Emanuele Albini
AI Research - Vice President at J.P. Morgan
London, England, United Kingdom
Summary
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Senior🎓
Top SchoolEmanuele Albini is an AI research leader with 8 years of experience, currently Vice President of AI Research at J.P. Morgan, where he bridges foundational Trustworthy AI research and production-grade ML systems for high-stakes finance applications like credit lending and market making. He holds a PhD from Imperial College London and has a strong academic-to-industry trajectory focused on XAI, particularly argumentation-based explainability and robustness for complex models. His background includes hands-on optimization work at Fujitsu’s Digital Annealer group—where he improved solutions by up to 30%—and a track record of deploying interpretable, auditable models across enterprise domains. Based in London, he blends rigorous research with pragmatic engineering, making explainability work at scale in regulated, mission-critical environments.
8 years of coding experience
1 year of employment as a software developer
Master's degree Computer Science and Engineering, Master's degree Computer Science and Engineering at Università degli Studi di BresciaIntensive Course Japanese Language and Culture, Intensive Course Japanese Language and Culture at Naganuma SchoolDoctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at Imperial College LondonExchange studies Computer Engineering, Exchange studies Computer Engineering at Mid Sweden UniversityCollegio Universitario "Luigi Lucchini"Liceo Scientifico "Leonardo", Brescia, Italy
Italian, English, Japanese
Github Skills (18)
explainable-artificial-intelligence9
magicmirror7
machine-learning6
feature-selection6
ssa5
xgboost5
todoist4
textlint4
chrome-extension4
glossary4
api3
python3
qualtrics3
shap3
shapley2
Programming languages (4)
Github contributions (5)
emanuele-albini/emutils
Apr 2021 - Jan 2022
Contributions:11 releases, 65 pushes, 1 branch in 9 months
jpmorganchase/cf-shap
Jul 2022 - Dec 2022
Counterfactual SHAP: a framework for counterfactual feature importance
Contributions:41 commits, 4 pushes, 1 comment in 5 months
xgboostcounterfactual-explanationsshapalgorithmic-recourseexplainability
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