Andrew Carnegie Society Scholar Award (CMU 2022); Outstanding Academic Achievement Award (CMUQ 2022); Allen Newell Award for Excellence in Undergraduate Research (Runner-up, CMU 2022); Best Technique and Data-Efficiency Award in the Trojan Detection Challenge (Runner-up, NeurIPS 2022); Best Project Award at the Meeting of the Minds Research Symposium (2nd and 3rd place, CMUQ 2022); Qatar Campus Scholar Award (CMUQ 2022). Publications: 'DeBackdoor: A Deductive Framework for Detecting Backdoor Attacks on Deep Models with Limited Data' (USENIX Security '25); 'FedTeams: Towards Trust-Based and Resource-Aware Federated Learning' (CloudCom 2022). Reviewer for IEEE Transaction on Dependable and Secure Computing (TDSC 2023) and ACM International World Wide Web Conference (WWW 2023).
Research Experience
Research Engineer in the Cyber Security Research Group at Qatar Computing Research Institute. Projects include: aiXamine (LLM Safety & Security, Simplified), Fanar (An Arabic-Centric Multimodal Generative AI Platform), DeBackdoor (A Deductive Framework for Detecting Backdoor Attacks with Limited Data), FedTeams (Towards Trust-Based and Resource-Aware Federated Learning), CASPRE (A CRISPR-Cas12a–Powered Handheld Kit for Rapid Genetic Carrier Testing).
Education
BSc in Computer Science from Carnegie Mellon University, 2018-2022.
Background
Research interests include backdoor attacks and defenses in deep learning, robust machine learning, security of LLMs, federated learning, and the ethics of AI.