PhD Student in Systems and Computer Engineering
Data Science ResearcherI am a mathematician with a strong background in applied modeling and computational analysis. My current work focuses on the integration of uncertainty-aware predictive models into decision-making processes for complex systems.
Through my doctoral research, I focus on integrating uncertainty into predictive models to improve decision-making in emergency response systems. I study how incomplete information and intervention-induced behavioral changes affect planning and resource allocation. At DataLab, I contribute to the development of data-driven tools for assessing health risks, optimizing interventions, and supporting public sector decision-making.
Security & Crime Prediction · Animal Health & Epidemiology · Decision Support Systems · Network Modeling
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Universidad Nacional de Colombia, Bogotá D.C., Colombia.Department of Systems and Industrial Engineering
Ph.D. StudentAug. 2023 - present -
Université Laval (Quebec, Canada) / CERVO Research CentreVisiting Ph.D. Research Intern (ELAP Mobility Stay)Jan. 12, 2026 – May 7, 2026 -
Universidad Nacional de Colombia, Bogotá D.C., Colombia.Department of Mathematics
M.Sc. in Applied MathematicsFeb. 2018 - Nov. 2020 -
Universidad Distrital Francisco José de Caldas, Bogotá D.C., Colombia.Faculty of Science and Education
B.Sc. in MathematicsFeb. 2011 – Apr. 2017
Experience
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DataLab – Universidad Nacional de ColombiaResearcher in Predictive AnalyticsDec. 2019 – Present
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Universidad Antonio Nariño (UAN)Adjunct Professor (Lecturer 2022–2024, Adjunct from 2024)Feb. 2022 – Dec. 2025 -
ViveLab BogotáResearcher in Emerging TechnologiesJun. 2019 – Sep. 2019 -
Fundación Universitaria de Ciencias de la SaludResearch Assistant – Medical ImagingMar. 2018 – Nov. 2019
Honors & Awards
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Best Student Paper Award - 7th Int. Conference on Behavioral and Social Computing (BESC)2020
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Emerging Leaders in the Americas Program (ELAP) Scholarship – Government of Canada. Selected for the ELAP scholarship funded by Global Affairs Canada to carry out a 4-month doctoral research stay at Université Laval (Quebec, Canada) from Jan. 12, 2026 to May 7, 2026.2025
Selected Publications (view all )
Quantifying representational mismatch between narratives and structured reports in near-death experiences
Cristian Pulido, Francisco Gómez, Prejaas K. B. Tewarie, Roxane S. Hoyer†, Steven Laureys† († co-senior authors)
Submitted to Consciousness and Cognition Under ReviewConsciousness
This study examines representational mismatch between narrative and questionnaire-based reports of near-death experiences. Results show systematic but incomplete correspondence across emotional tone, experiential features, and life changes, suggesting that disagreement across formats reflects a structured property of reporting rather than extraction error alone.
[Journal] [Review Status] [Preprint DOI] [Web Page] [Demo] [Video] [Code]
Quantifying representational mismatch between narratives and structured reports in near-death experiences
Cristian Pulido, Francisco Gómez, Prejaas K. B. Tewarie, Roxane S. Hoyer†, Steven Laureys† († co-senior authors)
Submitted to Consciousness and Cognition Under ReviewConsciousness
This study examines representational mismatch between narrative and questionnaire-based reports of near-death experiences. Results show systematic but incomplete correspondence across emotional tone, experiential features, and life changes, suggesting that disagreement across formats reflects a structured property of reporting rather than extraction error alone.
[Journal] [Review Status] [Preprint DOI] [Web Page] [Demo] [Video] [Code]
Quantifying Predictive Uncertainty in Crime Forecasting using Conformal Prediction
Cristian Pulido, Francisco Gómez
Accepted at 19° Congreso Colombiano de Computación (CCCesp 2025) SecurityUncertainty
This work presents a model-agnostic framework using Conformal Prediction to generate calibrated prediction intervals for crime hotspot forecasting. Applied to Chicago data, it reveals spatial variations in prediction confidence, highlighting the value of uncertainty in decision-making.
Quantifying Predictive Uncertainty in Crime Forecasting using Conformal Prediction
Cristian Pulido, Francisco Gómez
Accepted at 19° Congreso Colombiano de Computación (CCCesp 2025) SecurityUncertainty
This work presents a model-agnostic framework using Conformal Prediction to generate calibrated prediction intervals for crime hotspot forecasting. Applied to Chicago data, it reveals spatial variations in prediction confidence, highlighting the value of uncertainty in decision-making.
A Question-Driven AI Framework for Early-Stage Territorial Decision Support
Cristian Pulido*, Oscar Sánchez*, Diana Aldana, Juan Diego Murcia, Sarah Coral, Francisco Gómez (* co-first authors)
Accepted at 19° Congreso Colombiano de Computación (CCCesp 2025) Spotlight Decision Support
This work introduces a modular AI framework combining guiding questions with LLM-based assistants to support early-stage territorial planning in Colombia. Two assistants—traditional RAG and agentic RAG—were evaluated, showing improved response quality and usefulness.
A Question-Driven AI Framework for Early-Stage Territorial Decision Support
Cristian Pulido*, Oscar Sánchez*, Diana Aldana, Juan Diego Murcia, Sarah Coral, Francisco Gómez (* co-first authors)
Accepted at 19° Congreso Colombiano de Computación (CCCesp 2025) Spotlight Decision Support
This work introduces a modular AI framework combining guiding questions with LLM-based assistants to support early-stage territorial planning in Colombia. Two assistants—traditional RAG and agentic RAG—were evaluated, showing improved response quality and usefulness.