Jan-Nico Zaech

Johns Hopkins University, ETH Zurich, Sofia University "St. Kliment Ohridski"

Papers

Total Citations

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About

Jan-Nico Zaech is a researcher at the forefront of integrating machine learning with advanced robotic systems, with a primary focus on medical imaging and autonomous robotics. His most impactful work, "Enabling machine learning in X-ray-based procedures via realistic simulation of image formation" (2019, 61 citations), pioneered the use of realistic simulations to train deep learning models for X-ray guidance, significantly improving the safety and efficiency of image-guided interventions. Building on this, his research in "Task-Specific Trajectory Optimisation for Twin-Robotic X-Ray Tomography" (2021, 28 citations) advanced the capabilities of robotic C-arm CT systems by enabling complex, optimized scanning trajectories, expanding the clinical and industrial applications of computed tomography. More recently, Zaech has contributed to the robotics foundation model community with "ReVLA: Reverting Visual Domain Limitation of Robotic Foundation Models" (2024–2025), addressing critical visual domain gaps in Vision-Language-Action models to make robotic generalists more robust across diverse environments. His work bridges simulation, perception, and control, earning recognition for its practical impact on both medical and industrial robotics.