synergize AI, machine vision and microscopy (and multi-omics!)
AI-based microscopy machine vision research is a highly interdisciplinary field requiring good knowledge of machine learning, computer vision, microscopy and the associated biomedical applications. We develop new deep learning and computer vision algorithms driven by real biomedical applications for R&D. We also generalize or productionize existing algorithms for high-dimenstional microscopy images, so that more and more the high-end AI algorithms are accessible to biomedical researchers. Currently, our focus is applications arose from whole-body or whole-organ imaging using lightsheet flurorescence microscopy (LSFM), high resolution confocal microscopy images, and high throughput timelapse microscopy, as well as mass spectrometry imaging. But, the methods and tools are mostly generalizable for other modalities and applications. In our group, we are building a diverse team with different expertises and embrace extensive internal and external collaborations.
(New!) Our group is extending our expertise in AI and microscopy to multi-modal data. Analytical measurement, such as mass spectrometry image based proteomics, provide additional important biochemical information besides the morphological information from microscopy. Mutli-modal learning offers a new opportunity to revolutionize analyical biomedical research in 4D (quantity, type, location, and time).
(Thesis Projects!) Master students in the Ruhr area are welcome to conduct their master thesis in our lab.
(Open Position!) Highly motivated PhD and Postdoc students are always welcome to inquiry about our open opportunities.
Highlights
Our Research
AI-based microscopy machine vision is a highly multi-disciplinary field. There are so many fanscinating problems to explore and study.
Our Resources
Our group is commited to open science, such as open source softwares/packages, public datasets, open access publications. We believe open science can lead to impactful science.
Our Team
We are building a team with diverse background and expertises, from software enigneering, machine learning, image analysis, data analysis to microscopy and computational biomedical modeling.