About Me

Amira Guesmi received her Engineer degree in Computer Science & Electrical Engineering from the National School of Engineers of Sfax, Tunisia, in 2016, graduating Magna cum laude. She earned her Ph.D. in Computer Systems Engineering from the National School of Engineers of Sfax and the Polytechnic University Hauts-De-France, France, in 2021, with Summa cum laude honors. Following her Ph.D., she worked as a Postdoctoral researcher at the IEMN-DOAE Laboratory (CNRS-8520) at Polytechnic University Hauts-De-France. Currently, Dr. Guesmi is a research group leader at New York University (NYU) Abu Dhabi, UAE.

Her research interests encompass AI safety, machine learning security and privacy, lifelong learning, approximate computing, and energy-efficient design.

Dr. Guesmi has extensive experience in developing secure frameworks and techniques to protect machine learning models and data from adversarial and backdoor attacks, as well as identifying vulnerabilities in AI systems. She has created methods to ensure the privacy of data in machine learning processes and investigated approaches to make deep learning models more interpretable, enhancing transparency and trust in their decisions and predictions. Additionally, she has explored cutting-edge techniques in computer vision and designed and optimized computing systems to achieve high performance with minimal energy consumption.

She has managed and collaborated on multiple projects simultaneously, contributing to open-source projects and fostering community engagement and innovation. Her work has been published in multiple top-tier conferences across various disciplines, including CVPR, ASPLOS, IROS, and DAC.