Andreas leads the Centre’s creative strategy. He is responsible for the development of digital content, a brand strategy, and relationships with academic researchers, clinicians, and industry partners.
Andreas studied Biology, Evolutionary Biology, and Biological Anthropology, in which he is currently pursuing a PhD.
He is fascinated by the intersection of science and communication, and works on making the transformation of healthcare through Ai and machine learning accessible through the outreach of CCAIM.
Miha acts as intermediary between all parties involved in CCAIM. She oversees the development, delivery and evaluation of the Centre’s projects.
She is passionate about helping people connect to achieve the best possible outcome and impact for CCAIM.
Miha has a background in Economics and has worked in variety of finance roles, ranging from trading to project management.
Evgeny is one of the centre’s research engineers, and has been a part-time PhD student at the van der Schaar lab since 2021. His educational background is Natural Sciences at the University of Cambridge, followed by postgraduate study in Computer Science at University of Southampton.
Evgeny was an AI Resident at Microsoft Research Cambridge before joining the lab, where he worked on projects covering meta-learning and reinforcement learning as applied to recommender systems. He also has experience in computational finance, having worked in a fintech start-up and commodities trading.
Evgeny facilitates turning the lab’s research code into robust production quality code, making it more scalable, applying software engineering best practices; he also collaborates with our PhD students on some research topics.
He is particularly interested in working on AutoML and time-series modelling, as well as machine learning for time series, and synthetic data.
Rob is one of our research engineers since joining in 2022. His educational background is Physical Natural Sciences at the University of Cambridge.
Rob worked for five years at a medical software company before joining us. In his roles of Senior Data Scientist and Data Engineer, he focussed on data extraction from scientific literature, and it was here he became excited by applying Machine Learning methods in medical contexts.
Rob works to make research code robust, ensuring software engineering best practices are applied. He also creates user interfaces that demonstrate the research methods to make sure that their power can be understood by as many people as possible.
He has so far shown a great interest in the interpretability of Machine Learning methods.