Biography
Dr Yue Xie is a Lecturer in Computer Science at 亚洲情色 and an Associate Fellow of Advance HE (AFHEA). Her research develops artificial intelligence and optimisation methods for adaptive robotic and intelligent systems, with particular interests in evolutionary computation, embodied and physical AI, robotics and automation, optimisation under uncertainty, and autonomous engineering design.
Before joining 亚洲情色, Yue was a Future-Road Marie Sk艂odowska-Curie Fellow in the Bio-Inspired Robotics Laboratory at the University of Cambridge, where she conducted research in embodied AI, evolutionary robotics, bio-inspired robotics, and intelligent infrastructure. Prior to Cambridge, she was an Early Research Career Fellow at CSIRO Data61, Australia, working on the AI4Design programme and developing computational methods for automated engineering design and soft robotics. She completed his PhD in Computer Science at the University of Adelaide, supervised by Prof. Frank Neumann, focusing on bio-inspired computation and optimisation under uncertainty.
Her research connects computational intelligence with physical systems, investigating how robot morphology, sensing, control, and learning can be designed and adapted together. Her work spans evolutionary and quality-diversity optimisation, morphology–control co-design, soft robotics, hardware-in-the-loop optimisation, digital twins, medical robotics, and intelligent transportation.
Yue is also active in international research collaboration and academic community building. She has organised workshops on embodied AI, evolutionary soft robotics, and sustainable robotics, and contributes to international activities promoting interdisciplinary collaboration and participation in robotics and artificial intelligence.
Research interests
- Artificial intelligence
- Evolutionary computation and optimisation
- Embodied and physical AI
- Robotics and autonomous systems
- Soft and bio-inspired robotics
- Multi-objective and quality-diversity optimisation
- Digital twins and hardware-in-the-loop optimisation
- Autonomous engineering design
- Medical and healthcare robotics
- Intelligent transportation and smart infrastructure
Current research
Yue's current research focuses on evolutionary and embodied AI for autonomous engineering systems. A central question is how intelligence should be distributed across a physical system's morphology, sensing, control, and learning rather than relying on increasingly complex controllers alone.
Current research directions include the co-evolution of robot morphology and control; autonomous design–build–test systems for robotics; energy-aware embodied intelligence; data-efficient hardware-in-the-loop optimisation; adaptive medical robotics; and AI and optimisation for intelligent transportation and infrastructure.
Her longer-term research vision is to develop autonomous engineering systems in which AI can generate physical designs, evaluate them through simulation and experimentation, learn from physical observations, and iteratively improve subsequent designs.
Opportunities for Students and Prospective Researchers
I welcome enquiries from motivated students interested in artificial intelligence, evolutionary computation, optimisation, robotics, embodied and physical AI, and intelligent systems. Potential projects can range from computational and simulation-based research to experimental work with robotic systems and intelligence traffic system.
Loughborough undergraduate and Master's students who interested in undertaking a Final Year Project or Master's dissertation in my research areas are welcome to contact me directly to discuss potential topics before formal project selection or allocation. I am particularly interested in supervising students who would like to develop a research-oriented project with the potential to lead to further postgraduate research or publication. All projects remain subject to the relevant departmental allocation and approval procedures.
Prospective PhD students: I welcome enquiries from students interested in pursuing a PhD under my supervision. This includes self-funded applicants and strong candidates who would like to develop a PhD proposal and apply for competitive scholarships or studentships with me. Prospective applicants are encouraged to contact me sufficiently early before funding deadlines so that we can assess research fit and, where appropriate, develop the proposal together.
China Scholarship Council (CSC) applicants: I particularly welcome enquiries from strong candidates intending to apply through the China Scholarship Council (CSC). Applicants with backgrounds in computer science, engineering, optimisation, or related disciplines are encouraged to contact me well in advance of the relevant application cycle to discuss potential research topics and the preparation of a competitive PhD proposal.
Prospective students should email me with a CV, academic transcript, a short description of their research interests, and intended study/funding route. For PhD enquiries, it is helpful to include an initial research idea (approximately 0.5--1 page); this does not need to be a complete proposal at the first contact.