- Developed a link prediction model to streamline drug discovery by leveraging knowledge graphs, significantly improving the efficiency of identifying potential targets.- Led R&D efforts in developing a deep learning framework for lipid nanoparticle analysis, utilizing cryo-electron microscopy images to enhance characterization precision and drug efficacy analysis.- Developed generative AI frameworks, including Retrieval-Augmented Generation (RAG) and multi-agent systems, for… Show more - Developed a link prediction model to streamline drug discovery by leveraging knowledge graphs, significantly improving the efficiency of identifying potential targets.- Led R&D efforts in developing a deep learning framework for lipid nanoparticle analysis, utilizing cryo-electron microscopy images to enhance characterization precision and drug efficacy analysis.- Developed generative AI frameworks, including Retrieval-Augmented Generation (RAG) and multi-agent systems, for drug discovery, pre-clinical, and clinical analysis, enhancing biomedical data interpretation and decision-making capabilities across healthcare research and development.- Collaborated in the research and development of large language models for genomics, primarily for single-cell annotation. Show less

- Led the research and development of graph-based models for node classification and link prediction in supply chain data, enhancing failure mode analysis using graph neural networks.- Implemented an automated inventory system used in distribution centers, incorporating computer vision for label extraction and efficient matching to product catalogs.- Refined ETA prediction accuracy by leveraging geospatial data insights to correct sensor inaccuracies in the centralized control… Show more - Led the research and development of graph-based models for node classification and link prediction in supply chain data, enhancing failure mode analysis using graph neural networks.- Implemented an automated inventory system used in distribution centers, incorporating computer vision for label extraction and efficient matching to product catalogs.- Refined ETA prediction accuracy by leveraging geospatial data insights to correct sensor inaccuracies in the centralized control platform. Show less

Master's degree internship- Research and development of a novel framework for optimizing portfolios solely composed of volatility strategies, accounting for margin requirements.

- Worked on complex network dynamics reconstruction from data through sparse recovery techniques.- Studied the behavior of the Lyapunov exponent as a predictor of critical changes in dynamical regime.- During the COVID-19 pandemic, collaborated on the research and development of a computational model for disease spread, accounting for the general social dynamics of any community (CORMOBUSS).

- Optimized marketing investments for different countries, based on user metrics and past campaign efficiency.

- Developed a capital allocation optimization software for private pension portfolios under regulatory constraints.

- In collaboration with Professor Karl Friston's neuroscience team at UCL, researched state transitions in time series and reconstruction techniques for the dynamics of complex networks.