Research Volunteer
| website: https://www.linkedin.com/in/isaac-mateo-g-55aa7a318/
Isaac Mateo Gavilanes Chavez is a Systems Architect at the MIT Critical Data Global Consortium and an undergraduate researcher at Yachay Tech University (Ecuador). He specializes in designing large-scale automated data pipelines (ETL) and deploying machine learning architectures for global health equity and scientometric analysis. Notably, he recently optimized and deployed the ultra-lightweight Titan v4 LLM on the CEDIA High-Performance Computing cluster for edge deployment in low-resource settings. His current work focuses on federated data architecture, causal inference, and evaluating geographical bias in medical AI research, including leading the backend infrastructure for the 2026 Vivli AMR Challenge.
Research Interests
Systems Architecture & Data Engineering (ETL pipelines, API orchestration), Applied Artificial Intelligence & Edge AI (Lightweight LLMs, NLP), Causal Inference & Biostatistics in Health Informatics, Global Health Equity & Scientometrics