Tim Adler
About
Hi, I'm Tim! I'm a freshly graduated computer science Ph.D. student. I am working at hema.to where we develop machine learning methods to improve leukemia diagnostics. I worked on my Ph.D. at the German Cancer Research Center (DKFZ) in the group of Lena Maier-Hein. There, I focused on uncertainty quantification in biomedical imaging using machine and deep learning techniques. I have a background in mathematics and physics (which comes in very handy from time to time). In my spare time, I love to play pen-and-paper role-playing games, practice yoga, and hike.
I am more than happy to chat about my work and my private projects. You can find a selection of communication channels below.
Contact
Talks
- Merantix Paper Reading Group 2023: Uncertainty Quantification in Biomedical Imaging video
- IPCAI 2022: Video-rate perfusion imaging in laparoscopy
- Photonics North 2021: Uncertainty-aware deep learning for spectral image analysis Keynote @ “Photonics and AI” (joint with Lena Maier-Hein)
- MICCAI UNSURE 2019: Out of Distribution Detection for Intra-Operative Functional Imaging paper | arXiv
- IPCAI 2019: Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks short talk | long talk | paper | arXiv
- Older Talks
First author publications
- Spectral imaging enables contrast agent-free real-time ischemia monitoring in laparoscopic surgery L Ayala*, TJ Adler*, S Seidlitz, S Wirkert, C Engels, A Seitel, J Sellner, A Aksenov, M Bodenbach, P Bader, S Baron, A Vemuri, M Wiesenfarth, N Schreck, D Mindroc, M Tizabi, S Pirmann, B Everitt, A Kopp-Schneider, D Teber**, L Maier-Hein** *,** equal contribution (respectively) Science Advances 2023 paper | medRxiv | press release (in German)
- Out of Distribution Detection for Intra-operative Functional Imaging TJ Adler, L Ayala, L Ardizzone, HG Kenngott, A Vemuri, BP Müller-Stich, C Rother, U Köthe, L Maier-Hein MICCAI UNSURE 2019 paper | arXiv | talk
- Uncertainty handling in intra-operative multispectral imaging with invertible neural networks TJ Adler, L Ardizzone, L Ayala, J Gröhl, A Vemuri, SJ Wirkert, BP Müller-Stich, C Rother, U Köthe, L Maier-Hein MIDL 2019 OpenReview
- Uncertainty-aware performance assessment of optical imaging modalities with invertible neural networks TJ Adler, L Ardizzone, A Vemuri, L Ayala, J Gröhl, T Kirchner, SJ Wirkert, J Kruse, C Rother, U Köthe, L Maier-Hein IPCAI 2019 paper | arXiv | short talk | long talk
Education
- Dr. rer. nat. Computer Science, Heidelberg University, Germany. Thesis: “Uncertainty quantification in biophotonic imaging using invertible neural networks”, 2018 - 2022
- M. Sc. Mathematics, Heidelberg University, Germany. Thesis: "A boundary map to the Roller boundary of a CAT(0) cube complex", 2014 - 2017
- B. Sc. Physics, Heidelberg University, Germany. Thesis: "Further improvement of a NO to NO2 converter for CE-DOAS measurements", 2010 - 2016
- Exchange Year, University of North Carolina at Chapel Hill, NC, USA. 2014 - 2015
- B. Sc. Mathematics, Heidelberg University, Germany. Thesis: "A Uniformization Theorem for compact Riemann surfaces", 2011 - 2014
- Abitur, Hartmanni-Gymnasium Eppingen, Germany, 2001 - 2010