I lead the Science team’s work on guest vertical products within Uber for Business (U4B), where I develop measurement frameworks, experimentation strategies, and data-driven insights that inform product decisions and enhance the travel experience across a three-sided marketplace of coordinators, riders, and drivers. Before joining Uber, I worked for 2 years as a Principal Researcher for Fujitsu Research leading a team of data scientists to productionize and extend the traffic simulation technology developed during my PhD in Civil and Environmental Engineering at Carnegie Mellon University (CMU).

My academic background is highly interdisciplinary. In addition to my PhD, I have an M.S. in Machine Learning from the CMU School of Computer Science (SCS) and an M.S. in Cognitive and Decision Sciences from the Department of Experimental Psychology at University College London (UCL). I also earned a BSc in Industrial Engineering, a minor in Social Psychology, and an M.S. in Transportation Engineering from Pontifical Catholic University of Chile (PUC). I continuously seek to expand and leverage my skill set on problems at the intersection of machine learning, artificial intelligence, optimization, human behavior, and transportation.