Hi 👋, I am Peter and fascinated to make computers smarter. I have studied and worked in different places. I can help you, for example, for your job search or shape your research topic.

Mentoring: Ideal mentees would be early career in tech. Instead of a generic approach, I prefer to support you in your situation and give you instructions. This should enlighten your paths and reflect your situation.
Besides that, I can give you feedback on your CV and I can give you help to become better in LeetCode interview questions by supervising your learning strategies.

My background: Postdoctoral Research Fellow at Nanyang Technological University (NTU) Singapore, 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., which I completed in 3.5 years, I conducted an internship at MIT-IBM Watson AI Lab and achieved notable , 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.