2026
Quantifying fairness in spatial predictive policing
Diego Hernández, Cristian Pulido, Francisco Gómez
Published in Artificial Intelligence and Law. Fairness
This article studies fairness in spatial predictive policing, evaluating how model outputs and operational deployment can produce uneven impacts across territories and population groups.
Quantifying fairness in spatial predictive policing
Diego Hernández, Cristian Pulido, Francisco Gómez
Published in Artificial Intelligence and Law. Fairness
This article studies fairness in spatial predictive policing, evaluating how model outputs and operational deployment can produce uneven impacts across territories and population groups.
2025
Uncertainty-Informed Framework for Enhancing Decision-Making in Emergency Response Management
Cristian Pulido, Francisco Gómez, Mario Arrieta-Prieto
Accepted at Simposio de Maestrías y Doctorados en Computación – SMD 2025 In Progress Decision Support
This work presents a doctoral research project in progress that explores how predictive uncertainty can be quantified and integrated into emergency response systems. The proposed framework combines Conformal Prediction and allocation strategies to improve transparency and adaptability in high-stakes decision-making.
Uncertainty-Informed Framework for Enhancing Decision-Making in Emergency Response Management
Cristian Pulido, Francisco Gómez, Mario Arrieta-Prieto
Accepted at Simposio de Maestrías y Doctorados en Computación – SMD 2025 In Progress Decision Support
This work presents a doctoral research project in progress that explores how predictive uncertainty can be quantified and integrated into emergency response systems. The proposed framework combines Conformal Prediction and allocation strategies to improve transparency and adaptability in high-stakes 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.
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 (* equal contribution)
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 (* equal contribution)
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.
2024
Assessing Intervention Impact: Robustness Analysis of Emergency Response Management
Cristian Pulido, Mario Arrieta-Prieto, Francisco Gómez
Submitted to MAPI3 – Tercera Conferencia Colombiana de Matemáticas Aplicadas e Industriales Robust Modeling
This study evaluates the robustness of predictive and allocation models in emergency response under intervention-induced behavioral changes. Results show that while robust predictors handle moderate interventions well, standard allocation models fail to adapt effectively, highlighting a key modeling gap.
Assessing Intervention Impact: Robustness Analysis of Emergency Response Management
Cristian Pulido, Mario Arrieta-Prieto, Francisco Gómez
Submitted to MAPI3 – Tercera Conferencia Colombiana de Matemáticas Aplicadas e Industriales Robust Modeling
This study evaluates the robustness of predictive and allocation models in emergency response under intervention-induced behavioral changes. Results show that while robust predictors handle moderate interventions well, standard allocation models fail to adapt effectively, highlighting a key modeling gap.
Resting state networks in patients with acute disorders of consciousness after severe traumatic brain injury
Edgar G. Ordóñez-Rubiano, Marcelo A. Castañeda-Duarte, Laura Baeza-Antón, Jorge A. Romo-Quebradas, Juan P. Perilla-Estrada, Tito A. Perilla-Cepeda, Cesar O. Enciso-Olivera, Jorge Rudas, Jorge H. Marín-Muñoz, Cristian Pulido, Francisco Gómez, Darwin Martínez, Oscar Zorro, Emilio Garzón, Javier G. Patiño-Gómez
Clinical Neurology and Neurosurgery 2024 Neuroimaging
This study describes resting state network alterations in patients with disorders of consciousness after severe TBI. Findings reveal three distinct RSN activation patterns—normal, asymmetric, and absent—highlighting significant disruptions compared to healthy controls.
Resting state networks in patients with acute disorders of consciousness after severe traumatic brain injury
Edgar G. Ordóñez-Rubiano, Marcelo A. Castañeda-Duarte, Laura Baeza-Antón, Jorge A. Romo-Quebradas, Juan P. Perilla-Estrada, Tito A. Perilla-Cepeda, Cesar O. Enciso-Olivera, Jorge Rudas, Jorge H. Marín-Muñoz, Cristian Pulido, Francisco Gómez, Darwin Martínez, Oscar Zorro, Emilio Garzón, Javier G. Patiño-Gómez
Clinical Neurology and Neurosurgery 2024 Neuroimaging
This study describes resting state network alterations in patients with disorders of consciousness after severe TBI. Findings reveal three distinct RSN activation patterns—normal, asymmetric, and absent—highlighting significant disruptions compared to healthy controls.
