2025-06-01 — New Paper Published: "Digital Divides in Telehealth Accessibility" in npj Digital Medicine. Learn more →
2025-05-10 — Dataset on ZCTA-level cancer incidence interpolation released on Harvard Dataverse. Learn more →
Updates
Events
2025-07-21 — GeoAI & GenAI Workshop, Harvard CGA, Cambridge MA. Learn more →
2025-03-15 — Presentation at AAG 2025: “GNN for Health Service Area Detection”. Learn more →
MIGIS: Mindful Intelligence in GIS
MIGIS is an interdisciplinary research initiative that integrates spatial thinking, geospatial modeling, and explainable artificial intelligence to address critical challenges in urban health, environmental justice, and data-driven decision-making. Led by Dr. Lingbo Liu at Harvard University’s Center for Geographic Analysis, MIGIS emphasizes not only the technical rigor of geospatial intelligence but also the ethical, human-centered, and policy-relevant dimensions of spatial data science. MIGIS stands at the intersection of spatial modeling, digital equity, and open science. Its core mission is to develop mindful and responsible spatial analytics—tools and methods that are not only powerful but also interpretable, inclusive, and actionable. The initiative contributes to global research through open-source toolkits, reproducible workflows, and collaborative platforms that empower governments, researchers, and communities to build healthier and more equitable cities.
Featured Projects
GeoAI
Explainable geospatial machine learning models for public health and climate resilience.
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Healthy Cities
Accessibility modeling and urban health analysis based on human mobility and spatial equity.
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Visual Programming
KNIME-based visual tools for geospatial workflows, teaching, and reproducible research.
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