Sergey Prokudin is a senior scientist and computer vision researcher based in Zurich with 11 years of experience building robust, efficient algorithms for 3D and 4D scene analysis and probabilistic deep learning. He progressed from malware analysis and large-scale ML systems at Kaspersky to a PhD at the Max Planck Institute and applied science internships at Amazon, culminating in postdoctoral and senior scientist roles at ETH Zürich. His work blends geometric deep learning, uncertainty quantification, and computational efficiency, with peer-reviewed contributions such as ICCV 2019 on point-cloud encoding. Known for turning theoretical models into practical, scalable methods, he thrives on problems that require marrying mathematical rigor with engineering trade-offs.
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