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Adelin Travers

I'm a 2nd year PhD Student at the University of Toronto and the Vector Institute co-supervised by Prof. Nicolas Papernot and Prof. David Lie. I obtained my MSc. in Computer Science from the University of Oxford under the supervision of Prof. Samson Abramsky and my Diplôme d'Ingénieur from Télécom ParisTech.

Before coming back to academia, I worked as security auditor at a Big 4 consulting firm. I then moved to a Japanese financial firm where I developed trading algorithms for a short time before leading the creation of an in-house penetration testing team. I hold various certifications.


I'm interested in topics at the intersection of ML, AI, and security. I'm especially interested in offensive, audit, and forensics methods as drivers of interpretable safety-critical AI. You can find my academic publications here and my contributions to AI Security Policy and industry standards here.




SoK: Machine Learning Governance.

Varun Chandrasekaran*, Hengrui Jia*, Anvith Thudi*, Adelin Travers*, Mohammad Yaghini*, Nicolas Papernot. arXiv preprint.

On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples.

Adelin Travers*, Lorna Licollari, Guanghan Wang, Varun Chandrasekaran, Adam Dziedzic, David Lie, Nicolas Papernot. arXiv preprint.

Machine Unlearning.

Lucas Bourtoule*, Varun Chandrasekaran*, Christopher Choquette-Choo*, Hengrui Jia*, Adelin Travers* , Baiwu Zhang*, David Lie, Nicolas Papernot. Proceedings of the 42nd IEEE Symposium on Security and Privacy, San Francisco, CA. (2021)

AI Security Thought Leadership and Policy

AI Village (AIV) Response to the NIST RFI on Artificial Intelligence Risk Management Framework (AI RMF)

Adelin Travers, Anita Nikolich, Abhishek Gupta, Stella Biderman, Brian Pendleton, Erick Galinkin, Brian Martin, John Irwin, Anusha Ghosh.

Professional certifications