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F.B. / Manifesto
— 01 —MMXXVI
Robotics · Perception · AI
FedericoBennasciutti
Robotics & AI Engineer/ Leuven · BE
Teaching machines to see the world before they move through it.
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— manifesto —
Machines that understand before they act.
Most of what makes a robot useful is invisible: the part where it figures out the world before it does anything. That’s the part I work on. The goal is technology that ages well — quiet, careful, and built to be trusted.
01Life2016 — present
2022 →Leuven, Belgium
Senior Robotics Engineer // Intermodalics
Building perception and SLAM pipelines for autonomous mobile robots, integrating 2D/3D cameras, LiDAR, and GNSS.
Designing and optimising AI detection and tracking stacks for NVIDIA Jetson edge platforms.
Built a near-realtime navigation stack for autonomous logistics robots.
2021 — 2022Lund · Stockholm, Sweden
R&D Researcher // Ericsson
Investigated object detection pipelines for AR/VR applications.
Explored deep-learning representations for semantic SLAM frameworks.
2020 — 2022KTH · Stockholm, Sweden
M.Sc. Systems, Control & Robotics // KTH
Multidisciplinary Master’s focused on modern robotics — Applied Estimation, Computer Vision, Deep Learning.
Thesis with Ericsson: extending input modalities for deep feature extraction to improve robustness in Visual SLAM.
2020Pi School · Rome, Italy
AI Fellow // School of Artificial Intelligence
Highly competitive, merit-based fellowship for top engineering professionals.
Engineered an AI-powered voice interface for call-centre triage using Natural Language Understanding.
2019 — 2020Shanghai, China
Machine Learning Intern // Moseeker Inc.
Built an ML model to predict candidate employability from audio signals in large-scale interview datasets.
Designed data pipelines and audio feature-extraction workflows end-to-end.
Rigorous dual-degree across Bologna and Shanghai — engineering with a global, cross-cultural lens.
Two theses: CNNs for proportional myocontrol (decoding muscle signals for prosthetic control); audio-signal classification for predicting candidate employability.