I am a group leader in the Cellular Genetics programme at the end of April 2024. I am a European Laboratory for Learning and Intelligent Systems (ELLIS) member, and an associate faculty member at the Cambridge Centre for AI in Medicine at the University of Cambridge. My primary research goal is to leverage artificial intelligence and advanced experimental techniques to engineer cells and modulate their response to disease and perturbations. I envision that my team's work will lay the foundations for future therapies using cell engineering.

Leveraging cutting-edge Machine Learning and high-throughput genomics

My team and I will seek to leverage artificial intelligence (AI) and machine learning (ML) models to capture the real-world behaviour of all the cells within individual human organs. Our ultimate goal is to generate the knowledge required to build computer-based models that are so realistic that they can model the responses of cells caused by diseases, genetic disorders, and environmental factors or treatments. This will enable new engineering of new cells and therapies that intervene at the cellular level to enhance the cells’ resistance to disease, or even reverse it, by precisely modulating cellular behaviours.

Training these ML/AI models requires massive high-resolution genomics and phenotypic data sets. To achieve this, we will combine High-Throughput Genomics, Imaging, and large-scale perturbation experiments to engineer or reverse cells to capture how genomic changes affect cellular behaviour.

About me

I am passionate about translating my research to aid patients by focusing on designing more efficient therapies and facilitating effective drug discovery and design. I will work across the pharmaceutical industry and academia to support the transition of my and my future team’s discoveries from the laboratory bench to the patient bedside.

My approach

I am a computational biologist and a computer and machine learning scientist. I studied for my PhD in Munich and have worked in several AI and Biotech companies.

My experience of working across fields and types of research has shown me the combined value of many different experiences and viewpoints. For this reason, I will be creating a team that is highly interdisciplinary in its research and expertise – ranging from wet lab techniques to data analysis and machine learning.


My publications

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