Valentina Donzella (Senior Member, IEEE) received the B.Sc. degree in electronics engineering from University of Pisa, the M.Sc. degree from Sant’Anna School of Advanced Studies, Pisa, and the Ph.D. degree in innovative technologies for information, communication, and perception engineering from Sant’Anna School of Advanced Studies.
She is currently full Professor in Sensors and Perception for Intelligent Systems; Head of SPRING group (Sensing and PeRception for INtelliGent Systems), School of Engineering and Materials Science, Queen Mary University of London. She was awarded a Royal Academy of Engineering Industrial Fellowship on camera sensors from 2020 to 2022, and currently leads the work package on perception sensor noise models within the four-year EU ROADVIEW project. Prof. Donzella is Full College Member of EPSRC, and a Senior Fellow of the Higher Education Academy.

Milan Lovric earned a diploma in Computing from the University of Zagreb (Croatia) in 2005 and completed his PhD in Finance at Erasmus University Rotterdam (the Netherlands) in 2011. Prior to joining Queen Mary University of London, he was as an Assistant Professor at the University of Warwick (UK). He has also held research appointments at several leading institutions, including University College London (Centre for Transport Studies), the University of Southampton (Transportation Research Group), MIT (Smart Centre in Singapore), the University of Oxford (Mathematical Institute and INET), the Santa Fe Institute, and Rotterdam School of Management. His research interests span agent‑based simulation, transport demand and supply modelling, and - more recently - automated mobility and sensor technologies.

Pak Hung Chan received a M.Eng. degree in mechanical engineering and a M.Sc degree in smart, connected and autonomous vehicles from the University of Warwick, Coventry, U.K., in 2018 and 2023 respectively. Since graduating, he has been working in the automated vehicles’ field, on various projects relating to perception sensors. He is currently at Queen Mary University of London, working on the EU ROADVIEW Project, on physics-based modelling of noise factors on automotive sensors, and has produced a framework to analyze noise factors and break them down to understand how the noise affects the output data. He has several publications with IEEE, including a review article in the IEEE JSTQE and effect of compression on perception in the IEEE T-ITS.

Boda Li is a Research Assistant in the School of Engineering and Materials Science at Queen Mary University of London, where he works on the Horizon Europe ROADVIEW project. He received the B.Sc. degree in Vehicle Engineering from Hunan University and the M.Sc. degrees in Sustainable Automotive Engineering and in Smart, Connected and Autonomous Vehicles from WMG, University of Warwick. He subsequently obtained the Ph.D. degree in Engineering from WMG, University of Warwick, where his research focused on automotive camera noise factor modelling and simulation for robust perception in autonomous driving. His research interests include automotive perception sensor data modelling, controllable scene generation, and closed‑loop training and testing for automated driving systems and mobile robotics. He is an Associate Fellow of the Higher Education Academy.

Jiangyin is a PhD researcher at the University of Warwick, where her doctoral work focuses on LiDAR perception and point cloud processing for autonomous vehicles. Her research investigates how noise impacts sensor performance and develops data reduction techniques to improve perception reliability, achieving high-precision results under challenging conditions. Building on her background with dual postgraduate training in smart connected systems and mechanical engineering, she integrates simulation, sensor fusion, and infrastructure considerations to address both technical and practical challenges of future mobility. Alongside her research, she has gained experience through teaching support and industry collaborations, contributing to the wider field of intelligent transportation.

Lintong is a PhD candidate at the University of Warwick, specialising in multi-agent decision making for automated driving systems. Her research focuses on developing decision-making frameworks that allow autonomous vehicles to operate safely and efficiently in complex traffic scenarios such as intersections and roundabouts. By combining reinforcement learning, social attention mechanisms, and advanced simulation environments, she investigates how multiple agents can cooperate, coordinate, and negotiate in dynamic driving conditions. With a background in mathematics and data analytics, she integrates strong quantitative skills with applied machine learning to tackle key challenges in intelligent transportation and the future of mobility.

Jocelyn (Yiting) is currently a visiting PhD student in the SPRING Group, Queen Mary University of London, and a Ph.D candidate in WMG, University of Warwick, UK. Prior to that, she completed a master's degree in Smart Connected and Autonomous Vehicles with distinction at the University of Warwick, UK. Her research interests are perception robustness, computer vision and sensor fusion.

Anima Rahman is a PhD researcher in Future Mobility Technologies at WMG, University of Warwick, with a focus on intelligent vehicle sensors and driver monitoring systems. Her research integrates machine learning to develop non-contact solutions for driver state detection. She has a background in Electronic and Electrical Engineering (BEng, University of Birmingham) and a postgraduate certificate in Automotive Technology, and specialises in automotive sensors, sensor fusion, machine intelligence, and human-technology interaction.

Hetian Wang is a PhD candidate in SPRING group. He received an MSc degree in Smart, Connected, and Autonomous Vehicles. He received BEng degrees in Mechanical Engineering (Automotive) and Vehicle Engineering from University of Birmingham, UK and Hefei University of Technology, China. His research focus covers image/video processing, camera compression, data transmission, camera simulation, and camera perception systems etc.

Zixiang Wei is currently a PhD candidate in University of Warwick. He worked as a research assistant at The Hong Kong University of Science and Technology, the VLIS LAB of Artificial Intelligence Thrust and Tongji University, Department of Electrical Engineering. His research interests lie in low-level computer vision tasks, and his current research primarily focuses on data degradation and impact on learning based model. He has served as reviewer of IEEE T-ITS, IEEE T-ASE, PeerJ Computer Science and IET Image Processing. His research interests also include bench press (PR 135kg), squat (PR 190kg) and deadlift (PR 235kg).

Yunruo is a PhD candidate at SPRING Group, WMG. He received his bachelor's degree in Electronic and Electrical Engineering from Liverpool John Moores University and his master's degree from the University of Bristol. His research foucs on image and video processing, image restoration, computer vision, image generative models, and thermal infrared images. Besides, he is also interested in badminton restringing and different rackets stringing methods.

Luyao Wang received her B.Eng. in Telecommunication Engineering from Beijing University of Posts and Telecommunications and her M.Sc. in Optical Communications and Signal Processing from the University of Bristol. Her research focuses on robust object detection for autonomous driving in adverse weather, with an emphasis on multi-modal sensor fusion across camera, LiDAR, and RADAR data.

Yufeng Zhang is a Ph.D. student in the school of Engineering and Materials Science at Queen Mary University of London. He received a BEng degree in Data Science and Big Data Technology with Contemporary Entrepreneurialism from Xi'an Jiaotong-Liverpool Univeristy and a MSc degree in Smart, Connect and Autonomous Vehicles from WMG, University of Warwick. His research interest includes deep learning, computer vision, domain adaptation and active learning.