Tomáš Chobola

[email protected]

𝕏 / GitHub / Google Scholar / ORCID / CV / 🇨🇿


I am a doctoral candidate at the Helmholtz Zentrum München and Technische Universität München.

My research interests include:

My mission is to develop new techniques that improve image quality, paving the way for advancements in biomedical research.

I am also part of MUDS.

Education & previous projects

Prior to my doctoral studies, I completed my master’s degree in Data Engineering and Analytics from TUM.

Additionally, I had the opportunity to contribute to several projects that involve:

I was also fortunate to spend time at The Hong Kong Polytechnic University.

Featuered projects

Fast Context-Based Low-Light Image Enhancement via Neural Implicit Representations.
One-shot low-light image enhancement based on the HSV color space.
Accepted to ECCV ‘24.

Leveraging Classic Deconvolution and Feature Extraction in Zero-Shot Image Restoration.
Self-supervised network for microscopy image synthesis.
Accepted to ICCV ‘23 BioImage Computing Workshop.

A Feature-Driven Richardson-Lucy Deconvolution Network.
Volumentric microscopy image restoration model.
Accepted to MICCAI ‘23.