Data Champions Search

I am a PhD student in engineering, in the machine learning group. I am passionate about using version control for data/code management, and various kinds of virtual lab notebooks.

My background is neuropsychology, and later, computational neuroscience. During my studies, I developed strong skills in applied data science and machine learning, as well as fundamental knowledge of neural computation. Currently, I am based in the Cambridge Centre for Neuropsychiatric Research, where our team is working on biomarker discovery for neuropsychiatric disorders, as well as on developing algorithms for more data-informed diagnostics in mental healthcare.

Dr. Pingfan Song is a senior research associate at the Machine Learning group in University of Cambridge. He is endorsed under the Global Talent by UK Research and Innovation (UKRI) in recognition of his critical contributions.  
   He has been working on trustworthy machine learning which aims to advance work on key technical underpinnings of interpretability/transparency, fairness, and robustness of machine learning systems, and to develop timely key applications in real world healthcare settings, such as medical imaging diagnosis systems. In addition to machine learning, he is also a professional in image processing, sparse modeling and sampling theory. His research has been applied to multi-disciplinary fields such as medical imaging, biological imaging, and other computational imaging tasks and inverse problems.  
   He is a STEM ambassador in UK and a mentor of in2scienceUK where he provides free teaching, career guidance and advice for A-level students in order to empower students from disadvantaged backgrounds to achieve their potential and progress to STEM and research careers. He is also Co-president of London PhD Network (LPN), a non-profit academic association promoting interdisciplinary communication.