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Kashif Siddiq
Tech Entrepreneur - Radar Technology Expert - Founder & Managing Director at Oxford RF Solutions Ltd
Kashif Siddiq is a prominent tech entrepreneur and the Founder & Managing Director of Oxford RF Solutions Ltd, based in Manchester, England. He specializes in electronic product design, particularly in commercial sensing technologies with a focus on radar systems for Advanced Driver-Assistance Systems (ADAS) and autonomous robotics. Siddiq is recognized for inventing a groundbreaking method for solid-state 360-degree perception sensing, which enables vehicles and robots to perceive their environment without the use of moving parts, setting a new standard in the industry.12
Professional Background
- Founder & CEO at Oxford RF (October 2019 - Present): Under his leadership, Oxford RF has developed the world's first solid-state 360-degree radar system, which aims to streamline the number of sensors needed in vehicles, thereby reducing costs and enhancing reliability.23
- Radar Subject Matter Expert at National Highways (May 2023 - March 2024): Contributed expertise in radar technology to improve highway systems.1
- Previous roles include Senior Radar Engineer at Navtech Radar and Radar Systems Architect at Raymarine, where he led significant projects in radar technology development.1
Education
Siddiq holds a Ph.D. in Electronic and Electrical Engineering from the University of Bath, where his doctoral research focused on oscillator phase noise in millimeter-wave radar systems. He also earned both Bachelor's and Master's degrees in Electrical Engineering from the National University of Sciences and Technology (NUST) in Pakistan.1
Achievements
Kashif Siddiq has received multiple awards throughout his career, including:
- The British Engineering Excellence Award for the 'Design Team of the Year' for his work on Navtech's Clearway product.
- Top honors during his Master's program with a perfect CGPA of 4.0/4.0.14
Siddiq's innovative contributions have positioned him as a key figure in advancing radar technologies for autonomous vehicles, addressing critical challenges such as sensor redundancy and data processing efficiency.23

