Wenjie Ruan

Dr. Wenjie Ruan is a Senior Lecturer in Data Science at the Department of Computer Science, College of Engineering, Mathematics and Physical Sciences, University of Exeter, a Russell Group university. He is also the Co-Lead of the Trustworthy AI Theme at IDSAI. Previously, he was a Lecturer at Lancaster University and a Postdoctoral Researcher at the University of Oxford, funded by EPSRC. He holds a PhD from the University of Adelaide and conducted research at Tsinghua University.

• University: University of Exeter
• School: College of Engineering, Mathematics and Physical Sciences
• Department: Department of Computer Science
• Position: Senior Lecturer (~Associate Professor)
• Research Theme: Co-Lead, Trustworthy AI at IDSAI

His primary research interests lie in robustness, safety, and interpretability of deep learning models, with applications in health data analytics and human-centred computing. He focuses on adversarial robustness, verification, testing, and explainable AI, particularly in safety-critical domains such as healthcare and autonomous systems.

The recent publications reflect a strong trend in trustworthy machine learning, with emphasis on adversarial robustness (e.g., Vision Transformers, 3D models), verification techniques, and healthcare applications (e.g., COVID-19 severity prediction, EMR data analysis). His work often includes open-sourced tools like GUAP, DeepConcolic, and DeepGO, highlighting a commitment to reproducibility and practical impact.

• Dean's Commendation for Doctoral Thesis Excellence, University of Adelaide (2017)
• Scholarship for Outstanding PhD Students Abroad, Chinese Government (2017)
• Best Student Paper, ADMA 2016
• Best Poster Award, ACM IOT & Cloud Computing Workshop (2016)
• PRF Project Grant (£180K) from ORCA Hub
• Subcontract from DSTL via Liverpool University (£15K)

Dr. Ruan has actively advised numerous PhD and Master’s students, many of whom have achieved distinctions or secured prestigious positions. He has been involved in significant research grants, including projects on accountable AI in robotics and AI test coverage metrics for defense applications. His leadership in the ORCA-funded AELARS project demonstrates his role in guiding emerging researchers and shaping future work in trustworthy AI.

He leads a dynamic research group and has hosted postdoctoral researchers like Dr. Syed Yuns. His team focuses on developing robust, verifiable, and interpretable AI systems, particularly in digital health and autonomous robotics. Collaborations with institutions such as Oxford, Liverpool, and Imperial College London further enrich the lab’s research ecosystem.