As a Research Scientist at SEDDI, I currently work on researching new learning based methods for improving fabric materials digitization from single images and generative modeling of SVBRDF materials among other topics. Also, I am charge of continuous improvement efforts for the neural network model behind textura.ai, SEDDI’s flagship fabric digitization tool, ensuring it remains at the forefront of the industry.

As a member of the Computer Vision and Aerial Robotics Research Group, I developed learning based computer vision algorithms for aerial robotic perception, with a strong focus on applied research and industriy collaboration in real world problems. During this time, I worked on my PhD. thesis, entitled: Adaptive Learning with Weak Supervision for Robotic Perception, with a focus on developing unsupervised methods to reduce the amount of data required to train deep learning models.

As part of two EU H2020 projects, POLAR-EM and MAGTOOLS, I developed software tools for efficient and reliable analysis of magnetic materials in electron microscopy imaging.

As an intern at the Altran Innovation Centre for Advanced Manufacturing, I gained experience working with virtual and augmented reality-based simulators for advanced manufacturing systems and worker training, providing practical and immersive learning opportunities in this field.

During my time with the Intelligent Computation Systems research group, I focused on using CUDA-enabled GPUs to accelerate tomography reconstruction algorithms for electron microscopy imaging. Additionally, I developed a low-cost system for indoor positioning based on multiview cameras.