Research Projects

Social Media Data Mining for Transport Commute Decisions (Aug. 2022- Jul. 2023)

Objective: Retrieve, filter, and analyze social media posts to gather US-based conversations regarding transportation behavior and implement Natural Language Processing techniques to draw real-time estimates on commuting decisions.

Researchers: Juan Acosta-Sequeda

A Twitter data downloading framework for geographical analysis and sustainability research (May 2022 – Jun. 2023.)

Objective: Develop a high-level tool to download geographically referenced Twitter data from user-defined parameters and compute basic preliminary text and statistical analyses.

Researchers: Juan Acosta-Sequeda

Investigating Attitudinal and Behavioral Changes in US Households Before, During, and After the COVID-19 Pandemic (May 2020 – Aug. 2022)

Objective: Develop, deploy, and analyze a household travel survey to capture attitudinal and behavioral changes in US households with the COVID-19 pandemic. All data collected is anonymized and shared in open access. Find out more on the project, the survey, and the data at covidfuture.org.

Researchers: Rishabh Chauhan

Train Delay Prediction Modeling (Aug. 2018 – Jul. 2022)

Objective: Build database of Amtrak train arrival times and other variables (e.g., weather) and use Machine Learning (ML) to model train delay prediction.

Researchers: Pipatphon Lapamonpinyo

Investigate Interdependencies and Interrelationships in Urban Infrastructure (Aug. 2016 – Jul. 2022)

Objective: Identify and study the presence of interdependencies in how infrastructure operates and interrelationships in how people use infrastructure services.

Researchers: Ali Movahedi

Converting Infrastructure Maps from CAD to GIS (Aug. 2017 – Dec. 2021)

Objective: Develop protocols and machine learning models to accurately convert infrastructure maps from CAD to GIS format.

Researchers: Mohamed Badhrudeen

The Affluence-Technology Connection (Aug. 2016 – Dec. 2019)

Objective: Explore the Affluence-Technology connection (from the IPAT equation) through the development of new metrics that reveal how technological attributes and consumption affluence influence and relate to each other.

Researchers: John Mulrow

Machine-based Statistical Learning of Urban Metabolism (Aug. 2015 – Dec. 2019)

Objective: Design high-performance machine-based statistical learning models that can be applied in the context of urban metabolism.

Researchers: Dongwoo Lee

Stormwater Runoff of Argyle Street: Pre and Post Green Infrastructure (Aug. 2017 – Aug. 2019)

Objective: Model pre and post stormwater runoff management scenario of existing green infrastructure in Argyle Street in Chicago using EPA SWMM.

Researchers: Ranjita Tiwari

Sentiment Analysis of Tweets Related to Civil Infrastructure across US Cities (Aug. 2018 – Aug. 2019)

Objective: Collect tweets with specific keywords related to civil infrastructure for a list of cities across the US and analyze their sentiment using Natural Language Processing (NLP) and QGIS.

Researchers: Yijing Xiao

Value Engineering Cities (Jan. 2017 – Jul. 2018)

Objective: Develop an assessment method to evaluate the value of cities based on their infrastructure.

Researchers: Scot Maciver

Modeling the Impact of Climate Change on Stormwater Infrastructure: Application to Elmhurst, IL (Dec. 2017 – Mar. 2018)

Objective: Simulate the impact of Climate change on existing stormwater infrastructure by using the climate model output and XPSWMM.

Researchers: Dena Delpazir

Tracking Resource Consumption Trends using Network Theory (Aug. 2014 – Dec. 2017)

Objective: Create, develop and apply a new fundamental network theoretical methodology to track trends in resource consumption in the world.

Researchers: Nasir Ahmad

Measuring the Resilience of Urban Transportation Networks to Extreme Events (Aug. 2013 – May 2017)

Objective: Simulate and measure the impact of extreme events on urban transportation systems by using climate model outputs and concepts of network science.

Researchers: Amirhassan Kermanshah

Urban Infrastructure is not a Tree: Integrating and Decentralizing Urban Infrastructure Networks (Aug. 2015 – May 2016)

Objective: Adapt Christopher Alexander’s A City is not a Tree concept to urban infrastructure and determine how urban infrastructure networks can be better integrated and decentralized for smarter cities.

Researchers: Paloma Morais de Souza, Daniel Kessler

GIS to Network Tool Development (Jan. 2015 – Aug. 2016)

Objective: Develop an ArcGIS, python, and QGIS tool to convert any GIS polyline feature into a network format.

Researchers: Alireza Karduni, Amirhassan Kermanshah

Facility-Scale Industrial Symbiosis (Jan. 2015 – May 2016)

Objective: Define a novel approach to co-locating small production businesses within a single facility, based on established industrial symbiosis and circular economy principles.

Researchers: John Mulrow

Estimating The Cost of Over-Cooling Commercial Buildings in the United States (Aug. 2014 – Aug. 2015)

Objective: Compare building electricity use data with simulated data (using DOE’s eQuest) to estimate the energy and monetary cost of over-cooling commercial buildings.

Researchers: Matthew Reeder

Water Consumption Networks in the United States (Aug. 2013 – Jul. 2014)

Objective: Adopt a network science methodology to study how water consumption has evolved in the United States.

Researchers: Nasir Ahmad

Geometric Complexity of Urban Road Networks (Aug. 2012 – Dec. 2014)

Objective: Develop novel methodologies to study and characterize the complex geometry of urban road networks, which can in turn lead to a better understanding of their encompassing urban systems.

Researchers: Farid Peiravi