Data Champions Search

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.

I am bioinformatician who has been working in Cancer Research UK Cambridge Institute since 2017. I have a background in biology and have experience with HPC, version control, R and python, and confidential data. I work with big volumes of cancer patient data on a daily basis.

Additional areas of expertise:

High Performance Computing (HPC) - cluster.

Swati is a Research Assistant in the Department of Engineering at the University of Cambridge. Currently, her research focuses primarily on understanding the temporal structure of pain through behavioral assessment of chronic pain patients. In addition to her research, she actively participates in mentorship initiatives such as Google’s WomenTechmaker Program. Prior to joining Nox lab, she worked with collaborators from Mayo Clinic, Oxford University, and Accenture Research Lab.