Trilce Encarnación, PhD
Dr. Encarnación’s research and teaching interests focus on data analytics applications in humanitarian operations, post-disaster environments and city logistics. Her work is focused on improving disaster response efforts by leveraging on emerging data sources, including social media data. Moreover, she conducts empirical research to understand behavioral responses to disasters and their implications for response operations. Prior to her academic career, she worked in industry for close to a decade, as a consultant and holding management positions in Business Analytics.
Ph.D. Transportation Engineering, Rensselaer Polytechnic Institute, 2019
M.E. Industrial and Management Engineering, Rensselaer Polytechnic Institute, 2017
M.S. Scientific Computing, University of Puerto Rico at Mayaguez, 2006
B.S. Systems Engineering and Computer Science Cum Laude, Pontificia Universidad Católica Madre y Maestra, Dominican Republic, 2002
Dr. Encarnacion's research focuses on the development and use of econometric, analytical modeling, and statistical analysis methods to guide decision making in disaster response logistics. Her work explores the implications of behavioral considerations unique to post-disaster environments in relief operations. She is also interested in leveraging social media and new data to improve disaster response.
Holguín-Veras J., Encarnación T., Ramirez-Rios D., He X., Kalahasthi L., Perez-Guzman S., Sanchez-Díaz I., González-Calderón C. (2020) A Multi-Class Tour-Flow-Model and its Role in Multi-Class Freight Tour Synthesis. Transportation Science, Vol 54, No 3, pp 631-650.
Holguín-Veras J., Encarnación T., Perez-Guzman S., Yang X. (2020) Mechanistic Identification of Freight Activity Stops from Global Positioning System Data. Transportation Research Record: Journal of the Transportation Research Board, Vol 2674, Issue 4, pp 235-246.
Holguín-Veras J., Encarnación T., González-Calderón C. (2020) User Perception of Fairness of Time-of-Day Pricing and other Typical Toll Discounts. Transportation Research Part A: Policy and Practice, Vol 137, pp 560-581.
SCMA 3300 Business Analytics and Statistics