sebszyller

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Sebastian Szyller sebszyller

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Researcher in adversarial & trustworthy machine learning

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sebszyller/README.md

Hello there

My name is Sebastian and I'm a tenure-track assistant professor at the Department of Computer Science at Aalto University. I lead Trustworthy & Adversarial Computing Lab (group GitHub). I work on trustworthy machine learning and adjacent topics.

You can get a better idea by looking at my publication list (Google Scholar) or blog posts.

Here you can find the forks of the official releases of my scientific work:

LLMart a toolkit for generating adversarial prompts
ML pipeline attestation with Atlas
model watermarking with DAWN
PRADA defence against model extraction
conflicts in ML protection mechanisms
clustering for fraud detection

as well as some tinkering projects:

(I use neovim, btw)

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ssg-research/dawn-dynamic-adversarial-watermarking-of-neural-networks ssg-research/dawn-dynamic-adversarial-watermarking-of-neural-networks Public

Watermarking against model extraction attacks in MLaaS. ACM MM 2021.

Jupyter Notebook 34 5
SSGAalto/prada-protecting-against-dnn-model-stealing-attacks SSGAalto/prada-protecting-against-dnn-model-stealing-attacks Public

Reference implementation of the PRADA model stealing defense. IEEE Euro S&P 2019.

Python 35 11
ssg-research/amulet ssg-research/amulet Public

Amulet: A Library for Interactions among Machine Learning Defenses and Risks

Python 8
IntelLabs/LLMart IntelLabs/LLMart Public

LLM Adversarial Robustness Toolkit, a toolkit for evaluating LLM robustness through adversarial testing.

Python 44 8
rust-with-llms rust-with-llms Public

Learning rust with the help of ChatGPT

Rust 2