About Dr. Diego F. Cuadros

Professor of Epidemiology, Digital Epidemiologist, and AI-Human Interaction Researcher

Dr. Diego F. Cuadros, Ph.D.

Professor, University of Cincinnati

Director, Digital Epidemiology Lab

Biography & Mission

Born and raised in Bogota, Colombia, Dr. Diego F. Cuadros earned his B.Sc. in Biology from the National University of Colombia, followed by a Ph.D. in Biology from the University of Kentucky. His doctoral research on HIV epidemiology in sub-Saharan Africa cultivated his passion for quantitative epidemiology and health geography.

Dr. Cuadros's current research program bridges AI-human interaction, agentic AI systems, digital epidemiology, mathematical modeling, and disease ecology. His group studies how AI agents behave in real scientific workflows, how memory and oversight should be governed, and how complex data can be translated into actionable insight for researchers, health agencies, and communities.

Research Pillars

AI-Human Interaction & Agentic Systems

Designing and evaluating AI agents, collaborative memory systems, oversight mechanisms, and decision workflows that keep human authority visible and accountable.

AI Agents

AI-Human Interaction

Memory Governance

Oversight

Infectious Disease Epidemiology

Pioneering research on HIV/AIDS, COVID-19, and Hepatitis C, focusing on co-infections, transmission dynamics, and intervention strategies in high-risk populations.

HIV/AIDS

COVID-19

HCV

Pandemics

Health Geography & Spatial Epidemiology

Utilizing GIS and spatial analysis to map disease hotspots, uncover environmental and social determinants of health, and analyze geographic disparities in healthcare access.

GIS

Hotspot Analysis

Health Disparities

Substance Use Epidemiology

Analyzing the spatial and temporal evolution of the U.S. opioid crisis, identifying demographic shifts and geographic drivers to inform targeted public health interventions.

Opioid Crisis

SUD

Public Health

Career Trajectory

2025-Present

Professor

University of Cincinnati, Dept. of Biological Sciences

Leading a research program in AI-human interaction, digital epidemiology, infectious disease modeling, and disease ecology.

c. 2021-Present

Director, Digital Epidemiology Lab

UC Digital Futures

Building data-driven, AI-supported, and human-centered approaches for scientific reasoning, surveillance, equity, and decision support.

2022-2025

Associate Professor

University of Cincinnati, Dept. of Geography & GIS

Advanced digital epidemiology, spatial epidemiology, HIV research, and computational public health.

2016-2022

Assistant Professor

University of Cincinnati, Dept. of Geography & GIS

Established the Health Geography and Disease Modeling Lab, laying the foundation for current research.

2016

Research Fellow

Africa Health Research Institute, South Africa

Modeled community-, household-, individual-, spatial, and genetic determinants of HIV acquisition and transmission.

c. 2015

Consultant

The World Bank

Contributed modeling expertise to evaluate and improve HIV resource allocation tools for health policy.

2012-2014

Postdoctoral Fellow

Weill Cornell Medicine - Qatar

Examined spatial patterns of HIV and Hepatitis C, honing skills in advanced spatial statistics and GIS.

Completed 2012

Ph.D. in Biology

University of Kentucky

Doctoral dissertation on the epidemiological impact of co-infections on HIV transmission in sub-Saharan Africa.

B.Sc. in Biology

National University of Colombia

Foundation in biological sciences that sparked an interest in ecology and quantitative science.

Technical Expertise

AI-Human Interaction & Agent Systems

Geographic Information Systems (GIS)

Spatial Statistics, Geospatial AI & Modeling

Mathematical & Computational Epidemiology

Data Science, R, Python & Public Health Analytics

Global Research Footprint

My research spans five continents, involving universities, ministries of health, global health institutes, and data partnerships. This interactive map highlights projects where AI-human interaction, modeling, spatial epidemiology, and disease ecology support real-world decisions.

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