Amith J. Kamath

Yet another PhD student.


ARTORG Center for Biomedical Engineering Research

University of Bern

My name is Amith (meaning ‘infinite’ in Sanskrit) and I enjoy investigating problems in image analysis and building tools to solve them. I like mathematics as applied to gain a better understanding of what we see (naturally, or otherwise).

I am currently a doctoral student with Prof. Mauricio Reyes in the Medical Image Analysis lab, at the ARTORG Center, learning more about pixel-level segmentation using Deep Learning models and its’ robustness in clinical settings as applied to radiotherapy planning. Earlier, I learnt vision and robotics at Georgia Tech remotely, and wrote a masters’ dissertation at Minnesota, focusing on reducing MRI acquisition times while maintaining accurate orientation measurement of white matter fibers in our brains.

Along the way, I wrote code for image/vision at the MathWorks, built technical content for undergraduate courses, ran interactive workshops/seminars across India, all in the broad areas of computer science, biomedical engineering, and mathematics.

Here is a more detailed CV. I am grateful to call Bern, Bengaluru, Boston, Minneapolis, and Mangalore as home at various points in time.


Oct 8, 2023 :scroll: Our papers titled “Do we really need that skip connection? Understanding its’ interplay with task complexity” and “Dose Guidance for Radiotherapy-oriented Deep Learning Segmentation” are both (early) accepted at MICCAI ‘23 in Vancouver. More details soon!
Oct 8, 2023 :mega: iMIMIC is back at MICCAI 23: see website for important dates. More details to come: stay tuned!
Jul 24, 2023 :scroll: Our paper titled “ASTRA: Atomic Surface Transformations for Radiotherapy quality Assurance” is accepted as an Oral Presentation at EMBC ‘23 in Sydney. Elated to win the 2nd place - best student paper award: click for more!.
Jun 5, 2023 :mega: Delighted to be invited to share my “Young Researchers’ Tales” story in the 8x8’ event hosted at Haus der Universität, organized by the MVUB. See here for more.
May 5, 2023 :mega: At the Bern Data Science Day, presenting again our work on dose prediction model sensitivity. See here for more.
Apr 18, 2023 :scroll: Our paper titled “How sensitive are deep learning based radiotherapy dose prediction models to variability in Organs At Risk segmentation?” is accepted at ISBI ‘23 in Cartagena. See here for more.