NEP-AI

Cpt. Saif works at the intersection of artificial intelligence, robotics, unmanned systems and public safety & security, with a focus on transforming emerging technologies into deployable government capabilities.

Cpt. Saif played a pivotal role in establishing Dubai Police's Unmanned Aerial Systems Center and in building the operational and technical foundations of Dubai Police's core drone capability. His work has supported the adoption of unmanned and autonomous systems across security, emergency response, airspace governance and technology-enabled public safety operations.

He led the development and operation of DroneBox, Dubai Police's autonomous drone station network, and its integration into routine security and public safety response, delivering the first fully autonomous Drone-as-First-Responder (DFR) solution. He has also contributed to securing and supporting major national and international events using unmanned systems, including COP28 and Expo 2020 Dubai.

His key projects include establishing the Autonomous Operations Room, developing counter-UAS detection and response capabilities, machine learning-based UAV classification using micro-Doppler radar, UAS management platforms, and drone-based traffic accident reconstruction for investigative and evidentiary workflows. His work focuses on AI-enabled decision support, autonomous operations, unmanned aerial, ground and surface systems, and intelligent security applications that improve decision speed, coordination and situational awareness across government agencies.

Cpt. Saif holds a Master's degree in Machine Learning and Deep Learning from the University of Strathclyde, Glasgow, and a Bachelor's degree in Computer Science from the American University of Sharjah. He has also completed advanced professional training in artificial intelligence, machine learning and emerging technologies through leading academic, industry and national programs.