I am enthusiastic about collaborating with the Φ-lab team at the European Space Agency (ESA) to contribute to Earth Observation (EO) science and research on projects related to deep learning, computer vision, machine learning, Artificial Intelligence (AI), and signal processing. I aim at accelerating the future of Earth Observation (EO) and remote sensing by developing innovative Artificial Intelligence (AI) technologies and solutions, including deep generative models and discriminative classifiers, to more accurately quantify and understand the impact of climate change and predict climate change applications.
I am a Research Fellow at the European Space Agency (ESA). My background is in deep learning and computer vision. I have experience in (i) deep generative models, including Generative Adversarial Networks (GAN), invertible flow-based models, Variational Autoencoders (VAE), and diffusion models, and (ii) deep discriminative classifier models, including Convolutional Neural Networks (CNN) and Residual Networks (ResNet). My models perform Out-of-Distribution (OoD)/ anomaly detection, object of interest detection and classification, and OoD/ novelty detection in the real Open World (e.g., (a) joint classification and OoD detection, i.e. Open-Set recognition, and (b) Open-World classification). My methodologies are based on semi- and self-supervised learning, contrastive similarity learning, and representation learning. My methods are also based on few-shot learning, data augmentation, probability density estimation, and confidence assignment and assessment (aleatoric and epistemic uncertainty quantification and reduction). I have four-year Post-Doctoral experience working as a Research Associate in Machine Learning at the University of Edinburgh (UoE) and the University Research Collaboration in Signal Processing conducting research on Robust Generative Neural Networks, a PhD degree in Signal Processing from Imperial College London, and a Masters MEng degree (including Bachelor’s level study) in Electrical and Electronic Engineering from Imperial College London
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