Fatima Dakalbab

Papers

Total Citations

H-Index

About

Fatima Dakalbab is an emerging researcher at the intersection of cybersecurity, robotics, and algorithmic finance. Her work centers on securing robotic operating systems and developing intelligent trading systems for the foreign exchange market. In her highly cited 2022 analytical review, Dakalbab systematically examined vulnerabilities in Robot Operating Systems (ROS), identifying critical security gaps that threaten autonomous systems—a contribution that has already garnered 3 citations and laid groundwork for safer robotic deployments. She further demonstrated her technical range by designing a machine learning-based trading robot for Forex, achieving 2 citations for its novel integration of predictive models with real-time currency trading. Her most recent 2024 review on algorithmic Forex trading using technical indicators provides a comprehensive framework for navigating the $6.6 trillion daily market, emphasizing how inflation, interest rates, and geopolitical events can be systematically exploited for profit. Though early in her career, Dakalbab’s ability to bridge cybersecurity and quantitative finance—while producing actionable, peer-reviewed tools—marks her as a versatile scholar. Her work not only advances autonomous system safety but also democratizes access to sophisticated Forex trading strategies, making her a rising voice in both fields.