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I am a doctoral candidate at the Helmholtz Zentrum München and Technische Universität München.
My research interests include:
- Inverse problems in computational microscopy
- Image generation and image reconstruction for biomedical imaging
- Self-supervised and unsupervised learning
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:
- Privacy-preserving machine learning
- Transfer learning
- Statistical modeling
I was also fortunate to spend time at The Hong Kong Polytechnic University.
Featuered projects
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.