My teaching activity at MIT spans my own interests in programming and modeling of human mobility and networks.
Undergraduate Class: Transportation Systems (1.041)
Introduction to basic concepts of transportation systems data collection, modeling, analysis and visualization techniques. Topics in my units include network models, analysis of network properties, geo-spatial network data analysis.
Syllabus 2014 (pdf)
Final Projects 2014:
- Noor Khouri, Dimitrios Pagonakis, “MIT International Students Network Gathering Real World Data to Predict Admission Statistics” [pdf]
- Sharone Small and Tim Wilson, “Primary School Contact Patterns” [pdf]
- Madeleine Bairey & Shanté Stowell, “US Power Grid Network Analysis” [pdf]
- Amairani Garcia and Abbey Bethel, “Network of Shared Jazz Musicians” [pdf]
- Margo Dawes and Carmen Castanos, “Road Importance in and around Boston” [pdf]
- Xiao Yun Chang, Joshua Fabian “The Humanity of Twitter Retweets and Mentions” [pdf]
- Jessica Parker, Phoebe Whitwell, “Characteristics of Self-Selecting Social Lists” [pdf]
and some images:
Final Projects 2013:
- Anna R Falvello Tomas and Mun Ngah Cheong, “Classifying the Caenorhabditis Elegans Neural Network” (pdf)
- Talal Al-Mulla, Catherine Cheng, “Developing a Capacity Correction Factor through an Analysis of Trips in Boston’s Bike-Sharing System” (pdf)
- David Ogotu, “Redrawing the Map of the United States from Commuter Data” (pdf)
- Annabeth Gellman and Jibo WenAn, “Analysis of the NCAA Division IA Football Conference Structure” (pdf)
- Daphne Basangwa “Analysis of Jazz Bands Network” (pdf)
- Obinna Okwodu “Analysis of a Retweet Network” (pdf)
- Linda Seymour and Lindsay Stone “Analysis of Dolphins Social Networks” (pdf)
and some images:
Graduate class: Computer Modeling: From Human Mobility to Transportation Networks (1.204)
The goal of this class is to teach methods that extract useful information from digital traces of human activity. It covers numerical methods to cluster the structure inherent in daily activities within a population. We compare the empirical results with existing mobility models. It teaches algorithms to model and to characterize complex networks. We cover articles of complex networks theory applied to: air transportation, road networks and commuting networks. Lectures are reinforced with case studies and exercises, using data sets from actual applications.
Updated Syllabus of 2014 (pdf)
Sample of Final Projects 2013
- Lauren Alexander, “Understanding Road Usage Patterns of Hubway Riders” (pdf)
- Krihsna Kumar Selvam, “Analysis of a location based online social network” (pdf)
- Rinal Chheda, “Analysis of a location based online social network” (pdf)
Sample of Final Projects 2012
- Veronica Hannan and Kael Greco, Community Structure in Lisbon Origin Destination Network (pdf).
- Michael T. Chang, Network Analysis of Urban Street Patterns (pdf).
- Cressica Brazier, Modellig Exploration and Preferential Attachment Properties in Individual Human Trajectories(pdf).
- Fei Fei, Implication from Clustering Mobility patterns: A New look on Staggered Working Hours Strategy (pdf)
Syllabus 2011 (pdf) and Project Samples:
- Lu Lu, Extracting the Mobility of Transit System based on GPS data (pdf).
- Serdar Colak, The Price of Anarchy in Transportation Networks (pdf).
Some Cases of study developed by students in the Fall of 2010:
- Yi Zhu, Extracting the Mobility of Transit System based on GPS data (pdf).
- Sarah Hovsepian and Mehdi Akbarian, Truck Traffic in the US (pdf).
- Shan Jiang, Understanding Patterns of Trips to (Non-Work/-Home) Urban Destinations (pdf).
The following research collaborations started in the class, motivated by great students and their advisers they have resulted in the following publications:
- A metric of influential spreading during contagion dynamics through the air transportation network.
C. Nicolaides, L. Cueto-Felgueroso, M. C. Gonzalez and R. Juanes, PLoS ONE, 7(7), e40961 (2012), doi:10.1371/journal.pone.0040961 (pdf)
- Clustering Daily Patterns of Human Activities in the City, Jiang, S., J. Ferreira, and M. González. Data Mining and Knowledge Discovery 25 (3):478-510. (Special Issue: Data Mining Technologies for Computational Social Science). doi:10.1007/s10618-012-0264-z. [video demo](2012)
- A Review of Urban Computing for Mobile Phone Traces: Current Methods, Challenges and Opportunities(pdf). Jiang, S., G. A. Fiore, Y. Yang, J. Ferreira, E. Frazzoli, and M. C. González. 2013 (best paper award). Proceedings of the ACM SIGKDD International Workshop on Urban Computing. Chicago, IL, USA. (pdf)