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Beat Buesser | Origin Story | Adversarial Robustness Toolbox


Join us for a conversation with researcher, machine learning engineer, and software developer, Beat Buesser. His current work focuses on automated machine learning, data science, computer vision, adversarial machine learning, and security in artificial intelligence. Beat tells us his origin story, as well as, about his work on the Adversarial Robustness Toolbox (ART), which is a Python library for defending, certifying, and verifying ML models against the adversarial threats of evasion, poisoning, extraction, and inference.

ART GitHub

Beat Buesser’s IBM Research profile

You can watch the replay of Beat’s talk, “Adversarial Robustness Toolbox (ART) – Evasion, Poisoning, Extraction and Inference,” from the IBM Cloud Native Security Digital Developer Conference.