IEEE AP-S/URSI 2022
COVID-19 Updates
General
Home
Steering and Organizing Committee
Important Dates
Photos from the Conference
Registration
Program
Technical Program
Plenary Talks
Short Courses
Special Sessions
Women in Engineering
Social Program
Companion Program
Amateur Radio Activities
Master Class
Technology Demonstrations
For Authors
Call for Papers
Submit a Paper
Upload Virtual Presentation
AP-S Topics
URSI Topics
Raj Mittra Travel Grant
Mojgan Daneshmand Grant
TICRA Travel Grants
For Students
Student Paper Competition
Student Design Contest
Student Travel Grant
C. J. Reddy Travel Grant for Graduate Students
Region 9 Student Travel Grants
Master Class
Venue/Travel
Visa Requirements
Venue
Hotels
Things to See and Do
Travel
Event Locations
Sponsorship & Exhibition
Current Sponsors & Exhibitors
Sponsorships
Exhibits
10-15 July 2022 • Denver, Colorado, USA
IEEE AP-S/URSI 2022
10-15 July 2022 • Denver, Colorado, USA
Technical Program
Session TU-A1.1A
Paper TU-A1.1A.4
TU-A1.1A.4
Virtual Presentation
Robustness Optimization of Nanophotonic Devices Using Deep Learning
Ronald Jenkins, Sawyer Campbell, Pingjuan Werner, Douglas Werner, The Pennsylvania State University, United States
Session:
Design and Optimization of Antennas using Machine Learning I
Track:
AP-S: Antennas
Location:
Granite A/B/C (HR)
Presentation Time:
Tue, 12 Jul, 09:00 - 09:20 Denver Time (UTC -6)
Session Co-Chairs:
Zhi Ning Chen, National University of Singapore and Peiqin Liu, National University of Singapore
Presentation
Discussion
Session TU-A1.1A
TU-A1.1A.1: Restoration of Antenna Radiation Pattern Using Conditional Generative Adversarial Network
Yi-Huan Chen, Trung Dung Ha, Danilo Erricolo, Pai-Yen Chen, University of Illinois Chicago, United States
TU-A1.1A.2: Computationally-Efficient and Reliable Antenna Design within the System-by-Design ML-Based Framework
Andrea Massa, Marco Salucci, Pietro Rosatti, Lorenzo Poli, ELEDIA@UniTN - University of Trento, Italy
TU-A1.1A.3: Design of Wideband Mushroom Antennas Using Single- and Multi-Objective Bayesian Optimization
Yunjia Zeng, Xianming Qing, Michael Yan Wah Chia, Institute for Infocomm Research, Singapore
TU-A1.1A.4: Robustness Optimization of Nanophotonic Devices Using Deep Learning
Ronald Jenkins, Sawyer Campbell, Pingjuan Werner, Douglas Werner, The Pennsylvania State University, United States
TU-A1.1A.5: Machine learning based tandem network approach for antenna design
Aggraj Gupta, Chandan Bhat, Uday Khankhoje, IIT Madras, India; Emir Karahan, Kaushik Sengupta, Princeton University, United States
TU-A1.1A.6: A Deep-Learning Characteristic Modes Classification Model for Patch Antennas
Ricardo E. Sendrea, Constantinos L. Zekios, Stavros V. Geogakopoulos, Florida International University, United States
TU-A1.1A.7: Power Pattern to Planar Dipole Array Synthesis Using a Text-to-Image Transformer Based Model
Chen Niu, Puyan Mojabi, University of Manitoba, Canada
TU-A1.1A.8: Supervised Machine Learning Model for Accurate Output Prediction of Various Antenna Designs
Sai Sampreeth Indharapu, Anthony N Caruso, University of Missouri - Kansas City, United States; Kalyan C. Durbhakula, University of Missouri kansas city, United States
TU-A1.1A.9: A Generalized Approach to Real-Time Performance Estimation of Antenna Types Using Deep Learning
Md Rayhan Khan, Constantinos L. Zekios, Shubhendu Bhardwaj, Stavros V. Georgakopoulos, Florida International University, United States
TU-A1.1A.10: Deep Learning based Modeling and Inverse Design for Arbitrary Planar Antenna Structures at RF and Millimeter-Wave
Emir Ali Karahan, Kaushik Sengupta, Princeton University, United States; Aggraj Gupta, Uday K Khankhoje, IIT Madras, India
Resources
No resources available.