Hi there! 👋
I am a Robotics & Computer Vision Engineer on a mission to give machines full spatial autonomous intelligence. From tinkering with Arduinos to pushing autonomous drones through high-speed, GPS-denied environments at ETH Zürich, I’ve dedicated my career to bridging the gap between perception and physical action: what we now call Physical AI.
My technical foundation spans spatial computing, multi-agent coordination, and real-time state estimation across demanding hardware platforms.
Since December 2026, I serve as a Senior Robotics Engineer at Verity AG, bringing autonomous systems into high-impact real-world environments.
🚀 Industry Experience
Verity AG (Senior Robotics Engineer): Pushing the boundaries of autonomous drone systems and robotic intelligence in complex indoor operations.
Magic Leap (Senior Computer Vision Engineer): Engineered high-performance C++/Python sensor fusion, Visual-Inertial Odometry (VIO), and online calibration pipelines for next-generation AR/VR/XR headsets. Optimized SLAM estimation accuracy across complex edge cases, directly boosting tracking robustness and user experience against key KPI benchmarks.
- Google XR (External Vendor via Magic Leap): Contributed advanced perception algorithms and spatial intelligence software for Google’s next-generation, AI-powered AR smart glasses.
Magic Leap (Computer Vision Research Intern): Developed a solution to critical scale-drift challenges in AR tracking, as validated by improved scale estimation accuracy across thermal operational ranges, by architecting a C++/Python online multi-camera calibration pipeline that modelled thermal induced focal length shifts.
Schindler Aufzüge AG (Software Engineer Intern): Developed core software engineering solutions for physical industrial systems.
🎓 PhD & Research Roots
In April 2023, I earned my PhD in Robotics & Computer Vision from the Vision for Robotics Lab (V4RL) at ETH Zürich, supervised by Prof. Dr. Margarita Chli.
The focus of my dissertation was on multi-robot coordination and semantic perception-aware active planning for autonomous MAVs. My doctoral research pioneered how autonomous drones perceive, navigate, and land in extreme environments using semantic cues and deep Reinforcement Learning (RL).
Core Technical Expertise
Spatial AI & Perception: Visual-Inertial Odometry (VIO), Visual SLAM, Structure-from-Motion (SfM), Multi-Sensor Fusion, Online Calibration.
Autonomy & Control: Active Perception, Semantic Path Planning, 3D Reconstruction/Mapping, Reinforcement Learning (Sim-to-Real), Multi-Agent Swarm Coordination.
📬 Let’s Connect & Collaborate
Whether you’re interested in spatial perception, autonomous navigation, or cutting-edge Physical AI research, I’m always open to discussing new ideas, technical challenges, and groundbreaking projects.