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Department of Computer Science and Technology

  • PhD Student

I am a PhD student in the Computing department under the supervision of Prof Mateja Jamnik.


My research is on Multi-Modal and Explainable Machine Learning on Biomedical Data, where I am interested in the following topics: 

  • Multi-modal data fusion, especially looking at ways to improve early fusion models
  • Explainability of multi-modal pipelines
  • Looking at applications in digital pathology, radiology, spatial transcriptomics, and precision medicine
  • Happy to explore any problem that deals with image, tabular, and graph data

I am very lucky to be funded by the Gates Cambridge Trust to conduct this research and work with many great people in the department along the way. 


I have capacity to supervise two MPhil/Part III students as a co-supervisor alongside Prof. Mateja Jamnik each year. You can find project descriptions here (you'll need a Raven login to view). If you want to propose your own project and think that my background is suitable for this, feel free to send me an email. 

I am also involved in teaching the following undergraduate and postgraduate modules: 

  • Multi-Modal Machine Learning (part of Advanced Topics in Machine Learning): Course Author
  • Scientific Computing: Teaching Assistant
  • Machine Learning & Real-World Data: Teaching Assistant


I grew up in the beautiful city of Hamburg in Germany and moved to the UK after high school for my undergraduate degree at the London School of Economics. About a year into my time at LSE, I realised that I was more interested in mathematics & statistics than the economics aspects of my degree, which eventually led me to self-educate myself in Computer Science on the side. I then did a Master's in Computer Science at Imperial College London, where I focussed on various disciplines ranging from Cybersecurity to Natural Language Processing. I really enjoyed Natural Language Processing and Machine Learning more generally and started working as a Senior Data Scientist for the Boston Consulting Group for a few years. At BCG, I primarily worked on drug yield optimisation of Pharmaceutical API production as well as various other interesting modelling challenges in the pharmaceutical industry, travel & tourism industry, the public sector, and even the dating app market. Working alongside chemical engineers on pharma production sites originally piqued my interest in bioinformatics and my current research is an evolution of this (after many, many iterations). 

Professional Activities

  • Scientific Advisor, Creator Fund, 2022-present
  • Senior Data Scientist, Boston Consulting Group, 2019-2021
  • Fixed Income Summer Intern, PIMCO, 2016


Book chapters

  • Hemker, K., Shams, Z. and Jamnik, M., 2023. CGXplain: Rule-Based Deep Neural Network Explanations Using Dual Linear Programs
    Doi: 10.1007/978-3-031-39539-0_6
  • Conference proceedings

  • Rizos, G., Hemker, K. and Schuller, B., 2019. Augment to Prevent Proceedings of the 28th ACM International Conference on Information and Knowledge Management,
  • Contact Details