Lars Hillebrand
Machine Learning Team Lead Financial And Legal Intelligence at Fraunhofer IAIS
Cologne Bonn Region Germany
Summary
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Senior🎓
Top SchoolLars Hillebrand is a Machine Learning Team Lead and PhD in AI with eight years of experience building applied ML systems for financial, legal and sustainability domains. At Fraunhofer IAIS he leads production deployments of generative AI and custom ML—including an agentic legal-document analysis system and an AI recommender for audit efficiency used with PwC. His research brought KPI-BERT and KPI-Check into practical use for extracting and reconciling KPIs from German financial reports, and he designed sustain.AI to map sustainability disclosures to GRI requirements. He combines rigorous academic training (magna cum laude PhD and an elite MSc in Economics & Finance) with hands-on product integration for large enterprise clients. Known for bridging research and industry, he focuses on interpretable NLP pipelines and audit-ready automation rather than black-box models. Based in the Cologne–Bonn region, he uniquely blends economic domain knowledge with ML engineering to deliver measurable compliance and efficiency gains.
8 years of coding experience
Doctor of Philosophy - PhD, Artificial Intelligence, 0,66 - magna cum laude, Doctor of Philosophy - PhD, Artificial Intelligence, 0,66 - magna cum laude at Rheinische Friedrich-Wilhelms-Universität BonnElite M.Sc., Advanced Economics and Finance (Cand.oecon), 1.3 (11/12), Elite M.Sc., Advanced Economics and Finance (Cand.oecon), 1.3 (11/12) at Copenhagen Business School
German, English
Stackoverflow
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0reached
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Github Skills (136)
python10
deep-learning10
gpu10
streamlit10
gpu-acceleration10
acceleration10
numpy10
falcon10
jupyter-widget10
neural-network10
transformer10
nlp10
jupyter10
pipelining10
tensorboard10
Programming languages (7)
Github contributions (5)
fluidml/fluidml
Aug 2020 - Nov 2022
FluidML is a lightweight framework for developing machine learning pipelines.
Contributions:9 releases, 4 reviews, 196 commits in 2 years 3 months
developingdata-sciencedeep-learningmachine-learningmlops
LarsHill/metadict
Jan 2022 - Oct 2022
MetaDict is a powerful dict subclass enabling (nested) attribute-style item access/assignment and IDE autocompletion support.
Contributions:3 releases, 27 commits, 7 PRs in 9 months
pythondot-notationitemautocompletionide
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