Faculty
Adam Dziedzic is a tenure-track faculty member at CISPA, where he co-leads the SprintML group with a research focus on Secure, Private, Robust, Interpretable, and Trustworthy Machine Learning. Before joining CISPA, he was a Postdoctoral Fellow at the Vector Institute and the University of Toronto, a member of the CleverHans Lab, advised by Prof. Nicolas Papernot. He earned his PhD in computer science at the University of Chicago, where he was advised by Prof. Sanjay Krishnan and worked on input and model compression for adaptive and robust neural networks.
European Conference on Computer Vision (ECCV) Data Circuit Breaker: Identifying Training, Test, and Generated Data in Image Generative Models
The 19th European Conference on Computer Vision (ECCV), 2026 MultiMem: Measuring and Mitigating Memorization in Multi-Modal Contrastive Learning
IH&MMSec '26: ACM Workshop on Information Hiding and Multimedia Security Watermark Degradation Across Model Iterations
Proceedings of the ACM Asia Conference on Computer and Communications Security ADAGE: Active Defenses Against GNN Extraction
International Conference on Machine Learning (ICML) Finding DoRI: Discovery of Retained Images in Diffusion Models
International Conference on Machine Learning (ICML) Concept Removal in Frontier Image Generative Models
International Conference on Learning Representations (ICLR) Natural Identifiers for Privacy and Data Audits in Large Language Models
International Conference on Learning Representations (ICLR) SERUM: Simple, Efficient, Robust, and Unifying Marking for Diffusion-based Image Generation
International Conference on Learning Representations (ICLR) Benchmarking Empirical Privacy Protection for Adaptations of Large Language Models
International Conference on Learning Representations (ICLR) Data Provenance for Image Auto-Regressive Generation