Cursos

• IIND-2107 Probabilidad y Estadística II
• IIND-4123 Statistical Learning for Data Analytics
• IIND-4114 Tópicos Avanzados en Estadística
• IIND-4100 Modelos Estadísticos Lineales
• IIND-4102 Métodos Estadísticos Multivariados
• MIIA-4100 Modelos de Análisis Estadístico
• MIIA-4101 Herramientas Computacionales para el Análisis de Datos
• MIIA-4200 Minería de Datos
• MIIA-4203 Modelos Avanzados Análisis de Datos 2
• MIIA-4202 Introducción Machine Learning
• MIIA-4405 Deep Learning

Investigación

Después de completar sus estudios de doctorado, Carlos Valencia ha estado trabajando en la Universidad de los Andes como profesor e investigador. Sus principales intereses de investigación son estadísticas aplicadas, modelos predictivos y aprendizaje automático. Específicamente, se enfoca en el estudio de métodos de regularización para la estimación funcional y problemas dimensionales elevados. Le gusta trabajar en la solución de problemas complejos que requieren análisis de datos.

PhD Students:

Graduated:

• Andrés Felipe Ramírez (2021)
• Diego Armando Salazar (2022)

Current:

• Santiago Castro Villarreal
• Carlos Guilllermo Ramírez
• Carlos Darío Valencia González
• Germán Andrés Sánches

Publicaciones

• Acevedo-Ramos, J. A., Valencia, C. F., & Valencia, C. D. (2023). The Environmental Kuznets Curve hypothesis for Colombia: impact of economic development on greenhouse gas emissions and ecological footprint. Sustainability, 15(4), 3738
• Quintero-Ossa, A. M., Solano, J., Jarcía, H., Zarruk, D., Bahnsen, A. C., & Valencia, C. (2022). Privacy-Preserving Machine Learning for Collaborative Data Sharing via Auto-encoder Latent Space Embeddings. arXiv preprint arXiv:2211.05717
• Abedrabbo, A. F., Osorio, J. C., Abolghasem, S., Valencia, C., & Rojas, F. (2022). Predicting subgrain size and dislocation density in machining-induced surface microstructure of nickel using supervised model-based learning. Materials Today Communications, 30, 103162
• Roa, L., Rodríguez-Rey, A., Correa-Bahnsen, A., & Arboleda, C. V. (2022). Supporting financial inclusion with graph machine learning and super-app alternative data. In Intelligent Systems and Applications: Proceedings of the 2021 Intelligent Systems Conference (IntelliSys) Volume 2 (pp. 216-230). Springer International Publishing
• Cabrales, S., Valencia, C., Ramírez, C., Ramírez, A., Herrera, J., & Cadena, A. (2022). Stochastic cost-benefit analysis to assess new infrastructure to improve the reliability of the natural gas supply. Energy, 246, 123421
• Salazar, D. A., Pržulj, N., & Valencia, C. F. (2021). Multi-project and Multi-profile joint Non-negative Matrix Factorization for cancer omic datasets. Bioinformatics, 37(24), 4801-4809
• Salazar, D., Rios, J., Aceros, S., Flórez-Vargas, O., & Valencia, C. (2021). Kernel joint non-negative matrix factorization for genomic data. IEEE Access, 9, 101863-101875
• Cepeda-Vega, A., Amaya-Gómez, R., Asuaje, M., Torres, C., Valencia, C., & Ratkovich, N. (2022). Pipeline two-phase flow pressure drop algorithm for multiple inclinations. Processes, 10(5), 1009
• Ramírez, A. F., & Valencia, C. (2021). Spatiotemporal correlation study of traffic accidents with fatalities and injuries in Bogota (Colombia). Accident Analysis & Prevention, 149, 105848
• Ramírez, A. F., Valencia, C. F., Cabrales, S., & Ramírez, C. G. (2021). Simulation of photo-voltaic power generation using copula autoregressive models for solar irradiance and air temperature time series. Renewable Energy, 175, 44-67
• Arias, A. F., Lamadrid, A., & Valencia, C. (2022, January). Virtual Power Plant Day Ahead Energy Unit Commitment. In Proceedings of the 55th Hawaii International Conference on System Sciences
• Castro-Villarreal, S., Beltran-Ostos, A., & Valencia, C. F. (2021). Estimation of Prevalence and Incremental Costs of Systemic Lupus Erythematosus in a Middle-Income Country Using Machine Learning on Administrative Health Data. Value in Health Regional Issues, 26, 98-104
• Suarez, G., Raful, J., Luque, M. A., Valencia, C. F., & Correa-Bahnsen, A. (2021). Enhancing User's Income Estimation with Super-App Alternative Data. arXiv preprint arXiv:2104.05831
• Sarmiento, C., Valencia, C., & Akhavan-Tabatabaei, R. (2018). Copula autoregressive methodology for the simulation of wind speed and direction time series. Journal of Wind Engineering and Industrial Aerodynamics, 174, 188-199
• Hernandez, J. S., Valencia, C., Ratkovich, N., Torres, C. F., & Muñoz, F. (2019). Data driven methodology for model selection in flow pattern prediction. Heliyon, 5(11), e02718
• Pulido, E. S., Arboleda, C. V., & Rodríguez Sánchez, J. P. (2019). Study of the spatiotemporal correlation between sediment-related blockage events in the sewer system in Bogotá (Colombia). Water Science and Technology, 79(9), 1727-1738
• Valencia, C., Cabrales, S., Garcia, L., Ramirez, J., & Calderona, D. (2019). Generalized additive model with embedded variable selection for bankruptcy prediction: Prediction versus interpretation. Cogent Economics & Finance, 7(1), 1597956
• Castro, Y., Huertas, C. A., Obando, C. E., & Valencia, C. F. (2019). Análisis de supervivencia para predicción de bancarrota: Caso de las industrias minoristas en Colombia. Revista ESPACIOS, 40(01)
• Shabbir, A. H., Zhang, J., Liu, X., Lutz, J. A., Valencia, C., & Johnston, J. D. (2019). Determining the sensitivity of grassland area burned to climate variation in Xilingol, China, with an autoregressive distributed lag approach. International Journal of Wildland Fire, 28(8), 628-639
• Shabbir, A. H., Zhang, J., Groninger, J. W., van Etten, E. J., Sarkodie, S. A., Lutz, J. A., & Valencia, C. F. (2020). Seasonal weather and climate prediction over area burned in grasslands of northeast China. Scientific Reports, 10(1), 19961
• Cabrales, S., Solano, J., Valencia, C., & Bautista, R. (2020). Pricing rainfall derivatives in the equatorial Pacific. Agricultural Finance Review, 80(4), 589-608
• Valencia-Arboleda, C. F., & Segura-Acosta, D. H. (2020). Estimativa das expectativas do mercado para seleção de portfólio usando modelos estatísticos penalizados. Revista científica, (38), 133-146
• Pulido, E. S., Arboleda, C. V., & Sánchez, J. P. R. (2019). Spatiotemporal Modelling of Sediment-Related Blockages in the Sewer System of Bogotá (Colombia). In New Trends in Urban Drainage Modelling: UDM 2018 11 (pp. 869-873). Springer International Publishing
• Morales, G. A., Morales, R. S., Valencia, C. F., & Akhavan-Tabatabaei, R. (2014, December). A forest fire propagation simulator for Bogotá. In Proceedings of the Winter Simulation Conference 2014 (pp. 1505-1515). IEEE
• Valencia, C., & Yuan, M. (2013). Radial basis function regularization for linear inverse problems with random noise. Journal of Multivariate Analysis, 116, 92-108