Carlos Cotrini

Carlos Cotrini

Senior Scientist Focus Education

About

I'm a lecturer at the Institute of Machine Learning at ETH Zürich, under the supervision of Prof. Joachim Buhmann. I teach courses in machine learning and computer science with a focus on making complex concepts accessible to students and bridging theory with practical applications.

My research journey includes a PhD in information security under the supervision of Prof. David Basin, where I developed expertise in privacy-preserving machine learning and security analysis. Prior to joining ETH, I worked on infon logic under the guidance of Prof. Yuri Gurevich.

My current work focuses on developing robust machine learning algorithms, privacy-preserving technologies, and educational methodologies that help students understand complex mathematical and computational concepts through intuitive explanations and practical implementations.

Recent Research Highlights

S-BDT: Distributed Differentially Private Boosted Decision Trees
ACM CCS 2024
Thorsten Peinemann, Moritz Kirschte, Joshua Stock, Carlos Cotrini, Esfandiar Mohammadi
A novel differentially private distributed gradient boosted decision tree learner that improves privacy protection while maintaining utility through non-spherical multivariate Gaussian noise and tight subsampling bounds.
Automated Large-Scale Analysis of Cookie Notice Compliance
USENIX Security 2024
Ahmed Bouhoula, Karel Kubicek, Amit Zac, Carlos Cotrini, David A. Basin
The first general, automated, large-scale analysis of cookie notice compliance, analyzing 97k websites and revealing that 65.4% of websites likely collect user data despite explicit negative consent.
View All Publications

Teaching Philosophy

I believe in making complex concepts accessible through clear explanations, practical examples, and step-by-step implementations. My courses range from statistical learning theory to hands-on machine learning tutorials, always emphasizing the connection between mathematical foundations and real-world applications.

All about Transformers and Stable Diffusion: A Step-by-Step Guide
Learn to implement transformer-based translators and stable diffusion models from scratch, with clear explanations and minimal prerequisites.
View Teaching Portfolio