QMUL Centre for Advanced Robotics News

International Women in Engineering Day: meet Mona Jaber and Valentina Donzella.

Wed, 17 Jun 2026 23:00:00 +0100

In celebration of International Women in Engineering Day, we highlight the innovative research of Mona Jaber and Valentina Donzella. Dr Mona Jaber is Head of the Centre for Networks, Communications and Systems. As a child, Mona was fascinated by how engineering could solve real-world problems and she knew then that she wanted to be an engineer. That early curiosity has grown into a lifelong passion that now drives her research in artificial intelligence and Internet of Things technologies. In this video, Mona discusses her research and explains how the Internet of Things—networks of connected devices and sensors—can help create healthier, more sustainable cities by improving the way we manage resources, services and urban infrastructure. Professor Valentina Donzella is a member of the Centre for Intelligent Transport and the Deputy Head of the Centre for Advanced Robotics. Her research focuses on making intelligent technologies, such as robots and self-driving vehicles, safer and more reliable. She studies how sensors—including cameras, radar, thermal cameras and LiDAR—collect information about the world, and how factors such as bad weather, poor visibility or busy environments can affect the quality of that information. Valentina develops new methods to improve and combine data from different sensors, helping artificial intelligence systems make better decisions in real-world situations. She is particularly interested in using computer simulations and AI-generated data to test and train intelligent systems, as well as developing ways to assess data quality and system performance. Her work also explores how intelligent systems can operate safely using less data, helping to make future transport and robotic technologies both safer and more sustainable.

Queen Mary Experts Chosen to Help Drive Forward UK Science Policy in Prestigious Government ...

Wed, 25 Feb 2026 00:00:00 +0100

Two senior academics from Queen Mary University of London — Professor Akram Alomainy from the School of Electronic Engineering and Computer Science (EECS) and Professor Jan Mol from the School of Physical and Chemical Sciences — have been selected as Fellows in the highly competitive Expert Exchange Programme led by the Department for Science Innovation and Technology DSIT. Professor Akram Alomainy and Professor Jan Mol were appointed following a rigorous national selection process, securing two of only 17 Fellowship places awarded across the UK. The Fellowships are part of His Majesty's Government's drive to embed leading expertise directly into policy making. Professor Alomainy will work with the Advanced Connectivity Technology team within Department for Science, Innovation and Technology, contributing his internationally recognised expertise in antennas, electromagnetics and wireless technologies to support future connectivity strategy. His work will focus on translating cutting edge research into practical policy insight for the UK's digital and communications ambitions in 6G and beyond building transformative landscape for next generation technologies. Professor Mol will join the Office for Quantum at DSIT, advising on policy related to quantum science and technology. Drawing on his extensive background in quantum materials and devices, his role will support the development of national capability in a field that is central to the UK's long term science and innovation strategy. Speaking about his appointment, Professor Alomainy said: "I am delighted and honoured to be selected for this Fellowship. Working closely with colleagues in DSIT on advanced connectivity is a unique opportunity to help shape national policy using evidence from frontier research. I see this as a vital bridge between academia and government, and I am excited to contribute to the UK's technology future." Professor Mol added: "It is a real privilege to be chosen as one of only 17 Fellows nationally. Quantum technologies are moving rapidly from the lab into real world applications, and I look forward to supporting the Office for Quantum in developing informed and effective policy that strengthens the UK's global position." The DSIT Fellowship places leading researchers into government for 12 months, enabling direct collaboration with civil servants while strengthening mutual understanding between academia and policy. The selection of Professors Alomainy and Mol highlights the strength of Queen Mary University of London's research and its growing role in informing national science and technology policy. Their appointments reinforce the importance of expert input into government decision making at a time when advanced connectivity and quantum technologies are critical to the UK's economic growth, security and global competitiveness.

New Robot Cafe' launched by the Centre for Advanced Robotics

Tue, 17 Feb 2026 00:00:00 +0100

The Centre for Advanced Robotics has just launched a new initiative: the Robot Cafe'. Open to all Queen Mary Robotics students as well as members of the Electronics Society, the Robot Café provides an opportunity to deepen technical knowledge, experiment with tools and technologies, and connect with like-minded peers in a welcoming environment. The Robot Cafe' opened on Wednesday 11th Februrary with an interactive session on OpenCV (Open Computer Vision). The session introduced students to the fundamentals of computer vision and practical implementation in Python and received a very positive feedback from the students attending in person and online. The Robot Café will continue every Wednesday from 3pm to 6pm in Room 0.14, IQ East Court, running until the end of the semester. For more details on the upcoming session see here.

Prof Althoefer publishes new research on using fuzzy reinforcement learning in endovascular robotics

Sun, 07 Sep 2025 23:00:00 +0100

Jointly with roboticists, Tianliang Yao, Yueqi Xu, Haoyu Wang, Xihe Qiu and Peng Qi, Professor Kaspar Althoefer has published a paper on 'Multi-Agent Fuzzy Reinforcement Learning with Large Language Models for Cooperative Navigation of Endovascular Robotics' in IEEE Transactions on Fuzzy Systems. The paper summarises recent work on context-aware, autonomous navigation of guidewires and catheters in complex vascular systems. Leveraging fuzzy reinforcement learning (a more human-like logic allowing for vagueness or nuance), the group's approach ensures efficiency and precision, surpassing traditional methods in 3D simulators. Endovascular interventions require precise, cooperative control of multiple instruments, such as guidewires and catheters, to navigate complex vascular anatomies. Current robotic systems, reliant on leader-follower control, depend heavily on operator expertise and lack intelligence. Learning-based methods, often limited to single-instrument control, fall short in complex clinical scenarios requiring multi-instrument coordination. This study proposes a Multi-Agent Fuzzy Reinforcement Learning (MAFRL) framework, guided by large language models (LLMs), for task-level autonomous, cooperative navigation in endovascular robotics. LLMs provide procedural priors and context-aware policy guidance, enabling adaptive decision-making for collaborative guidewire and catheter agents. Central to the framework, fuzzy reinforcement learning mitigates LLM-induced uncertainties by adaptively embedding clinical constraints into reward functions, ensuring strict adherence to procedural safety and precise alignment with the complexities of real-world endovascular interventions. Validated in a 3D vascular simulation, this approach achieves superior navigation performance and procedural efficiency compared to conventional methods, underscoring the transformative potential of fuzzy reinforcement learning in advancing LLM-guided MARL for endovascular robotics.