Salma Kharrat
- Ph.D. Student, Computer Science
- M.S., Computer Science
Biography
Salma Kharrat is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), where her research focuses on machine learning under limited information, spanning federated learning, multi-agent reinforcement learning, and large language models.
Her research has been published in leading AI and machine learning venues, including AISTATS, EMNLP, and ECAI, with contributions such as FilFL, DPFL, and ACING, which address client selection in federated learning, decentralized personalization, and instruction optimization for large language models. During her Ph.D., she was recognized with the KAUST Dean’s List Award.
Salma earned her M.S. in Computer Science from KAUST and her engineering degree from the National School of Computer Science in Tunisia, where she ranked among the top students.
In addition to her research, she has been actively involved in teaching and mentoring, serving as an instructor and teaching assistant for machine learning and AI courses at KAUST and across Saudi Arabia, and mentoring student research projects through KAUST Academy.
Research Interests
Salma research focuses on developing principled algorithms for decentralized learning, personalization under heterogeneity, and black-box optimization, with the goal of advancing scalable and robust intelligent systems.
Awards and Distinctions
- CEMSE Dean's List Award, King Abdullah University of Science and Technology (KAUST), Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division, 2023
Qualifications
Education
- Master of Science (M.S.)
- Computer Science, King Abdullah University of Science and Technology (KAUST), Saudi Arabia, 2023
- Bachelor of Science (B.S.)
- Computer Science, National School of Computer Science (ENSI), Tunisia, 2020