Computer Vision Engineer / Data Scientist
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Driven by a profound curiosity and a deep interest in machine learning, I am a researcher specializing in the innovative applications of computer vision and deep learning in medical image analysis. My work focuses on leveraging advanced algorithms, including CNNs and attention mechanisms, to address critical challenges in medical diagnostics and treatment, such as multiple sclerosis progression mapping, aortic dissection detection, and kidney segmentation in ADPKD patients.
My academic and professional experiences have equipped me with a solid foundation in machine learning, image processing, and statistics. My dedication to the field is demonstrated through my active contributions, including publishing and presenting my findings in multiple conferences and journals.
I strive for sustainable solutions in computer vision, with an emphasis on minimizing environmental impact while advancing the field. My experience supervising students, lecturing, and reviewing for medical journals showcases my commitment to the academic community and continuous learning.
As I continue to explore the frontiers of deep learning and medical imaging, I am eager to connect with like-minded professionals and organizations dedicated to making a significant impact on human lives through innovation and technology.
Research Associate (PhD) - Heidelberg University
Researching on medical image processing with machine learning using limited data.
M.Sc. - Medical Photonics