Christoph Clement
Machine Learning Engineer at Khumbu
Munich, Bavaria, Germany
I am a Machine Learning Engineer at Khumbu, an AI drug discovery startup based in Munich, where I leverage cutting-edge AI models for drug discovery with an initial focus on diabetes. I recently completed my PhD in Biomedical Engineering at the University of Bern (2021-2024), where I maintain a 5% postdoctoral affiliation.
My research focuses on applying deep learning and medical imaging analysis to solve significant healthcare challenges. During my PhD, I developed innovative approaches for high-resolution Organ-on-Chip imaging, interpreted tau-PET brain scans for neurodegenerative diseases, and advanced CT-free total-body PET segmentation. As a Visiting Researcher at the Center for Advanced Medical Computing and Analysis (CAMCA) in Boston, I worked on foundational models for PET/CT imaging under the supervision of Dr. Quanzheng Li.
I hold a Master’s degree in Robotics, Cognition, and Intelligence from the Technical University of Munich (TUM), where I specialized in computer-aided medical procedures, computer vision, and deep learning. I also completed an honors degree in Technology Management at the Center for Digital Technology and Management (CDTM), combining technical expertise with entrepreneurial skills.
Previously, I worked on deepfake detection at TUM’s Visual Computing Group in collaboration with the AI Foundation, and gained industry experience as a Data Science Trainer at Celonis, where I delivered hands-on workshops across Europe, and as a researcher at tacterion.
selected publications
- iScienceImproved Interpretation of 18F-Florzolotau PET in Progressive Supranuclear Palsy Using a Normalization-Free Deep-Learning ClassifieriScience, 2023
- JNMDynamic Imaging of Organs-on-Chips Using a Dedicated PET Scanner: A Simulation StudyJournal of Nuclear Medicine, 2023
- EJNMMI Phys