Predicting Tweet Posting Behavior on Citizen Security: A Hawkes Point Process Analysis
Cristian Pulido, Francisco Gómez
Submitted to arXiv & Engineering Applications of Artificial Intelligence. Under review. 2024 Social Sensing
This study presents a predictive model for anticipating short-term Perception of Security using social network data. The model incorporates external factors and repost dynamics, offering interpretable and timely insights for proactive security planning.
Predicting Tweet Posting Behavior on Citizen Security: A Hawkes Point Process Analysis
Cristian Pulido, Francisco Gómez
Submitted to arXiv & Engineering Applications of Artificial Intelligence. Under review. 2024 Social Sensing
This study presents a predictive model for anticipating short-term Perception of Security using social network data. The model incorporates external factors and repost dynamics, offering interpretable and timely insights for proactive security planning.
Caracterización, identificación y cuantificación de las barreras de acceso al diagnóstico en el sector porcino colombiano
Natalia Rodríguez Castañeda, Cristian Pulido, Clara Marcela Rodríguez Moreno, Fausto Camilo Moreno Vásquez, Gloria Cristina Córdoba Currea, Francisco Gómez
Revista de Medicina Veterinaria 2021 Animal Health
This study identifies and quantifies key barriers limiting access to veterinary diagnostic services among pig producers in Colombia. Training-related barriers were the most critical, highlighting needs for informed strategies to combat antimicrobial resistance.
Caracterización, identificación y cuantificación de las barreras de acceso al diagnóstico en el sector porcino colombiano
Natalia Rodríguez Castañeda, Cristian Pulido, Clara Marcela Rodríguez Moreno, Fausto Camilo Moreno Vásquez, Gloria Cristina Córdoba Currea, Francisco Gómez
Revista de Medicina Veterinaria 2021 Animal Health
This study identifies and quantifies key barriers limiting access to veterinary diagnostic services among pig producers in Colombia. Training-related barriers were the most critical, highlighting needs for informed strategies to combat antimicrobial resistance.
2023
Assessing Impartiality in Predictive Security: A Comprehensive Analysis of Predictive Models
Diego Hernández, Cristian Pulido, Francisco Gómez
Second Ibero-American Symposium of Master and Doctorate in Artificial Intelligence 2023 Fairness
This work analyzes fairness in three commonly used predictive policing models, focusing on disparities across protected variables. Results show consistent fairness levels across models, despite limited correlation between fairness and accuracy, emphasizing the need for just algorithmic strategies in public security.
Assessing Impartiality in Predictive Security: A Comprehensive Analysis of Predictive Models
Diego Hernández, Cristian Pulido, Francisco Gómez
Second Ibero-American Symposium of Master and Doctorate in Artificial Intelligence 2023 Fairness
This work analyzes fairness in three commonly used predictive policing models, focusing on disparities across protected variables. Results show consistent fairness levels across models, despite limited correlation between fairness and accuracy, emphasizing the need for just algorithmic strategies in public security.
Application of artificial intelligence in the qualitative analysis of needs and strategies of pig producers in the Context of Antimicrobial Resistance
Fausto Moreno, Cristian Pulido, Francisco Gómez, Erika D. Camacho, María F. Naranjo, Mario E. Peña, Fernando Rojas, Diana C. Zambrano
Revista Colombiana de Ciencias Pecuarias, Vol. 37(1), 2024 2024 AMR & Animal Health
This study applied Natural Language Processing to analyze interviews and focus group data from the swine sector, identifying 52 needs and 38 strategies related to veterinary diagnostics and antimicrobial resistance. Key priorities included training and technical assistance, supporting more efficient and data-driven decision-making processes.
