Our Team

Heba Sailem

Heba Sailem

Head of Biomedical Data Science

Heba Sailem

I am a Senior Lecturer at the School of Cancer and Pharmaceutical Sciences at King's College London. Before joining King's, I worked at the Institute of Biomedical Engineering and Big Data Institute at the University of Oxford as a Sir Henry Wellcome Research Fellow and Corpus Christi Junior Research Fellow. At Oxford I developed several approaches to tackle challenges in inferring gene function from phenotypic data.

I did my PhD at the Institute of Cancer Research in London where I developed methods for integrating phenotypic data with gene expression, modelling of the relationship between cell signalling and its context, and modelling the dynamics of cell morphogenesis. I have a BSc in Computer Information Systems and MSc in Data Warehousing and Data Mining.

I am passionate about data visualisation and communicating science through quantitative art. I devised PhenoPlot and ShapoGraphy (www.shapography.com). These methods facilitate the interpretation of high-dimensional data by generating pictorial representations of cells based on hundreds to thousands of measurements.

Danny Wu

PhD student

Danny is interested in developing weakly supervised approaches for classifying biomedical images. Recognizing the success of transformers in large language models, Danny aims to leverage their capabilities in processing spatial data like histopathological images.

Ryan Ma

Research assistant

Ryan is exploring the application of graph neural networks to create highly accurate and efficient deep models for classifying cellular image data. He also is developing a light-weight data visualisation web app that enables researchers and scientists to effortlessly explore datasets

Lakshmi Konduri

Research assistant

Lakshmi is currently investigating topological approaches for profiling image data.

Osama Mustafa

PhD Student

Osama is interested in developing Generative AI approaches.

Shiv Jamdade

Research assistant

Shiv will be working on developing AI approaches for drug discovery.