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I am a Machine Learning Research Associate at Imperial College London working for the Care Research and Technology Centre (CR&T) of UK Dementia Research Institute (UKDRI) and I am currently a member of Barnaghi Lab. I was recently 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), a project which aim was to develop cutting-edge technology to solve the problem of nuclear waste.

My current research focuses on detecting health related episodes in people living with dementia by applying recurrent deep learning models on personalised data (activity, sleep and physiologycal data). I previously worked on surface exploration for fracture detection and localisation in extreme environments (e.g., nuclear power plant) using vision techniques (e.g., object detection) to first localise the possible cracks which are then explored with a fibre optic sensor, attached as an end-effector to a robotic manipulator. I have collaborated in the past to the NinaPro and MeganePro project, acquiring DB6 to analyse the repeatability of sEMG classification of hand grasps.

As a Ph.D. graduate in engineering with a focus on machine learning, I have extensive knowledge of deep learning techniques and architectures. I have worked on projects related to supervised learning, object detection, semantic & instance segmentation, and 3D reconstruction, and am proficient in Python, PyTorch, and TensorFlow. For further information, please refer to the projects page.

Main research:

• 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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