Enrico Civitelli
Lead AI Specialist For Engineering And Controls at Baker Hughes
Florence, Tuscany, Italy
Summary
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Senior🎓
Top SchoolEnrico Civitelli is a Lead AI Specialist with a Ph.D. in Information Engineering and nine years of experience turning state-of-the-art models into production robotics and vision systems. He has patented perception tech for autonomous-driving-like applications, published in top venues (including IEEE TNNLS and ECCV), and led deep learning productization at Comau where his transformer-based grasping system became part of a commercial OnePicker line. Comfortable across research and engineering, he builds practical tools—robot stiffness estimation and manipulator-selection algorithms—that reduced engineering time and proved robust in real-world deployments showcased at major industrial fairs. He teaches and mentors extensively, supervising theses that integrate SAM, OWL-V2, Isaac Sim, and Azure ML while delivering internal LLM/GenAI courses and GDG lectures. Now at Baker Hughes, he focuses on scaling AI for engineering and controls, blending hands-on prototyping with executive-level dissemination. Colleagues note his uncommon mix of high-impact publications, patents, and shipped industrial products that bridge academic rigor with operational value.
9 years of coding experience
3 years of employment as a software developer
Visiting Ph.D. Machine Learning, Visiting Ph.D. Machine Learning at Universitat Autònoma de BarcelonaDoctor of Philosophy Control Optimization and Complex Systems, Doctor of Philosophy Control Optimization and Complex Systems at Università degli Studi di FirenzePerito Industriale Capotecnico Electronics & Information Technology, Perito Industriale Capotecnico Electronics & Information Technology at ITIS Galileo Galilei
English, Italian
Github Skills (60)
python10
machine-learning10
hierarchical-clustering10
numpy10
som10
deep-learning10
gpu10
neural-network10
self-organizing-map10
gnn9
wikipedia9
hierarchical9
topological-data-analysis9
iterative9
acceleration9
Programming languages (1)
Github contributions (5)
enricivi/encephalic_vasculature_mapping
Nov 2016 - Mar 2018
Contributions:36 commits, 2 PRs, 34 pushes in 1 year 3 months
blood-vesselsexploreapproachbloodfit
enry12/SEMI-FALKON
Jun 2018 - Sep 2020
Falkon is one of the most efficient algorithm able to work in a supervised large scale setting. This method is the result of a combination of three simple principles: sub-sampling, preconditioning and iterative solvers. In order to extend FALKON usability we have designed an extension able to work in a semi-supervised scenario.
Contributions:62 commits, 3 PRs, 18 pushes in 2 years 2 months
iterativesemi-supervisedpreconditioningableefficient-algorithm
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