Kate Čevora MEng

Kate runs the firm’s operations from a practical standpoint and also brings deep machine-learning expertise to projects, especially in computer vision, which is the subject of her doctoral research. Her work covers a wide range of ML topics — from developing new reinforcement-learning algorithms to using Bayesian statistics to predict bacterial resistance. She also co-developed Rosa, a tool that helps remove bias from datasets.

Kate previously worked as a Senior Data Scientist at illumr, a specialist AI consultancy. Her doctoral research focuses on AI for medical image analysis; she is affiliated with the Data Science Institute and the Biomedical Image Analysis Lab at Imperial College London. She works in particular on domain generalisation and on fairness in deep learning for abdominal CT segmentation.

She holds an MEng in Information Science and Electronics from the University of Cambridge. Her studies included signal processing and communications, machine learning, and semiconductor physics.