Career
Education
- PhD in Civil and Environmental Engineering, Carnegie Mellon University, 2023
- Thesis: Inferring demand and supply characteristics of transportation networks through multi-source system-level data
- Supervisor: Sean Qian
- M.S. in Machine Learning, Carnegie Mellon University, 2022
- Selected Coursework: Machine Learning with Large Datasets, Graduate Artificial Intelligence, Convex Optimization, Intermediate Deep Learning, Deep Reinforcement Learning, Probabilistic Graphical Models
- M.S. in Cognitive and Decision Sciences, University College London, 2017
- Thesis: A psychological approach to understanding decisions about time in public transport. Evidence from lab experiments in London, UK and Santiago, Chile
- Supervisors: Nigel Harvey, Paula Parpart and Juan Carlos Muñoz
- M.S. in Transportation Engineering, Pontificia Universidad Católica de Chile, 2015
- Thesis: What is behind fare evasion in public transport? An econometric approach
- Supervisors: Juan de Dios Ortúzar and Patricia Galilea
- B.S. in Industrial Engineering, Pontificia Universidad Católica de Chile, 2013
- Minor: Social Psychology
Awards
- Tata Consultancy Services (TCS) Presidential Fellowship (2021) [link]
- Becas Chile - Conicyt Master Fellowship (2016) [link]
- Michael Beesley Award (2015) [link]
- Scholarships for Engineering Students to Study Abroad (2012) [link]
- John Paul II Foundation Scholarship (2009) [link]
My academic journey
I completed a PhD in Transportation Engineering from Carnegie Mellon University under the supervision of Sean Qian in 2023. To contribute to the research efforts of my lab (MAC), my PhD enhanced traditional transportation network models by leveraging existing behavioral theories to depict travelers' decision-making at the micro level together with machine learning techniques to facilitate the analysis of high dimensional data at the network level. Before starting my PhD, I gained extensive experience in research, teaching and consulting in projects related with data science and transportation.Research experience
After completing my PhD, I worked for Fujitsu Research of America (FRA) as a Senior Researcher. At FRA, I developed advanced traffic simulation and optimization technologies to enhance the Fujitsu's Social Digital Twin (SDT) platform. My core projects leveraged machine learning, network modeling, optimization and computer vision to enhance large-scale, data-driven traffic simulators. I also led a team of data scientists to productionize and extend the traffic simulation technology developed during my PhD. Thanks to multiple collaborations, my time at FRA was very productive in terms of research output and impact. In less than two years, I filed two patents and published a journal article and two conference papers in top venues of the transportation and computer vision fields.
Before my PhD, I also gained relevant research experience. During the first semester of 2018, I worked as a research assistant for the Bus Rapid Transit Centre of Excellence (BRT-CoE) to extend the research conducted during my M.S. at UCL. Back in 2014, I had been a research assistant at the Bus Rapid Transit Centre of Excellence (BRT-CoE) and at the office of CEDEUS in Santiago, Chile. At CEDEUS, I conducted research on fare evasion in public transport and presented this work in various international conferences. During this period, I was the recipient of the Michael Beesley Award for my article Decreasing fare evasion without fines? A microeconomic analysis, which was later published in the journal Research in Transportation Economics. As a result of my master's thesis work, I previously published the article What is behind fare evasion in urban bus systems? An econometric approach in Transport Research Part A: Policy and Practice. I was always interested in the policy implications of my research on fare evasion and thus, I was actively collaborating in public events and academic workshops held in Santiago, Chile. </div>Teaching experience
Consulting experience
CV
To download my CV, please click here.