Aleksandr Kaminskii is a Senior Machine Learning Engineer at Deep Origin, where he builds physics-informed and deep learning models, scientific software, and simulation infrastructure to accelerate molecular and protein research. Trained in computational neuroscience and neuroengineering (MSc, Université Paris-Saclay) with a background in informatics and applied mathematics (ITMO University), he has worked on protein dynamics modeling, coarse-grained simulations, and biological data pipelines drawing on resources like PDB and UniProt. His prior research includes deep learning for neuronal imaging and graph-based representations at Institut Pasteur, complemented by extensive software engineering experience in high-performance systems and data pipelines. His interests span neurochemistry, protein interactions, and ML for biomolecular discovery.
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