Dunfrey Aragão is an Associate Professor and AI/ML scientist with 11 years of experience building end-to-end machine learning systems for public health, security, and industry. He holds a Ph.D. in Computer Engineering and an MBA in IT Management, and combines deep-learning time-series expertise with practical pipeline engineering (Python, TensorFlow, Pandas) to deliver actionable forecasts for diseases like COVID-19, dengue and Zika. His research blends neural architectures (LSTMs, attention/Transformers) with geospatial and socio-demographic data, translating models into policy-relevant insights and open-source tools. As an educator and mentor he designs systems and networking curricula while supervising multidisciplinary student projects that bridge academia and government. He has international research experience as a visiting fellow in Italy and a track record of high-impact publications and collaborations with public health agencies. Less obvious: he pairs rigorous computational modeling with operational deployment experience, having built dashboards and reproducible pipelines that moved prototypes into real-world decision support.
10 years of coding experience
4 years of employment as a software developer
Federal University of Rio Grande do Norte
Master Computer Science, Signs, digital and graphics systems, Master Computer Science, Signs, digital and graphics systems at Universidade Federal da Paraíba
Machine Learning: From Data to Decisions, Machine Learning: From Data to Decisions at MIT Professional Education
Master of Business Administration (MBA), Information Technology Management, Master of Business Administration (MBA), Information Technology Management at Faculdades Metropolitanas Unidas
Bachelor of Technology (B.Tech.), Telecommunications Technology/Technician, Bachelor of Technology (B.Tech.), Telecommunications Technology/Technician at Instituto Federal de Educação, Ciência e Tecnologia da Paraíba
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