- PhD in Egineering Systems, MIT | (expected) 2017.
- Advisors: Dr. Matthias Winkenbach and Prof. Yossi Sheffi
- Thesis: Leveraging High-Resolution Information for Urban Logistcs
- MSc in Engineering Systems, MIT | 2015
- Advisor: Dr. Edgar Blanco
- Thesis: Transshipment Networks for Last-Mile Delivery in Congested Urban Areas
- MSc in Industrial Engineering, Texas A&M University | 2009
- Advisor: Dr. Gary Gaukler
- Concetration: IT for Logistics and Sypply Chain Management
- BSc in Industrial Engineering, Universidad San Franicsco de Quito | 2007
- BSc in Industrial and Systems Engineering, Virginia Tech (Visiting Student) | 2005-2006
Daniel Merchán is pursuing a Ph.D. in Engineering Systems at the Massachusetts Institute of Technology. His research focuses on logistics operations in large urban areas. Specifically, Daniel explores how big data sources can be leveraged to inform last-mile strategies and operational plans, through data science, optimization and simulation methods. His research has been sponsored by Walmart Stores, B2W Digital, ABInBev and Flipkart. He has completed part of his data science studies at Harvard University.
Before joining MIT in 2013, Daniel served as co-Director of the Industrial Engineering Department at Universidad San Francisco (USFQ) in Ecuador. His educational background also includes a M.Sc. in Engineering Systems from MIT, a M.Sc. in Industrial and Systems Engineering from Texas A&M University sponsored by the Fulbright Program, and a B.Sc. in Industrial Engineering from USFQ with studies at Virginia Tech. Daniel has more than 8 years of experience in consulting and applied research in logistics systems design, analysis and optimization.
Daniel is the recipient of the 2016 Best Doctoral Paper Award by the Information Systems, Logistics and Supply Chain Conference and DINALOG; and of the 2016 L.L. Waters Scholarship awarded by APICs. He teaches a graduate level course in data science in the MIT GCLOG Program.