Resume
Academic Achievements
- Co-created and deployed SynthID, developed Med-Gemini and AMIE. Published numerous papers, and his open-source projects are widely adopted. Received the DAGM MVTec Dissertation Award 2023, Qualcomm Innovation Fellowship 2019, and was selected as an outstanding paper at CVPR 2021 CV-AML. Recognized as an outstanding/top reviewer for CVPR, ICML, and NeurIPS in several years.
Research Experience
- Led multiple cross-organizational research projects involving medical AI agents, watermarking, and LLM models. Contributed to safety evaluations in Bard (now Gemini). Worked as a web engineer at Microsoft, RS Computer, and Fraunhofer FKIE.
Education
- Completed his PhD at the Max Planck Institute for Informatics; obtained both bachelor's and master's degrees from RWTH Aachen University with a short stint at Georgia Tech.
Background
- Research interests include deep learning, AI agents, AI for science (e.g., health and protein folding), uncertainty estimation and factuality, and computer vision. He has been a research scientist at Google DeepMind, focusing on medical AI agents and watermarking.
Miscellany
- Personal interests and hobbies not specifically mentioned.