I investigate diffusion-based methods for generating synthetic medical imaging data in low-data regimes. As part of this work, I introduced DermaFlux, a framework that improves pathology classification performance by 8% through the curation of a 500k image–text pair dataset. In addition, I explore the use of large language models (LLMs) to generate synthetic medical captions and automate the classification of pathology reports.

As a Computer Vision Engineer at Huawei UK, I specialized in 3D facial reconstruction from monocular images. In this role, I integrated cutting-edge techniques to advance the field, focusing on enhancing the accuracy and effectiveness of reconstruction methods. My work involved pushing the boundaries of state-of-the-art approaches, such as NeRF and diffusion-based techniques. Moreover, I focused on designing a generic 3D Gaussian Splatting framework for animatable head avatars, enabling consistent identity generation across viewpoints.

I worked as a Research Assistant on the ARISE project at the Business School of Imperial College London. This EU-funded initiative focused on forecasting agricultural crop yields across regions and time periods. I developed machine learning models using satellite imagery and weather data, building pipelines to integrate spatial and temporal information effectively. To address data scarcity, I implemented synthetic data generation techniques, improving model generalisation and robustness in underrepresented regions.

My main responsibilities included the design of scalable automated pipelines for large-scale image collection from the web. In this way, the creation of high-quality datasets that reflect real-world scenarios was enabled. I also led the design and coordination of human annotation workflows at ArielAI, ensuring consistency and accuracy across labelled data. This work supported robust model training by combining efficient data acquisition with reliable annotation processes, contributing to the company’s eventual acquisition by Snap Inc..

In my capacity as the sole Machine Learning Engineer, I undertook the development of a robust network for automated product recognition within images captured from supermarket shelves. This required designing Computer Vision algorithms and tools for easy annotation and creating both training and detection procedures alongside with back-end support.