Sebastian Hurubaru
Course Developer at Stanford Center for Professional Development
Greater Munich Metropolitan Area Germany
Summary
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Rockstar🎓
Top SchoolSebastian Hurubaru is a Treasury and Capital Markets technology expert and course developer with over a decade of experience building and architecting trading systems and treasury platforms for major banks. He blends hands-on software engineering (C/C++, Python, Java, C#) with business analysis and system architecture, eliminating the need for intermediaries between technology and business stakeholders. Since 2018 he has deepened his AI expertise at Stanford, contributing to ML course code (notably to the cs224u repo) and working on projects in capital markets, anti-fraud and medicine using NLP, computer vision and reinforcement learning. Currently based in the Greater Munich area, he splits his time between senior engineering at Münchener Hypothekenbank and developing/facilitating Stanford professional AI courses. His profile is distinguished by rare domain depth across derivatives, FX and portfolio management combined with applied AI skills and production-grade infrastructure experience (containers, middleware, databases). He is also an advisor in the AI community and a lifelong math and physics competitor, underscoring a rigorous analytical foundation.
7 years of coding experience
7 years of employment as a software developer
Economics, Economics at CFA InstitutePOLITEHNICA București National University for Science and TechnologyArtificial Intelligence, Artificial Intelligence, Artificial Intelligence, Artificial Intelligence at Stanford University
Github Skills (11)
pytorch10
machine-learning10
nlp10
python10
openapi10
natural-language-processing10
scikit-learn9
scikit9
jupyter-notebook9
deep-learning8
data-science7
Programming languages (7)
Github contributions (5)
cgpotts/cs224u
Jan 2023 - Jan 2023
Code for Stanford CS224u
Role in this project:
ML Engineer
ML EngineerContributions:6 reviews, 5 commits, 3 PRs in 1 day
Contributions summary:Sebastian primarily contributed to code related to a machine learning course. They focused on modifying and improving existing code, including tasks such as refining functions for k-nearest neighbors, updating code to accommodate the Windows operating system, and passing parameters to functions in open-ended question answering. Additionally, the user addressed issues in the homework formatting guide and updated tools to match the grader versions. The user also made changes to the setup and tutorial files, implying a role in the overall maintenance and improvement of the codebase.
deep-learningstanfordmachine-learning
SebastianHurubaru/cs229_ai_fight_financial_crime
Nov 2019 - Dec 2019
Contributions:57 commits in 1 month
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