Summary
Amirreza Mahbod is an Assistant Professor and AI researcher with nine years of experience specializing in deep learning for medical image analysis, holding a PhD and a Habilitation track in Medical Informatics, Biostatistics & Complex Systems from the Medical University of Vienna. He has combined academic and industry roles—from postdoctoral work and lecturing at Vienna to research science positions and a visiting stint at KTH and Stanford—delivering practical machine learning solutions for microscopy and histopathology. His work focuses on developing robust deep-learning algorithms for nucleus detection, segmentation and classification, with a track record of translating research prototypes into applied tools within clinical and industrial settings. Based in Vienna, he bridges engineering, biostatistics and clinical needs, often tackling messy real-world imaging datasets rather than curated benchmarks. Colleagues note his rare blend of hands-on algorithm development and teaching, making him effective at both mentoring students and pushing applied AI projects toward deployment.
9 years of coding experience
10 years of employment as a software developer
Master’s Degree Biomedical/Medical Engineering, Master’s Degree Biomedical/Medical Engineering at KTH Royal Institute of Technology
Master’s Degree Electrical and Electronics Engineering- Bioelectric, Master’s Degree Electrical and Electronics Engineering- Bioelectric at Iran University of Science and Technology
Habilitation (Venia docendi) Medical Informatics Biostatistics and Complex Systems, Habilitation (Venia docendi) Medical Informatics Biostatistics and Complex Systems at Medical University of Vienna
English, Persian, German