Application of artificial intelligence in the qualitative analysis of needs and strategies of pig producers in the Context of Antimicrobial Resistance
Fausto Moreno, Cristian Pulido, Francisco Gómez, Erika D. Camacho, María F. Naranjo, Mario E. Peña, Fernando Rojas, Diana C. Zambrano
Revista Colombiana de Ciencias Pecuarias, Vol. 37(1), 2024 2024 AMR & Animal Health
This study applied Natural Language Processing to analyze interviews and focus group data from the swine sector, identifying 52 needs and 38 strategies related to veterinary diagnostics and antimicrobial resistance. Key priorities included training and technical assistance, supporting more efficient and data-driven decision-making processes.
Usage of graphs in the analysis of pig movements to identify high-risk nodes in the transmission of PRRS
Fausto Moreno, Cristian Pulido, Francisco Gómez, Andrés J. Bermúdez, María F. Naranjo, Mario E. Peña, Fernando Rojas
Revista Colombiana de Ciencias Pecuarias, Vol. 37(1), 2024 2024 Animal Health
This study uses temporal network analysis of pig movements in Colombia to identify municipalities at higher risk of PRRS. The model enables prioritization for epidemiological surveillance, supporting proactive disease prevention strategies.
Usage of graphs in the analysis of pig movements to identify high-risk nodes in the transmission of PRRS
Fausto Moreno, Cristian Pulido, Francisco Gómez, Andrés J. Bermúdez, María F. Naranjo, Mario E. Peña, Fernando Rojas
Revista Colombiana de Ciencias Pecuarias, Vol. 37(1), 2024 2024 Animal Health
This study uses temporal network analysis of pig movements in Colombia to identify municipalities at higher risk of PRRS. The model enables prioritization for epidemiological surveillance, supporting proactive disease prevention strategies.
2022
Prediction based on time-series of aggressive behaviors. A case study Bogotá, Colombia
Jorge Victorino, Miguel Barrero, Jorge Rudas, Cristian Pulido, Luisa Fernanda Chaparro, Camilo Estrada, Luz Ángela Narváez, Francisco Gómez
2022 International Symposium on Electrical, Electronics and Information Engineering (ISEEIE) 2022 Security & Behavior
This study presents a multi-scale, periodicity-based model to predict aggressive behavior incidents using historical data. The approach achieves high precision with an average relative error of 9.8%, outperforming existing methods.
Prediction based on time-series of aggressive behaviors. A case study Bogotá, Colombia
Jorge Victorino, Miguel Barrero, Jorge Rudas, Cristian Pulido, Luisa Fernanda Chaparro, Camilo Estrada, Luz Ángela Narváez, Francisco Gómez
2022 International Symposium on Electrical, Electronics and Information Engineering (ISEEIE) 2022 Security & Behavior
This study presents a multi-scale, periodicity-based model to predict aggressive behavior incidents using historical data. The approach achieves high precision with an average relative error of 9.8%, outperforming existing methods.
2021
Highly sessional aggressive behaviors link to temporal dynamics shared across space
Jorge Victorino, Jorge Rudas, Ana María Reyes, Cristian Pulido, Luisa Fernanda Chaparro, Camilo Estrada, Luz Ángela Narváez, Francisco Gómez
IEEE Access 2021 Security & Behavior
This study analyzes over three million emergency reports to uncover sessional and shared temporal patterns of aggressive behavior in Bogotá. Findings reveal high predictability in key city areas, supporting routine activity theory as a lens for crime prevention.
Highly sessional aggressive behaviors link to temporal dynamics shared across space
Jorge Victorino, Jorge Rudas, Ana María Reyes, Cristian Pulido, Luisa Fernanda Chaparro, Camilo Estrada, Luz Ángela Narváez, Francisco Gómez
IEEE Access 2021 Security & Behavior
This study analyzes over three million emergency reports to uncover sessional and shared temporal patterns of aggressive behavior in Bogotá. Findings reveal high predictability in key city areas, supporting routine activity theory as a lens for crime prevention.
