André Cruz
PHD Candidate
Tübingen, Baden-Württemberg, Germany
Summary
👤
Senior🎓
Top SchoolAndré Cruz is a PhD candidate at the Max Planck Institute for Intelligent Systems with a decade of experience researching trustworthy and responsible AI, particularly around reliable LLM evaluation, alignment, pluralism, and robustness. He bridges rigorous research and production impact—previously helping ship Responsible AI work at Feedzai and contributing to deployed client solutions. An active open-source ML engineer, André contributed key concept-drift handling logic to prominent streaming libraries such as River and scikit-multiflow, including an Additive Expert Ensemble implementation. His background combines top-ranked academic performance (Masters and BSc in Informatics, top 1%) with international research stints, including a visiting scholar role at Harvard focused on LLMs for preference elicitation and mechanism design. Colleagues describe him as someone who moves swiftly from algorithmic innovation to pragmatic engineering, making complex evaluation and fairness ideas operational.
10 years of coding experience
4 years of employment as a software developer
Master of Science - MS, Informatics and Computing Engineering, 18.7 out of 20 (top 1%), Master of Science - MS, Informatics and Computing Engineering, 18.7 out of 20 (top 1%) at Faculdade de Engenharia da Universidade do PortoDoctor of Philosophy - PhD, Machine Learning, Doctor of Philosophy - PhD, Machine Learning at University of TübingenMaster of Science - MS, Informatics, 1.4, Master of Science - MS, Informatics, 1.4 at Technical University Munich
Portuguese, English, Spanish, German
Stackoverflow
11reputation
76reached
0answers
1question
Github Skills (12)
scikit10
drift10
incremental-learning10
machine-learning10
online-machine-learning10
ensembles10
python10
numpy10
streaming-data10
scikit-learn10
stream9
django6
Programming languages (13)
Github contributions (5)
scikit-multiflow/scikit-multiflow
Mar 2019 - Apr 2019
A machine learning package for streaming data in Python. The other ancestor of River.
Role in this project:
ML Engineer
ML EngineerContributions:22 commits, 6 PRs, 8 comments in 14 days
Contributions summary:André's commits primarily involve the development and enhancement of machine-learning models within the scikit-multiflow library. They implemented and refined an Additive Expert Ensemble, a method for concept drift adaptation. The user also made minor fixes and improvements to existing code, and worked on other ensemble methods. The commits suggest a focus on developing and integrating advanced machine learning techniques for streaming data.
moapythonstreaming-datariverancestor
online-ml/river
Mar 2019 - Apr 2019
🌊 Online machine learning in Python
Role in this project:ML Engineer
ML EngineerContributions:22 commits in 14 days
Contributions summary:André primarily contributed to the development of an Additive Expert Ensemble, implementing and refining core functionalities for this online machine learning model. They added and modified code related to weight updates, expert predictions, and pruning strategies, demonstrating a focus on concept drift handling. The user's work included refactoring and debugging code related to the ensemble's architecture and interactions with the base estimators, particularly in the `skmultiflow/meta` directory.
stream-processingpythonstreaming-datadata-scienceonline-statistics
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