Tassilo Klein
Director Of Machine Learning Research Principal Scientist, SAP AI Research
Berlin, Germany
Summary
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Senior🎓
Top SchoolTassilo Klein is a Director of Machine Learning Research and Principal Scientist at SAP AI Research with 11 years of experience translating advanced ML research into enterprise-grade products, including SAP’s first foundation model for structured data. He leads cross-disciplinary teams building agentic AI, multi‑agent supply‑chain simulations, and privacy-preserving representation learners, and has driven open science by releasing the first open-source ERP dataset now used in Stanford’s RelBench. A prolific inventor and scholar, he holds 30+ patents and publications at ACL, NeurIPS, and CVPR, and mentors PhD-level researchers while shaping product roadmaps. His background in medical imaging and distributed deep learning informs a pragmatic approach to robust model training in data‑scarce, regulated domains. Based in Berlin, he also advises stealth startups on agentic architectures and generative UI protocols, bridging cutting-edge research with deployable enterprise systems.
11 years of coding experience
13 years of employment as a software developer
Computer Science, Computer Science at Concordia UniversityDoctor of Philosophy (PhD) Computer Aided Medical Procedures, Doctor of Philosophy (PhD) Computer Aided Medical Procedures at Technical University of MunichVordiplom (pre-diploma degree) equivalent Bachelor's degree Computer Science, Vordiplom (pre-diploma degree) equivalent Bachelor's degree Computer Science at Ludwig-Maximilians-Universität MünchenAbitur (high school diploma) Chemisty English Math Economics, Abitur (high school diploma) Chemisty English Math Economics at Gymnasium Starnberg
English, German, Persian
Github Skills (134)
transformers10
language-model10
python10
vector-database10
flax10
economics10
deep-learning10
simulate10
sec10
fine-tuning10
transformer10
gpt10
nlp10
jax10
application10
Programming languages (5)
Github contributions (5)
SAP-samples/acl2022-self-contrastive-decorrelation
Mar 2022 - Nov 2022
Source code for ACL 2022 paper "Self-contrastive Decorrelation for Sentence Embeddings".
Contributions:54 commits, 40 pushes, 8 comments in 8 months
ainlpresearch-paperself-contrastiveself-contrastive-decorrelation
SAP-samples/emnlp2021-attention-contrastive-learning
Sep 2021 - Apr 2022
Repository supporting an accepted paper at EMNLP 2021 on attention contrastive learning.
Contributions:14 commits, 11 pushes, 1 comment in 6 months
aiartificial-intelligenceemnlp2021machine-learningnatural-language-processing
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