Summary
Alex Fedorov is a Research Assistant Professor at Emory University with 11 years of experience developing self-supervised, multimodal, and generative AI methods for medical imaging. He has a strong academic foundation (PhD, MS) and a track record of translating unsupervised representation learning into neuroimaging tools and publications, including work on Deep InfoMax and brain segmentation tools like MeshNet and Brainchop. His industry research internships at Meta, Microsoft, and Descript advanced large-scale self-supervised models for video and audio, complementing his academic focus on robustness and interpretability. Alex bridges theory and practice, designing mutual information–based objectives and scalable training for real-world biomedical datasets. Based in Atlanta, he leads translational projects at the Center for Data Science that aim to make complex deep learning methods accessible to clinical researchers. A less obvious strength is his cross-disciplinary fluency—from low-level C/ASM implementations early in his career to state-of-the-art transformer-based models—enabling both efficient system design and cutting-edge algorithmic innovation.
12 years of coding experience
9 years of employment as a software developer
Doctor of Philosophy - PhD, Electrical and Electronics Engineering, Doctor of Philosophy - PhD, Electrical and Electronics Engineering at Georgia Institute of Technology
Master of Science - MS, Electrical Engineering, 3.83/4.33, Master of Science - MS, Electrical Engineering, 3.83/4.33 at The University of New Mexico
Bachelor’s Degree, Applied Mathematics, 4.42/5, Bachelor’s Degree, Applied Mathematics, 4.42/5 at National Research University of Electronic Technology (MIET)
English