My interest in research is the design of prediction models contributing to more reliable and trustworthy predictions in clinical contexts. This encompasses theoretical aspects of predictive modeling, e.g. generalizability, calibration, as well as practical aspects, e.g. deep architecture design and effective implementation. I am also interested in enabling health informatics research with information systems integrating various sources of data generated in hospital contexts.
My main project focuses on the development of graph-based prediction models to quantify the impact of genetic variants of drug transporter proteins. This project is part of an effort toward personalized medicine, ultimately aiming at a fast and reliable identification of suitable chemotherapeutic treatments for cancer patients based on their genetic profile.
I obtained my PhD under the supervision of Assoc. Prof. Saikat Chatterjee, in a collaborative project with Prof. Eric Herlenius at the department of Women's and Children's Health at Karolinska Institutet. My thesis is available online.
Link to my CV.