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Federico Bennasciutti
Robotics & AI Engineer
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Building the eyes and brains of autonomous robots
I love robotics, computer vision, and the challenge of making machines truly understand their surroundings.
Ultimately, I want to build technology that makes our life effortless.
Robotics Engineer @ Intermodalics
Aug 2022 - Now | Leuven, Belgium
Building perception and SLAM pipelines for autonomous mobile robots, integrating 2D/3D cameras, LiDAR, and GNSS.
Designing and optimizing AI detection and tracking stacks for NVIDIA Jetson edge platforms.
Built a near-realtime navigation stack for autonomous logistics robots.
R&D Researcher @ Ericsson
Jun 2021 - Jan 2022 | Lund & Stockholm, Sweden
Investigated object detection pipeline for AR/VR applications.
Explored Deep Learning representations and image analysis techniques for Semantic SLAM frameworks.
Machine Learning Intern @ Moseeker Inc
Sep 2019 - Jan 2020 | Shanghai, China
Built a machine learning model to predict candidate employability from audio signals extracted from large-scale interview datasets.
Designed data pipelines and audio feature extraction workflows to train and deploy the model end-to-end.
Master's in Systems, Control and Robotics
Aug 2020 - Jun 2022 | KTH Royal Institute of Technology, Sweden
Multidisciplinary Master's program focused on modern robotics. Key coursework: Applied Estimation, Computer Vision, and Deep Learning.
Thesis in collaboration with Ericsson: Extended input modalities for deep feature extraction networks to enhance robustness in Visual SLAM systems.
AI Fellow | School of Artificial Intelligence
Jun 2020 - Jul 2020 | Pi School, Rome, Italy
Highly competitive, merit-based program aimed at top-tier engineering professionals.
Engineered an AI-powered voice interface to automate call center triage, streamlining real-time operations through Natural Language Understanding (NLU).
Double Bachelor's in Automation Engineering
Sep 2016 - Dec 2019 | Università di Bologna & Tongji University
Completed a rigorous dual-degree program across Bologna and Shanghai, gaining a global perspective on engineering and cross-cultural collaboration.
Graduated with two independent theses:
CNNs for proportional myocontrol — decoding muscle signals to control prosthetic limbs.
Audio signal classification for predicting candidate employability from interview recordings.