Amith J. Kamath

PhD Researcher in Computer Vision, Biomedical Imaging

profile.png

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.

news

Apr 11, 2025 :mega: Grateful to be named one of five University of Bern Venture Fellows for 2025-26!
Mar 30, 2025 :mega: A short video on using MONAI and MATLAB together is now live on the MathWorks YouTube channel! Read more here.
Mar 14, 2025 :mega: We organized BART - the first Bern AI in RadioTherapy symposium on the 14th of March 2025. We had three keynote speakers, two sponsors, nine posters and ~100 registrations!
Nov 30, 2024 :mega: Zahira (master student advisee) won the CAIM Research Award in the Translation category for her contributions to ContourAId. Way to go, Zahira!
Nov 07, 2024 :mega: Our research is one of 100 “lab” pitches from researchers all over the world (60+ countries) at the 35th anniversary of the fall of the Berlin Wall - at the Falling Walls Science Summit 2024.
Oct 07, 2024 :scroll: Our paper “AutoDoseRank: Automated Dosimetry-Informed Segmentation Ranking for Radiotherapy” is accepted at the CaPTion@MICCAI Workshop.
Jul 01, 2024 :scroll: Our paper “Comparing the Performance of Radiation Oncologists versus a Deep Learning Dose Predictor” is accepted as an oral presentation at MIDL 2024 (18% acceptance for Oral, 36/217). Read more here.
May 27, 2024 :scroll: Two abstracts accepted at ISBI 2024! Congratulations to Zahira Mercado for presenting this as part of her Master thesis!
Oct 08, 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, top 14%) accepted at MICCAI 2023 in Vancouver. Read more here.
Jul 26, 2023 :mega: Elated to win the 2nd place - best student paper award! at EMBC 2023!