Gianluca Scarpellini is a Senior Research Scientist based in New York with seven years of experience pushing the frontier of AI for scientific problems, particularly diffusion models and robotics. He holds a PhD and has contributed state-of-the-art graph-based diffusion formulations and practical pipelines that solved large puzzles and advanced event-camera 3D pose estimation and object detection. At Genesis Molecular AI he focuses on diffusion approaches for protein folding and molecular docking, scaling pretraining and optimizing inference with consistency models and distillation. His DeepMind internship produced an ICLR-accepted contribution that sped up offline policy evaluation on real robots by up to 10x, and he has a strong track record of shipping reproducible open-source tools (notably repositories from IIT-PAVIS). He combines rigorous academic research with hands-on engineering across distributed systems and multi-GPU training, and uniquely blends curiosity-driven robotics exploration with molecular AI.
7 years of coding experience
5 years of employment as a software developer
Nanodegree, Deep Reinforcement Learning, Nanodegree, Deep Reinforcement Learning at Udacity
M.s. in Computer Science, Computer Vision, M.s. in Computer Science, Computer Vision at Università degli Studi di Milano-Bicocca
Contributions:49 pushes, 1 issue in 4 years 1 month
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Gianluca Scarpellini - Sr Research Scientist at Genesis Molecular AI