Welcome!

I am a Principal Investigator (Machine Learning and Computer Vision) at EssilorLuxottica’s Smart Eyewear Lab, where I work at the intersection of Computer Vision, Deep Learning, and Embedded Software. My research focuses on advancing the intelligence and functionality of smart eyewear technologies by applying optimized deep learning and computer vision techniques.

In this role, I supervise the Computer Vision team at Politecnico and oversee 7 ongoing projects aimed at developing innovative solutions for smart eyewear. My current focus is on researching machine learning models optimized for embedded deployment on microcontrollers, targeting context recognition for smart eyewear. I also drive efforts to identify innovative patents, having submitted 6 patents, and regularly contribute to the academic community with publications, authoring 3 research papers so far in this role.

In the past, I was a Machine Learning Research Associate at Imperial College London, working for the Care Research and Technology Centre (CR&T) of the UK Dementia Research Institute (UKDRI), and a member of the Barnaghi Lab.

I was awarded my Ph.D. from the Advanced Robotics Lab and HAIR Robotics Lab at the School of Electronics Engineering and Computer Science, Queen Mary University of London, United Kingdom. My Ph.D. was sponsored by the National Centre of Nuclear Robotics (NCNR), focusing on developing cutting-edge technology to solve the problem of nuclear waste.

During my time at Imperial College London, I specialized in detecting health-related episodes in people living with dementia by applying recurrent deep learning models to personalized data (activity, sleep, and physiological data). I also worked on surface exploration for fracture detection in extreme environments (e.g., nuclear power plants), using vision techniques such as object detection to localize cracks that were then explored with a fiber optic sensor attached to a robotic manipulator.

In addition to my roles at EssilorLuxottica and Imperial College, I have been involved in several other research initiatives. I contributed to the NinaPro and MeganePro projects, acquiring DB6 to analyze the repeatability of sEMG classification of hand grasps. I also worked as a Computer Vision Intern at the Tokyo University of Agriculture and Technology, where I developed a multi-modal fusion model for surface fracture detection, and as a Research Assistant at HES-SO Valais-Wallis, where I applied machine learning and computer vision techniques in healthcare.

As a Ph.D. graduate in engineering with a focus on machine learning, I possess extensive knowledge of deep learning techniques and architectures. I have worked on supervised learning, object detection, semantic and instance segmentation, and 3D reconstruction, with proficiency in Python, PyTorch, and TensorFlow.

For further information, please refer to the projects page.

Main research:

• Context Recognition
• Machine learning for Healthcare
• Image Classification
• Object Detection
• Signal Processing
• Learning from Noisy Data
• Haptic Exploration

I am currently learning how to develop with Unreal Engine and modelling and animate in Blender

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