Artificial Intelligence
Machine learning, predictive intelligence, knowledge representation and intelligent decision systems.
Technology leadership
Technology leadership.
Bridging scientific research and operational engineering.
Co-Founder & Development Manager
Dr Mohammad Rafiq Swash
Dr Mohammad Rafiq Swash brings a combination of advanced technology research and engineering leadership, translating deep technology into industrial application. His expertise lies at the intersection of machine intelligence and the physical world—developing systems that perceive complex environments and operate within real-world infrastructure.
Understand the problem. Develop the technology. Validate the system. Scale with evidence.
Research record
Scientific foundation.
These figures are attributed to Dr Swash in the official QAVEUM profile, reflecting his academic and publication record.
- Peer-reviewed publications
- 70+
- Doctoral researchers supervised
- 20+
- Postgraduate and undergraduate students supervised
- 200+
Expertise architecture
Connected expertise.
A multi-disciplinary approach to physical AI and autonomous systems.
Autonomous Systems
Mobile robotics, autonomous technologies and intelligent machines operating within dynamic physical environments.
Computer Vision
Machine perception, image understanding, object recognition and depth estimation for interpreting visual environments.
Multi-Sensor Fusion
Combining cameras, LiDAR and other sensing technologies to represent complex physical environments more reliably.
Physical & Embodied AI
Connecting artificial intelligence with machines and systems that sense, understand and act within the physical world.
Autonomous Digital Twins
Combining digital representations with operational information, artificial intelligence and decision support.
Advanced 3D & Spatial Intelligence
Three-dimensional imaging, reconstruction, spatial understanding, sensing and positioning technologies.
Intelligent Industrial Systems
Applying artificial intelligence, sensing, computer vision and autonomous technologies to industrial and logistics environments.
Career pathway
From research to deployment.
A progression from advanced machine perception to intelligent industrial applications.
- 01
Research foundation
Scientific research, engineering and practical technology development form the foundation.
- 02
Technology evolution
Work progresses from advanced imaging and machine perception into artificial intelligence, autonomous systems, robotics and intelligent industrial applications.
- 03
Industrial application
Academic work is accompanied by entrepreneurial experience translating AI and autonomous technologies into commercial applications, particularly in global industrial logistics.
- 04
QAVEUM contribution
This experience supports technology intended to understand and interact with the physical infrastructure that moves economies.
Credentials
Academic and professional record.
Academic foundation
- • PhD in Holoscopic 3D Imaging, Processing & Display Systems
- • First-Class BEng in Computer Systems Engineering
- • Lead, Holoscopic 3D Research Group at Brunel University London
- • Former Visiting Professor at the Chinese Academy of Sciences
Executive education
- • Executive Programme in Venture Finance, Saïd Business School, Oxford
- • High Impact Leadership Programme, Institute for Sustainability Leadership, Cambridge
Selected recognition
- • Chancellor's Prize
- • Brunel Medal for Outstanding Achievement
- • Vice Chancellor's Doctoral Research Prize
- • IEEE Broadcast Technology Society Best Paper Award
Selected research themes
Research direction.
Emerging systems in machine intelligence and spatial understanding.
- Advanced imaging
- Machine perception
- Embodied AI
- Robotics
- Robotics foundation models
- Vision-language-action systems
- Autonomous digital twins
- Reliable autonomy