Associate Professor, Electrical and Computer Engineering, University of Massachusetts Lowell
Committee Members:
- Xuejun Lu, Ph.D., Professor, Electrical and Computer Engineering, University of Massachusetts Lowell
- Wei Guo, Ph.D., Associate Professor, Physics and Applied Physics, University of Massachusetts Lowell
Brief Abstract:
In recent years, Machine Learning (ML) techniques and Deep Neural Networks (DNNs) emerged as a powerful tool that provides accurate predictions and generative designs, which have been adopted to solve problems in various areas such as Computer Vision (CV), Pattern Recognition and pharmaceutical industries. Meanwhile, the inverse design of flat optical devices and microwave components is highly non-intuitive and often time-consuming due to the trial-and-error design process. This PhD dissertation is focused on the application and customization of ML techniques including various types of DNNs (e.g., FC, CNN, GAN) to solve the metasurface forward modeling and inverse design problems. The proposed design approaches can also be extended to other electromagnetic spectrum regime.
All interested students and faculty members are invited to attend the online defense via remote access.