  | Bigi, F., Bosi, T., Pineda Jaramillo, J. D., Viti, F., & D'Ariano, A. (2023). ADDRESSING THE IMPACT OF MAINTENANCE IN SHUNTING OPERATIONS THROUGH SHUNT-IN POLICIES FOR FREIGHT TRAINS OPERATIONS [Paper presentation]. Transportation Research Board (TRB) 102nd Annual Meeting. |
  | Bigi, F., Bosi, T., Pineda Jaramillo, J. D., D'Ariano, A., & Viti, F. (2023). ADDRESSING THE IMPACT OF MAINTENANCE IN SHUNTING OPERATIONS THROUGH SHUNT-IN POLICIES FOR FREIGHT TRAINS OPERATIONS [Paper presentation]. Transportation Research Board (TRB) 102nd Annual Meeting. |
 | Pineda Jaramillo, J. D., & Viti, F. (2023). Identifying the rail operating features associated to intermodal freight rail operation delays. Transportation Research. Part C, Emerging Technologies, 147, 103993. doi:10.1016/j.trc.2022.103993  Peer Reviewed verified by ORBi |
 | Mesa Arango, R., Pineda Jaramillo, J. D., Araujo, D., Bi, J., Basva, M., & Viti, F. (2023). Missions and factors determining the demand for affordable mass space tourism in the United States: A machine learning approach. Acta Astronautica, 204, 307-320. doi:10.1016/j.actaastro.2023.01.006 Peer Reviewed verified by ORBi |
 | Bigi, F., Bosi, T., Pineda Jaramillo, J. D., D'Ariano, A., & Viti, F. (02 June 2022). The Wagon Assignment Policy problem: Policy Comparison on the Wagon Fleet optimization [Paper presentation]. European Association for Research in Transportation (hEART) 2022. |
 | Fazio, M., Vitello, P., Pineda Jaramillo, J. D., Connors, R., & Viti, F. (2022). A Classification Approach Using Machine Learning for Predicting Traffic Flows in Areas with Missing Sensors. In Transportation Research Board 101st Annual Meeting. Peer reviewed |
 | Pineda Jaramillo, J. D., Barrera-Jimenez, H., & Mesa-Arango, R. (2022). Unveiling the relevance of traffic enforcement cameras on the severity of vehicle--pedestrian collisions in an urban environment with machine learning models. Journal of Safety Research. doi:10.1016/j.jsr.2022.02.014 Peer reviewed |
 | Pineda Jaramillo, J. D., & Arbelaez-Arenas, O. (2022). Assessing the Performance of Gradient-Boosting Models for Predicting the Travel Mode Choice Using Household Survey Data. Journal of Urban Planning and Development, 148 (2), 04022007. doi:10.1061/(ASCE)UP.1943-5444.0000830 Peer reviewed |
 | Pineda Jaramillo, J. D., McDonald, W., Zheng, W., & Viti, F. (2022). Identifying the Major Causes Associated to Rail Intermodal Operation Disruptions Using Causal Machine Learning. In Transportation Research Board 101st Annual Meeting. Peer reviewed |
 | Pineda Jaramillo, J. D., & Pineda-Jaramillo, D. (2021). Analysing travel satisfaction of tourists towards a metro system from unstructured data. Research in Transportation Business and Management. doi:10.1016/j.rtbm.2021.100746 Peer Reviewed verified by ORBi |
 | Pineda Jaramillo, J. D. (2021). Travel time, trip frequency and motorised-vehicle ownership: A case study of travel behaviour of people with reduced mobility in Medellin. Journal of Transport and Health, 22, 101110. doi:10.1016/j.jth.2021.101110 Peer reviewed |
 | Pineda Jaramillo, J. D., Martinez-Fernandez, P., Villalba-Sanchis, I., Salvador-Zuriaga, P., & Insa-Franco, R. (2021). Predicting the traction power of metropolitan railway lines using different machine learning models. International Journal of Rail Transportation, 461--478. doi:10.1080/23248378.2020.1829513 Peer reviewed |
 | Pineda Jaramillo, J. D., & Arbelaez-Arenas, O. (2021). Modelling road traffic collisions using clustered zones based on Foursquare data in Medellin. Case Studies on Transport Policy, 9 (2), 958--964. doi:10.1016/j.cstp.2021.04.016 Peer reviewed |
 | Pineda Jaramillo, J. D. (2020). A Shallow Neural Network approach for identifying the leading causes associated to pedestrian deaths in Medellín. Journal of Transport Health. doi:10.1016/j.jth.2020.100912 Peer reviewed |
 | Pineda Jaramillo, J. D., & Sarmiento, I. (2020). Traction system choice for the Multipurpose Railway of Antioquia. Revista EIA. doi:10.24050/reia.v17i34.1406 Peer reviewed |