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Dr. Ramsey Faragher is a Senior Research Associate at the Computer Laboratory , University of Cambridge, and a Bye-Fellow at Queens' College. His work focuses on infrastructure-free indoor positioning systems, sensor fusion, and improvements to smartphone sensing capabilities. Academic Affiliation : University of Cambridge (Computer Laboratory) Professional Roles : Bye-Fellow at Queens' College, Senior Research Associate His research spans multiple disciplines within computer science and engineering, emphasizing innovative navigation solutions and signal processing techniques. Key areas include GNSS robustness, wireless security, and machine learning applications for positioning systems. Recent publications highlight advancements in supercorrelation for automotive GNSS, sensor data calibration, and motion-compensated signal processing. Articles frequently address challenges such as spoofing mitigation, urban navigation, and infrastructure-free localization. Scientific Recognition Fellow of the Royal Institute of Navigation Chartered Physicist (CPhys)

• Infrastructure-free Indoor Positioning
• Simultaneous Localisation and Mapping (SLAM)
• Smartphone Sensing
• +9 more

Dr. Peter Vial is a Senior Lecturer at the School of Electrical, Computer and Telecommunications Engineering, University of Wollongong. He holds a PhD in Electrical Engineering and has over three decades of experience in academia and industry. His academic journey includes a Bachelor's (1987), Master's (1997), and PhD (2009) from the University of Wollongong. Before academia, he worked at BHP Steel (1981-1991) and transitioned into teaching roles from 1992, becoming a Lecturer in 2004 and Senior Lecturer in 2022. Research Interests: Dr. Vial’s work focuses on wireless communication systems, including MIMO, spread spectrum, and ultra-wideband (UWB) technologies. He also explores signal processing applications in medical imaging (e.g., capsule endoscopy), steganography, energy harvesting, and robotics. His research integrates machine learning and embedded systems for practical solutions in healthcare, telecommunications, and sensor networks. Teaching & Supervision: Dr. Vial teaches courses in telecommunications, digital signal processing, and electronics. He has led laboratory development in embedded systems and supervised over 15 postgraduate students, including current PhD candidates in Delay Tolerant Networks (DTN), 60GHz Ad Hoc networks, and UWB channel measurements. His supervision spans topics like AI-driven sign language recognition, steganography, and energy-efficient generator design. Grants & Funding: He led an internal grant (2008-2009) developing an immersive learning platform for microcontroller education. His research has been supported by institutional funding, with outputs published in journals like Neurocomputing , Signal Processing , and IEEE Sensors . Labs & Teams: Dr. Vial has developed engineering laboratories in embedded Internet systems, telecommunications, and digital signal processing. He collaborates with industry partners and interdisciplinary teams on projects combining hardware/software systems for healthcare, energy, and robotics.

• Wireless Communications
• Signal Processing
• Image Steganography
• +5 more

Dr Alex Rast is a Senior Lecturer in Computing within the School of Engineering, Computing and Mathematics at Oxford Brookes University , where he also serves as Third-Year Tutor for all computing programmes. His career spans academic posts at the Universities of Manchester and Southampton and industry experience at wireless start-up Inficom, Inc. Education & Career Path A-level studies sparked lifelong interest in neural networks and neuromorphic hardware. Post-doctoral research at University of Manchester on cognitive robotics and neuromorphic chips. Research fellow at University of Southampton on large-scale parallel event-driven systems. Industry stint at Inficom working on control processors and modulation theory. Joined Oxford Brookes University, rising to Senior Lecturer while leading multiple research initiatives. Research Focus Dr Rast’s research integrates event-driven vision sensors with neuromorphic cognitive processors to create fully integrated autonomous neurorobotic systems capable of operating in unstructured natural environments. Core themes include: Real-time perception and SLAM for autonomous vehicles and racing robots. Large-scale spiking neural network models for learning and decision-making. Probabilistic temporal reasoning under uncertainty. Ethical decision-making and reinforcement learning for responsible AI agents. Novel applications such as neural models for fine-flavour cacao and chocolate assessment. Funding & Projects Knowledge Transfer Partnership (KTP) with Supponor on advanced scene infilling systems. CLAIMOR (Co-I; British Academy, Apr–Nov 2025) developing comprehensive large AI models for mobile robotics. Active consultancy to the Oxford Brookes Racing (OBR) Autonomous racing team on perception and SLAM. Research Groups & Labs Visual Artificial Intelligence Laboratory (VAIL) Autonomous Driving and Intelligent Transport (ADIT) group Machine Learning and Robotics Group (MLR) Artificial Intelligence, Data Analysis and Systems (AIDAS) Institute Institute for Ethical AI collaboration on ethical agents Teaching & Supervision Dr Rast is Third-Year Tutor for all computing programmes and teaches core AI and robotics modules: Artificial Intelligence (BSc, MSci, MSc), Cognitive Robotics, Autonomous Intelligent Systems, and Artificial Intelligence Systems Engineering. He supervises final-year projects and postgraduate research students in neuromorphic computing and autonomous systems.

