Alexander Radovic is a Machine Learning Engineer with nine years of experience translating cutting-edge deep learning research into high-impact production and scientific outcomes. With a PhD in High Energy Particle Physics from UCL, he led development of NOvA’s first convolutional vision network (CVN), a model that boosted analysis performance by ~30% and saved the experiment the equivalent of roughly $72M in equipment value. He has moved between academia and industry—leading ML research teams at Borealis AI and now engineering at Meta—bridging large-data scientific analysis, rigorous model validation, and deployable ML systems. Comfortable in Python and C++, he combines mathematical modeling and hands-on engineering to spot edge cases and build robust calibration and verification tools. Based in New York but with a global track record from London to Toronto and Chicago, he’s equally fluent presenting to public audiences and to top technical peers.
Contributions:57 commits, 26 pushes, 1 branch in 1 year 2 months
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