Teaching

Materials for courses and pedagogic events.

Graduate Courses

Medical Image Analysis Lab

2024 with Shelley.

More details Changelog: using GitHub classroom for assignments; updated simpler starter code repository and organization. Course evaluation score remains high at 4.89. Representative student feedback: "I absolutely enjoyed this course. I think that Shelley and Amith did a fantastic job with this course. I highly appreciate how interactive the course was during the lecture portion and how available and helpful they were during the lab portion. During the projects, we had quite some freedom to experiment which I think is great for our learning process and the feedback/guidance from the TAs has been really great."

2023, with Shelley and Mike.

More details Changelog: project specific slack channels; video lectures along with in-class presentation; hospital clinic visit. Course evaluation score remains high at 4.92. Representative student feedback: "I got to improve my programming skills and the TA was extremely helpful and nice!"

2022, with Elias and Jayden.

More details The overall course evaluation score increased from 3.25 in 2021 before I was involved to 4.94 this year!

Biomedical Engineering Lab

2022 with Yannick.

More details This is a short practical rotation course for incoming Masters' students in Biomedical Engineering to get a quick overview of what we do in the Medical Image Analysis lab.

Symposia and Community Events

Lead Organizer for Bern AI in Radiotherapy (BART) Symposium in March 2025.

More details Robert and I are co-organizers of BART, a one-day symposium for AI in Radiotherapy. We have three keynote speakers across radiation oncology, medical physics and engineering/AI. 100 registrants attended from 5 countries, with 11 posters and three flash talks. We are applying for funding to run this again next year.

Lead Organizer for Bern Interpretable AI (BIAS) Symposium in March 2023.

More details Yannick and I are co-organizers of BIAS, a one-day symposium for Interpretable AI, hosted at the Cupola room at the Uni Bern main building. We have an attendance of 140 researchers (70 online) and posters from 5 countries.

Tutorial at IEEE TenCon 2019 in 2019.

More details I ran a 3 hour tutorial on Deep Learning with MATLAB, including a refresher for Deep Learning, designing and visualizing deep networks, challenges and analysis of training deep networks, and finally deployment to GPUs. This was very interactive and by far the highest attended parallel tutorial session with several questions from the audience.

Pre-conference Workshop at IEEE DISCOVER 2019 in 2019.

More details I ran a full day workshop on Demystifying Deep Learning using MATLAB, including an introduction to deep learning, pre-trained networks, transfer learning, followed by training networks from scratch, deployment to GPUs, and assorted computer vision related demonstrations. This was attended by about 30 people.

Educational Content

AI in Radiotherapy

More details This is designed for someone with a computer science background, who would like to familiarize themselves with radiation oncology topics so as to build useful tools in this application area.

BENDER

More details This is a series of fun educational videos to learn nuances of Deep Learning as applied to Medical Imaging. We have also created a [GitHub Repo](https://github.com/ubern-mia/bender) which includes supporting material, including code and references. I play the role of a new graduate student who learns the ropes.