• Neuromorphic computing
• Artificial Intelligence
• Autonomous robotics
• +6 more

Dr. Bashar Saleem Abbas Alsadik is an Assistant Professor in the Department of Earth Observation Science at the Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, the Netherlands. He earned his PhD in 2014 from the same university with research on close-range photogrammetry for 3-D heritage modelling and holds a B.Sc. in Surveying Engineering (University of Baghdad, 1995). Before joining ITC he served as a faculty member at the University of Baghdad (1999-2014) and later as R&D Specialist Engineer at CycloMedia Technology (2015-2019). Education: PhD, University of Twente, 2014 – Guided Close-range Photogrammetry for 3D Modeling of Cultural Heritage Sites B.Sc., University of Baghdad, 1995 – Surveying Engineering Research interests centre on photogrammetry, geometric computer vision, UAV-based autonomous navigation and mapping exploiting SLAM and Next-Best-View methodologies, mobile mapping & LiDAR systems, adjustment computations, and heritage 3-D documentation. He actively develops educational material for ITC’s UAV centre and contributes to capacity-building projects. His publication record (h-index 11, 371 citations) demonstrates a clear trajectory from cultural-heritage photogrammetry toward real-time UAV autonomy, safety-critical infrastructure monitoring (e.g., Mosul dam), and multi-sensor geospatial datasets, reflecting interdisciplinary integration of computer vision, geodesy and robotics. Professional service: member of ISPRS, CIPA and the Iraqi Engineers Syndicate; reviewer for leading journals such as ISPRS J., Remote Sensing, IEEE T-GRS, Drones, Journal of Cultural Heritage, Photogrammetric Record, and several conferences.

• Photogrammetry
• Geometric computer vision
• UAV autonomous navigation and mapping
• +8 more

Prof Jochen Trumpf is a Professor in the School of Engineering at the Australian National University (ANU). He holds an ORCID identifier and has an h-index of 22 with over 2,500 citations. His research focuses on control theory, observer theory, optimization on manifolds, and applications in robotics, computer vision, and wireless communication. He completed his PhD in Mathematics at the University of Würzburg (2002) and held postdoctoral positions at Ben-Gurion University of the Negev and the University of Notre Dame prior to joining ANU in 2003. His research interests emphasize geometric approaches to nonlinear systems, including equivariant filter design, attitude estimation, and SLAM (Simultaneous Localization and Mapping). He has led or co-investigated multiple projects, including the National Facility for Electricity Grid Security and Resilience Research (2023–2025) and studies on distributed collaborative localization and control. He has collaborated widely, with notable contributions to sensor fusion, inertial navigation, and observer-based control strategies. Prof Trumpf’s work integrates mathematical rigor with practical engineering challenges, with over 90 publications in peer-reviewed journals and conferences. His projects often involve cross-disciplinary teams addressing issues in autonomous systems, navigation, and sensor technology. Despite no explicit awards listed, his citation metrics and project leadership reflect significant academic impact. He supervises research students and has been involved in doctoral training programs, such as the Defence Staff PhD Agreement with Joyce Mau (2018–2022). His research extends to applications in robotics, environmental sensing, and smart grid systems, reflecting a balance between theoretical innovation and real-world problem-solving.

• Control Theory
• Observer Theory
• Optimization on Manifolds
• +3 more

Dr Ze Ji is Reader of Robotics and Autonomous Systems at Cardiff University’s School of Engineering, where he leads the Robotics and Autonomous Intelligent Machines (RAIM) group and directs the Robotics and Autonomous Systems Laboratory. He is Co-Investigator and theme leader for the ERDF-funded IROHMS research centre and holds a Royal Academy of Engineering Industrial Fellowship hosted by Spirent Communications Ltd. Education PhD in Engineering, Cardiff University (2007) – EU FP6 TAI-CHI project MSc, Cardiff University BEng, Cardiff University Research Interests Dr Ji’s research centres on Robot Perception And Learning (RoPAL) , spanning: Simultaneous localisation and mapping (SLAM) Deep reinforcement learning for navigation and manipulation Human-robot collaboration & digital-twin based fatigue management Vision, tactile sensing, and smart sensing systems Unmanned surface vehicles (USVs) and UAV coordination Physics-based differentiable simulation for elastoplastic material handling Publications Trend Since 2021 Dr Ji has authored >120 peer-reviewed papers. A dominant theme is mapless navigation via hierarchical and preference-based reinforcement learning for ground, aerial and surface robots. Parallel streams investigate human-centric manufacturing (digital twins for fatigue-aware assembly), vision-based tactile sensing, defect detection on steel, and orchard robotics (green-fruit segmentation), all underpinned by deep learning and rigorous real-world validation. Scientific Awards & Fellowships Royal Academy of Engineering Industrial Fellowship EU FP6 Best Exhibit Prize, Helsinki 2006 (TAI-CHI project) Fellow of the Higher Education Academy (FHEA) Grants & Centres Principal Investigator, EPSRC-funded differentiable physics project (2025) Co-Investigator, IROHMS (ERDF/WEFO) Industrial Fellowship with Spirent Communications Ltd Laboratory & Facilities Dr Ji manages the Robotics and Autonomous Systems Laboratory , housing two KUKA LBR iiwa robots, Robotnik Vogui+, three KUKA YouBots, TurtleBots, drones, advanced 3-D vision systems, and sensors. The lab has also produced two student-built USVs (unmanned surface vehicles) for maritime research.

• Robotics and Autonomous Systems
• Robot Perception and Learning (RoPAL)
• Simultaneous Localisation and Mapping (SLAM)
• +7 more