Michaël Ughetto
Senior Director, AI Enterprise Process & Innovation Center
Gothenburg, Västra Götaland County, Sweden
Summary
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Senior🎓
Top SchoolMichaël Ughetto is a data-driven AI and graph technology leader with nine years of experience translating complex scientific problems into production-scale solutions, currently directing the Biological Insights Knowledge Graph and AI Strategy & Innovation at AstraZeneca. Trained as a PhD experimental particle physicist, he brings deep expertise in large-scale, compute-intensive statistical analysis and machine-learning classification developed on international collaborations like ATLAS at CERN. He is fluent in Python and C++ and has progressed from hands-on graph data science to engineering leadership, shaping knowledge-graph architectures that connect biology and AI. Known for bridging research rigor with product delivery, he combines academic discipline—such as developing multivariate flavour-tagging algorithms and spectrum calculators—with practical experience in industry data science. Based in Mölndal, Sweden, he is driven by bringing AI into everyday life and scaling scientific insight into impactful, production-ready systems.
9 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy (Ph.D.) Constituants élémentaires, Doctor of Philosophy (Ph.D.) Constituants élémentaires at University of Montpellier
French, English, German
Github Skills (68)
coverage10
shiny-apps10
recall10
godoc10
pandas9
plot9
recommender-system9
personalization9
neo4j9
chemistry9
cypher9
rank9
recommender9
python9
gpu9
Programming languages (9)
Github contributions (5)
AstraZeneca/skywalkR-graph-features
Nov 2021 - Feb 2022
Example notebooks that illustrate how to generate knowledge-based features. Features can be used in a variety of ML models, including recommender systems.
Contributions:1 release, 2 commits, 1 push in 3 months
mlmodelrecommender-systemknowledge-graph
mughetto/hep
Apr 2017 - Aug 2017
Contributions:7 pushes, 3 branches in 4 months
golangmonogo-hephepmono-repository
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