Structural and functional connectivity of the ascending arousal network for prediction of outcome in patients with acute disorders of consciousness
Cesar O. Enciso-Olivera, Edgar G. Ordóñez-Rubiano, Rosangela Est. Casanova-Libreros, Diana P. Rivera-Triana, Carol J. Zarate-Ardila, Jorge Rudas, Cristian Pulido, Francisco Gómez, Darwin Martínez, Natalia Guerrero, Mayra A. Hurtado, Natalia Aguilera-Bustos, Clara P. Hernández-Torres, José Hernandez, Jorge H. Marín-Muñoz
Nature Publishing Group UK London 2021 Neuroimaging
This study evaluates early BOLD and DTI imaging as predictors of neurological outcomes in comatose patients with TBI, CPA, or stroke. Results highlight structural and functional connectivity markers in the ascending arousal network as potential outcome biomarkers.
Structural and functional connectivity of the ascending arousal network for prediction of outcome in patients with acute disorders of consciousness
Cesar O. Enciso-Olivera, Edgar G. Ordóñez-Rubiano, Rosangela Est. Casanova-Libreros, Diana P. Rivera-Triana, Carol J. Zarate-Ardila, Jorge Rudas, Cristian Pulido, Francisco Gómez, Darwin Martínez, Natalia Guerrero, Mayra A. Hurtado, Natalia Aguilera-Bustos, Clara P. Hernández-Torres, José Hernandez, Jorge H. Marín-Muñoz
Nature Publishing Group UK London 2021 Neuroimaging
This study evaluates early BOLD and DTI imaging as predictors of neurological outcomes in comatose patients with TBI, CPA, or stroke. Results highlight structural and functional connectivity markers in the ascending arousal network as potential outcome biomarkers.
Quantifying perception of security through social media and its relationship with crime
Luisa Fernanda Chaparro, Cristian Pulido, Jorge Rudas, Jorge Victorino, Ana María Reyes, Camilo Estrada, Luz Ángela Narváez, Francisco Gómez
IEEE Access 2021 Social Sensing
This study proposes a machine learning model to quantify the Perception of Security on Twitter using sentiment analysis and crime-related filtering. Results reveal meaningful distinctions from traditional content-counting methods and dynamic links with specific crimes like robbery.
Quantifying perception of security through social media and its relationship with crime
Luisa Fernanda Chaparro, Cristian Pulido, Jorge Rudas, Jorge Victorino, Ana María Reyes, Camilo Estrada, Luz Ángela Narváez, Francisco Gómez
IEEE Access 2021 Social Sensing
This study proposes a machine learning model to quantify the Perception of Security on Twitter using sentiment analysis and crime-related filtering. Results reveal meaningful distinctions from traditional content-counting methods and dynamic links with specific crimes like robbery.
Interpretability Of The Perception Of Security Based On Tweets Content
Luisa Fernanda Chaparro, Cristian Pulido, Jorge Rudas, Ana María Reyes, Jorge Victorino, Luz Ángela Narváez, Darwin Martínez, Francisco Gómez
2021 International Conference on Applied Artificial Intelligence (ICAPAI) 2021 Security
This study presents a supervised learning approach to quantify the Perception of Security using Twitter data, with an emphasis on model interpretability. A case study in Bogotá demonstrates its viability as the first local application of social media for PoS analysis.
Interpretability Of The Perception Of Security Based On Tweets Content
Luisa Fernanda Chaparro, Cristian Pulido, Jorge Rudas, Ana María Reyes, Jorge Victorino, Luz Ángela Narváez, Darwin Martínez, Francisco Gómez
2021 International Conference on Applied Artificial Intelligence (ICAPAI) 2021 Security
This study presents a supervised learning approach to quantify the Perception of Security using Twitter data, with an emphasis on model interpretability. A case study in Bogotá demonstrates its viability as the first local application of social media for PoS analysis.
