Bernhard Kainz

I am Reader (= US/EU Associate Professor++) in the Department of Computing at Imperial College London where I lead the human-in-the-loop computing group and co-lead the biomedical image analysis research group (BioMedIA) and I am Professor at Friedrich-Alexander-University Erlangen-Nuremberg where I head the Image Data Exploration and Analysis Lab (IDEA Lab). We are a post-pandemic, borderless research group, across nations and institutions.

Our research is about intelligent algorithms in healthcare, especially Medical Imaging. We are working on self-driving medical image acquisition that can guide human operators in real-time during diagnostics. Artificial Intelligence is currently used as a blanket term to describe research in these areas.

Our current research questions are:

• Can we democratize rare healthcare expertise through Machine Learning, providing guidance in real-time applications and second reader expertise in retrospective analysis?
• Can we develop normative learning from large populations, integrating imaging, patient records and omics, leading to data analysis that mimics human decision making?
• Can we provide human interpretability of machine decision making to support the ‘right for explanation’ in healthcare?

My teaching is focused on real-time computing, Machine Learning, Image Analysis, Computer Graphics and Visualisation.

I am a scientific advisor for ThinkSono and Cydar Medical.