Benyamin Gheiji

👋 Machine Learning, Medical Imaging, Uncertainty Quantification

I'm Benyamin Gheiji, a medical student and AI researcher working at the intersection of medicine, medical imaging, and machine learning. My research focuses on developing trustworthy AI systems for healthcare, with particular interests in neuroradiology, uncertainty quantification, and deep learning. I am driven by a simple but critical question: how can we make AI not only powerful, but trustworthy enough to support real clinical decisions? My work centers on building models that are reliable, well-calibrated, and transparent—qualities that become essential when the outcome may influence a patient's diagnosis, treatment, or prognosis. My research has led to publications in peer-reviewed journals, presentations at international conferences, and recognition from leading medical imaging organizations. Beyond research, I actively contribute to the scientific community through mentoring, education, peer review, and the development of open resources that help advance medical AI. My long-term goal is to become a physician-scientist who bridges clinical medicine and artificial intelligence, translating cutting-edge research into tools that create meaningful impact for patients and healthcare systems. I am always interested in connecting with researchers, clinicians, and engineers who share the vision that the future of medicine depends not only on more capable AI, but on AI that clinicians can understand, trust, and confidently use.

📚 Research

→ full list on Google Scholar

🏆 Honors

💻 GitHub Repositories

→ see more on my GitHub profile

🎓 Education & Teaching

🛠️ Technical Skills