Research - Our Team

Ignacio García Vega is a data scientist specialising in infectious-disease and climate-health modelling. He holds an MSc in Fundamentals of Data Science from the University of Barcelona (2024), where his thesis examined tuberculosis dynamics in Argentina, and a BSc in Civil Engineering from the University of Chile (2014). He has advanced expertise in Python, time-series forecasting, geospatial analysis, and data visualisation.

From 2014 to 2022, he was Head of Innovation and Technological Projects at Polpaico/BSA in Chile, leading data-driven initiatives in logistics optimisation and occupational health. Since 2022, he has worked as an independent data-science consultant, developing predictive models, dashboards, and geospatial tools to support decision-making across sectors.

He currently leads the technical development of a multi-scale dengue early-warning and projection platform for Villa María, Argentina. His responsibilities include defining system architecture and indicators; creating Python libraries for mechanistic and machine-learning models (e.g., SEIR and LSTM); integrating a production-ready stack (FastAPI, Vue.js, and PostgreSQL); validating models with epidemiological, climate, and mobility data; coordinating with municipal stakeholders; and training end-users. The project is being delivered as an integrated software platform with user training. He is fluent in Spanish and English.

Lines of research

• Dengue early-warning & forecasting (SEIR+ML).
• TB spatiotemporal modelling; geospatial risk maps.
• Data engineering for surveillance platforms (Python/DB/APIs).