Bernhard Kainz

Timeline

1. 2002–2011

   Degrees and a PhD at Graz

   He completes a BSc from 2002 to 2005 and an MSc from 2005 to 2007 at Graz University of Technology. From 2007 to 2011, he completes a PhD in medical visualization, volume graphics and GPU algorithms in Dieter Schmalstieg's team at Graz's Institute for Computer Graphics and Vision.

2. 2011–2015

   From Graz to Imperial

   From May 2011 to February 2013, he works as a Research Associate at the Institute for Computer Graphics and Vision at Graz University of Technology. In March 2013, he joins Imperial College London's Department of Computing as a Marie-Curie Fellow until April 2015.

3. 2015

   King's College and Imperial lectureship

   From May 2015 to October 2015, Kainz works as a Senior Research Fellow at ISBE at King's College London, where he continues as an Honorary Research Fellow from October 2015. In October 2015, he returns to Imperial College London's Department of Computing as a Lecturer in real-time computing.

4. 2017–2019

   SonoNet and medical imaging awards

   In 2017, he coauthors SonoNet, a convolutional neural network system for real-time automated detection of 13 fetal standard scan planes and localisation of fetal structures in freehand ultrasound, and wins the 2017 Multimodal Brain Tumor Segmentation Challenge (BraTS) with Kamnitsas and colleagues. In 2019, he shares the Imperial President's Award for Outstanding Research Team with Daniel Rueckert, Ben Glocker and Wenjia Bai.

5. Since 2021

   Professorship at FAU and Imperial readership

   In September 2021, he becomes Professor of Image Data Exploration and Analysis in the Department of Artificial Intelligence in Biomedical Engineering at FAU. From September 2021 to August 2024, he also serves as a Reader in Computing at Imperial College London.

6. 2022–2023

   MICCAI challenges and an ERC grant

   With Li and colleagues, he wins the 2022 MICCAI FETA challenge, followed in 2023 by the MICCAI MOOD challenge with Müller, Baugh and colleagues. In 2023, he receives a five-year, €2 million ERC Consolidator Grant to train AI tools to recognize healthy human tissue in medical images.

7. 2025

   Fetal biometrics across ultrasound scans

   In 2025, he coauthors a study on 20-week ultrasound scans that estimates fetal biometrics across 1,457 recordings comprising 48 million frames and compares the AI estimates to real-time manual measurements.

8. Since 2024

   Professor at Imperial and collaborative AI

   Since September 2024, Kainz is a Professor in Imperial College London's Department of Computing, where he heads the human-in-the-loop computing group and is one of four academics leading the Biomedical Image Analysis (BioMedIA) Lab. In May 2026, he co-leads Imperial's fourth-year Deep Learning course with Yingzhen Li for more than 600 students, and in July 2026, he receives an ERC Proof of Concept grant to train collaborative AI models that track illness-linked patterns in patient data.