PhD Spotlight: Amani Al-shawabka, PhD’24, Computer Engineering

Amani Al-shawabka, PhD’24, computer engineering, made substantial contributions to the computer engineering field, particularly in the application of AI for wireless communication systems, with a focus on radio frequency fingerprinting through deep learning.

Originally from Jordan, Amani Al-shawabka earned a master’s degree in computer engineering from Northeastern in 2019 and transitioned to the PhD program in computer engineering. She also received a master’s degree in business administration from German Jordanian University and a bachelor’s degree in communication engineering from Yarmouk University in Jordan. Additionally, she has more than a decade of professional experience in the mobile and cellular network industry.

At Northeastern, Al-shawabka, advised by Tommaso Melodia, William Lincoln Smith Professor of electrical and computer engineering, made substantial contributions to the computer engineering field, particularly in the application of AI for wireless communication systems, with a focus on radio frequency fingerprinting through deep learning. She excelled in utilizing advanced techniques and algorithms in computer vision and natural language processing to address complex challenges within wireless systems. Al-shawabka developed and customized various neural networks, and she employed Generative Adversarial Networks (GANs) and transformers to solve different problems in the wireless communications domain.

Additionally, Al-shawabka designed and implemented testbeds to examine protocols connecting Internet of Things (IoT) devices, such as Wi-Fi, Long Range IoT and Narrowband IoT. She used these testbeds to create extensive datasets and made them available to the research community, where researchers could develop their AI models and use these datasets to benchmark their work and advance the domain.

Al-Shawabka worked with InterDigital Inc., a leading wireless communications and video research company, on applying machine learning to the physical layer of communications systems. Her efforts involve creating a testbed for real-world over-the-air RF data collection, curating RF datasets with detailed labeling in formats used by both industry and academia, and developing machine learning models for enhancing physical layer security in low-cost IoT devices.

Her commitment to research was recognized with Northeastern’s Electrical and Computer Engineering Excellence in Research Award in 2023. Al-shawabka has authored several publications that were presented at esteemed conferences, including the IEEE INFOCOM and MobiHoc, and received notable recognition within the academic community.

She plans to pursue further research, aiming to make significant contributions to AI for wireless systems.