About me

I am a machine learning engineer at 1001 AI. I received my BSc in Computer Science from Carnegie Mellon University.

I develop AI systems that perform complex tasks and help optimize operations. My research work covers adversarial and backdoor attacks in deep learning, robust machine learning, security of LLMs, federated learning, privacy, and genetics.

Projects

CyberXpert: Cybersecurity Expert Agentic System

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

Honors and Awards

• Andrew Carnegie Society Scholar Award, CMU 2022
• Outstanding Academic Achievement Award (1^st in class), 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 (2^nd and 3^rd place), CMUQ 2022
• Qatar Campus Scholar Award, CMUQ 2022

Conference Activities

• Reviewer, IEEE Transaction on Dependable and Secure Computing (TDSC 2023)
• Reviewer, ACM International World Wide Web Conference (WWW 2023)

Publications

• Fanar: An Arabic-Centric Multimodal Generative AI Platform,
  Fanar Team
  arXiv preprint arXiv:2501.13944 (2025)
• DeBackdoor: A Deductive Framework for Detecting Backdoor Attacks on Deep Models with Limited Data,
  Dorde Popovic, Amin Sadeghi, Ting Yu, Sanjay Chawla, and Issa Khalil
  In 34th USENIX Security Symposium (USENIX Security '25)
• FedTeams: Towards Trust-Based and Resource-Aware Federated Learning,
  Dorde Popovic, Hend K. Gedawy, and Khaled A. Harras
  In IEEE International Conference on Cloud Computing Technology and Science (CloudCom 2022)