Prediction of Perception of Security Using Social Media Content
Cristian Pulido, Luisa Fernanda Chaparro, Jorge Rudas, Jorge Victorino, Camilo Estrada, Luz Ángela Narváez, Francisco Gómez
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 25th Iberoamerican Congress, CIARP 2021, Porto, Portugal, May 10--13, 2021, Revised Selected Papers 25 2021 Security
This work proposes a predictive model to quantify and anticipate the Perception of Security using social media data. The approach incorporates external influences and retweet dynamics, offering interpretable and competitive short-term forecasts.
Prediction of Perception of Security Using Social Media Content
Cristian Pulido, Luisa Fernanda Chaparro, Jorge Rudas, Jorge Victorino, Camilo Estrada, Luz Ángela Narváez, Francisco Gómez
Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications: 25th Iberoamerican Congress, CIARP 2021, Porto, Portugal, May 10--13, 2021, Revised Selected Papers 25 2021 Security
This work proposes a predictive model to quantify and anticipate the Perception of Security using social media data. The approach incorporates external influences and retweet dynamics, offering interpretable and competitive short-term forecasts.
Multimodal prediction of aggressive behavior occurrence using a decision-level approach
Ana María Reyes, Jorge Rudas, Cristian Pulido, Luisa Fernanda Chaparro, Jorge Victorino, Luz Ángela Narváez, Darwin Martínez, Francisco Gómez
11th International Conference of Pattern Recognition Systems (ICPRS 2021) 2021 Security
This study proposes a decision-level data fusion approach to improve the prediction of aggressive behavior using multiple data sources. While fusion enhances hotspot detection, it increases prediction error and produces more complex spatial patterns.
Multimodal prediction of aggressive behavior occurrence using a decision-level approach
Ana María Reyes, Jorge Rudas, Cristian Pulido, Luisa Fernanda Chaparro, Jorge Victorino, Luz Ángela Narváez, Darwin Martínez, Francisco Gómez
11th International Conference of Pattern Recognition Systems (ICPRS 2021) 2021 Security
This study proposes a decision-level data fusion approach to improve the prediction of aggressive behavior using multiple data sources. While fusion enhances hotspot detection, it increases prediction error and produces more complex spatial patterns.
2020
Sentiment analysis of social network content to characterize the perception of security
Luisa Fernanda Chaparro, Cristian Pulido, Jorge Rudas, Ana María Reyes, Jorge Victorino, Luz Ángela Narváez, Francisco Gómez, Darwin Martínez
2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) 2020 Security
This study proposes a method to quantify the perception of security in Bogotá using sentiment analysis on Spanish-language Twitter data. The approach combines rule-based and supervised learning techniques to overcome limitations of traditional surveys.
Sentiment analysis of social network content to characterize the perception of security
Luisa Fernanda Chaparro, Cristian Pulido, Jorge Rudas, Ana María Reyes, Jorge Victorino, Luz Ángela Narváez, Francisco Gómez, Darwin Martínez
2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) 2020 Security
This study proposes a method to quantify the perception of security in Bogotá using sentiment analysis on Spanish-language Twitter data. The approach combines rule-based and supervised learning techniques to overcome limitations of traditional surveys.
Spatial-temporal patterns of aggressive behaviors. A case study Bogotá, Colombia
Jorge Victorino, Jorge Rudas, Ana María Reyes, Cristian Pulido, Luisa Fernanda Chaparro, Darwin Martínez, Luz Ángela Narváez, Francisco Gómez
2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) 2020 Security
This study presents a method to identify spatio-temporal patterns of aggressive behavior in Bogotá using rhythm and tempo metrics inspired by routine activity theory. Findings reveal shared behavioral dynamics across city zones, enabling targeted mitigation strategies.
