Peter Lorenz

NTU
Adversarial Machine Learning and Model Stealing
I am currently a Postdoctoral Research Fellow at Nanyang Technological University (NTU) Singapore, ranked 2nd worldwide in AI research, focusing on trustworthy AI. I recently completed my Ph.D. with magna cum laude from Heidelberg University, Germany, specializing in adversarial machine learning for classification, generative diffusion models with focus on harmful outlier detection to increase the trustworthness of AI models and prepare them for open-world problems. During my Ph.D. (thesis), which I completed in 3.5 years, I conducted an internship at MIT-IBM Watson AI Lab and achieved notable results, including a top 3% paper award at the ICASSP conference, a top-20 ranking in the CVPR 2022 Art-of-Robustness Challenge, and two times Oxford summer school acceptance.
In addition to my research, I actively contribute to the machine learning community as a reviewer for top-tier conferences such as ICML, ICLR, and NeurIPS. My passion lies in advancing the field of machine learning, with a particular focus on its practical applications.
Previously, I worked in academia and industry on the CARLA simulator for pedestrian safety and classification models for mobile robotics, including vehicles and drones. Before that, I contributed to the vision system of autonomous robots (Team TEDUSAR @TU Graz, that won the robocup competition “best in autonomy” in 2016.) in terms of my Bachelor thesis.
news
Jan 07, 2025 | Check out my continuously updated reading list about model stealing! |
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Mar 18, 2024 | I am happy to announce that I am a reviewer at the CVPR Workshop Robustness of Foundation Models 🎉 |
Jan 29, 2024 | I am accepted for the Oxford Summer School - Representation Learning |
Oct 18, 2023 | I am happy to announce that I am reviewer at ICASSP on the topics federated / split learning and quantum privacy 😄 |
Aug 26, 2023 | Check out my writeups from the Lakera Gandalf hackathon. |
latest posts
Mar 28, 2025 | Recommender Systems |
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Mar 28, 2025 | Imbalanced Data |
Mar 28, 2025 | MLSD |