معرفی
Cangxiong Chen is a Researcher at the Institute for Mathematical Innovation (IMI), University of Bath. Prior to this, he worked in startups in Cambridge, UK, and Beijing, China, applying machine learning and statistical methods to consumer behavior modeling, pricing strategies, and recommendation systems. He holds a PhD in Number Theory from the University of Cambridge (2017), an MPhil in Mathematics from the University of Hong Kong (2011), and a Bachelor’s degree from the same institution. His research focuses on advancing the mathematics of machine learning, particularly in designing algorithms with privacy, fairness, robustness, and generalisability. He explores topics like differential privacy in image/video processing, training data leakage prevention, and collective intelligence systems.
Education:
• Doctor of Philosophy in Mathematics, University of Cambridge (2011–2016)
• Master of Philosophy in Mathematics, University of Hong Kong (2009–2011)
• Bachelor’s degree in Mathematics, University of Hong Kong
His research interests span the theoretical foundations of machine learning, with a focus on privacy-preserving techniques such as differential privacy. He investigates robust algorithms for image and video processing, leveraging compressed sensing and dynamical systems. Additionally, he contributes to collective intelligence research, exploring how AI can enhance large-scale problem-solving and interdisciplinary collaboration. His work bridges pure mathematics (e.g., number theory) with applied domains like cybersecurity and social computing.
In his recent projects, he has analyzed vulnerabilities in models like CLIP, studied leakage via gradients in neural networks, and developed strategies for AI-driven collective intelligence. These studies highlight his commitment to advancing both ML theory and its practical applications in diverse fields.
Grants and Collaborations: Chen has contributed to seven research projects, including those funded by UKRI, EPSRC, and the Advanced Research and Inventions Agency. Notable roles include Researcher Co-Investigator (CoI) in projects like 'A New Analytical Framework for Dexterous Soft Robotic Manipulators' and 'AI for Collective Intelligence (AI4CI)’. He collaborates with interdisciplinary teams on topics ranging from soft robotics to policy strategy, emphasizing real-world impact through UK and international partnerships.
Labs and Teams: Affiliated with the Institute for Mathematical Innovation at the University of Bath, he engages with collaborative teams across multiple disciplines, including artificial intelligence, data science, and mathematical modeling. His work often intersects with industry needs, as evidenced by his startup experience and ongoing projects in applied ML.