Spatial-temporal patterns of aggressive behaviors. A case study Bogotá, Colombia
Jorge Victorino, Jorge Rudas, Ana María Reyes, Cristian Pulido, Luisa Fernanda Chaparro, Darwin Martínez, Luz Ángela Narváez, Francisco Gómez
2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) 2020 Security
This study presents a method to identify spatio-temporal patterns of aggressive behavior in Bogotá using rhythm and tempo metrics inspired by routine activity theory. Findings reveal shared behavioral dynamics across city zones, enabling targeted mitigation strategies.
Consistent spatial decomposition of temporal occurrence of aggressive behaviors: A case study in Bogotá, Colombia
Jorge Rudas, Ana María Reyes, Cristian Pulido, Luisa Fernanda Chaparro, Jorge Victorino, Luz Ángela Narváez, Darwin Martínez, Francisco Gómez
2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) 2020 Security
This study uses source decomposition to identify consistent and independent activity patterns underlying aggressive behaviors in Bogotá. Results suggest these events stem from reproducible sources observable across multiple spatial scales.
Consistent spatial decomposition of temporal occurrence of aggressive behaviors: A case study in Bogotá, Colombia
Jorge Rudas, Ana María Reyes, Cristian Pulido, Luisa Fernanda Chaparro, Jorge Victorino, Luz Ángela Narváez, Darwin Martínez, Francisco Gómez
2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) 2020 Security
This study uses source decomposition to identify consistent and independent activity patterns underlying aggressive behaviors in Bogotá. Results suggest these events stem from reproducible sources observable across multiple spatial scales.
An evolutionary algorithm for reducing fear of crime
Cristian Pulido, Ana María Reyes, Jorge Rudas, Jorge Victorino, Darwin Martínez, Luz Ángela Narváez, Francisco Gómez
2020 7th International Conference on Behavioural and Social Computing (BESC) 2020 Spotlight Security
This work proposes an optimization-based method to design policies that reduce fear of crime using mathematical models and evolutionary algorithms. Findings highlight the value of fostering intergroup interactions to enhance cohesion and reduce fear among vulnerable populations.
An evolutionary algorithm for reducing fear of crime
Cristian Pulido, Ana María Reyes, Jorge Rudas, Jorge Victorino, Darwin Martínez, Luz Ángela Narváez, Francisco Gómez
2020 7th International Conference on Behavioural and Social Computing (BESC) 2020 Spotlight Security
This work proposes an optimization-based method to design policies that reduce fear of crime using mathematical models and evolutionary algorithms. Findings highlight the value of fostering intergroup interactions to enhance cohesion and reduce fear among vulnerable populations.
Characterization of temporal patterns in the occurrence of aggressive behaviors in Bogotá (Colombia)
Ana María Reyes, Jorge Rudas, Cristian Pulido, Jorge Victorino, Darwin Martínez, Luz Ángela Narváez, Francisco Gómez
2020 7th International Conference on Behavioural and Social Computing (BESC) 2020 Behavior Analysis
This study analyzes temporal patterns of aggressive behaviors in Bogotá using Colwell’s predictability metrics. Results reveal spatial differences in predictability, suggesting the presence of cyclic trends useful for improving violence forecasting.
Characterization of temporal patterns in the occurrence of aggressive behaviors in Bogotá (Colombia)
Ana María Reyes, Jorge Rudas, Cristian Pulido, Jorge Victorino, Darwin Martínez, Luz Ángela Narváez, Francisco Gómez
2020 7th International Conference on Behavioural and Social Computing (BESC) 2020 Behavior Analysis
This study analyzes temporal patterns of aggressive behaviors in Bogotá using Colwell’s predictability metrics. Results reveal spatial differences in predictability, suggesting the presence of cyclic trends useful for improving violence forecasting.
