Practical problem solver in the fields of Computer Vision, Machine and Deep Learning. Particularly interested in Neuromorphic technologies and Astronomy. Academic background in Telecommunications and Electrical Engineering (ICT). Experienced in data collection, management and visualisation. Life-long learner.
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February 2022 - now / Remote 🌍
Visual defect detection from image segmentation (data pipeline, model training); object detection for drone warehouse applications (data synthesis, training, on-device deployment, c++ inference post-processor); design and on-premise deployment of LLM-based RAG system.
February 2022 - now / Vilnius 🇱🇹
Generative AI research for 3D (text-to-3d, image-to-3d) and integration into cgdream.ai; early-stage BE design and build of cgdream.ai; at-scale image classification and aesthetics ranking projects; custom deployment process of ML models (containers, custom registry, API).
October 2021 - December 2021 / Ljubljana 🇸🇮
Research on neural style transfer, from simulation to reality, and tests on data augmentation.
September 2019 - September 2021 / Trieste 🇮🇹
Research and prototyping of computer vision and learning-based algorithms for drones navigation and applications. Work on optical flow and object detection on resource constrained settings. Sensors research for system design. Mechanical parts control on Arduino.
April 2019 - August 2019 / Genève🇨🇭, Braunschweig 🇩🇪
Functional owning (concept design and testing) of a fleet management service, namely driving efficiency report, for a big car manufacturing company.
September 2018 - March 2019 / EuTEC, Stuttgart 🇩🇪
Internship and Master Thesis on multispectral data acquisition with event-based cameras. Use of events obtained from a spectral filter tuning to reconstruct the spectrum of the scene. Sensor tests and benchmark evaluation with simple reconstruction methods.
Oct 2016 - Apr 2019 / UNIPD (Padua) 🇮🇹
Score: 110 cum Laude / 110
Oct 2013 - Nov 2016 / UNIPD (Padua) 🇮🇹
Score: 98 / 110