Establishing an acquisition and processing protocol for resting state networks with a 1.5 T scanner: a case series in a middle-income country
Michela Moreno-Ayure, Cristian Páes, María A. López-Arias, Johan Mendez-Betancurt, Edgar G. Ordóñez-Rubiano, Jorge Rudas, Cristian Pulido, Francisco Gómez, Darwin Martínez, Cesar O. Enciso-Olivera, Diana P. Rivera-Triana, Rosangela Est. Casanova-Libreros, Natalia Aguilera, Jorge H. Marín-Muñoz
Medicine 2020 Neuroimaging
This study demonstrates that key resting state networks can be reliably identified using sICA on 1.5T fMRI scans in healthy individuals. Results support the feasibility of RSN analysis in middle-income settings using accessible imaging technology.
Establishing an acquisition and processing protocol for resting state networks with a 1.5 T scanner: a case series in a middle-income country
Michela Moreno-Ayure, Cristian Páes, María A. López-Arias, Johan Mendez-Betancurt, Edgar G. Ordóñez-Rubiano, Jorge Rudas, Cristian Pulido, Francisco Gómez, Darwin Martínez, Cesar O. Enciso-Olivera, Diana P. Rivera-Triana, Rosangela Est. Casanova-Libreros, Natalia Aguilera, Jorge H. Marín-Muñoz
Medicine 2020 Neuroimaging
This study demonstrates that key resting state networks can be reliably identified using sICA on 1.5T fMRI scans in healthy individuals. Results support the feasibility of RSN analysis in middle-income settings using accessible imaging technology.
La importancia de la estructura de comunicación de una comunidad para la reducción del miedo al crimen
Cristian Pulido, Director: Francisco Gómez
Bogotá-Ciencias-Maestría en Ciencias-Matemática Aplicada 2020 Social Modeling
This study extends a mathematical model of fear of crime to assess the impact of communication structures on its propagation. Results show that cohesive, community-based networks can help reduce fear levels, especially among highly victimized groups.
La importancia de la estructura de comunicación de una comunidad para la reducción del miedo al crimen
Cristian Pulido, Director: Francisco Gómez
Bogotá-Ciencias-Maestría en Ciencias-Matemática Aplicada 2020 Social Modeling
This study extends a mathematical model of fear of crime to assess the impact of communication structures on its propagation. Results show that cohesive, community-based networks can help reduce fear levels, especially among highly victimized groups.
2019
How the social interactions in communities affect the fear of crime
Cristian Pulido, Jeisson Prieto, Francisco Gómez
Systems Research and Behavioral Science 2019 Social Modeling
This study examines how community-based communication networks shape the spread of fear of crime. Results show that such structures may isolate fear within vulnerable groups, deepening perception gaps across social strata.
How the social interactions in communities affect the fear of crime
Cristian Pulido, Jeisson Prieto, Francisco Gómez
Systems Research and Behavioral Science 2019 Social Modeling
This study examines how community-based communication networks shape the spread of fear of crime. Results show that such structures may isolate fear within vulnerable groups, deepening perception gaps across social strata.
The Role of Communities in the Fear of Crime
Cristian Pulido, Francisco Gómez
2019 4th World Conference on Complex Systems (WCCS) 2019 Social Modeling
This work analyzes how community structure in social networks influences the spread of fear of crime. Results show that such structure can isolate fear within vulnerable groups, affecting perception and policy design.
The Role of Communities in the Fear of Crime
Cristian Pulido, Francisco Gómez
2019 4th World Conference on Complex Systems (WCCS) 2019 Social Modeling
This work analyzes how community structure in social networks influences the spread of fear of crime. Results show that such structure can isolate fear within vulnerable groups, affecting perception and policy design.
2017
Series finitas de fourier y caracteres de dirichlet
Cristian Pulido, Director: Milton Lesmes
Universidad Distrital Francisco José de Caldas 2017 Theoretical Math
This work explores Dirichlet characters and Gauss sums, using Lagrange interpolation to compute their finite Fourier series representations.
Series finitas de fourier y caracteres de dirichlet
Cristian Pulido, Director: Milton Lesmes
Universidad Distrital Francisco José de Caldas 2017 Theoretical Math
This work explores Dirichlet characters and Gauss sums, using Lagrange interpolation to compute their finite Fourier series representations.