Projects and Grants

Below, is a list of active funded projects and grants led by the COSC faculty. For more information, please contact individual faculty members.

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Collaborative Research: Personalized Systems for Wayfinding for First Responders

U.S. National Science Foundation (NSF)

June 2018 to May 2021

PI: Dr. Eric Jing Du

The objective of this project is to test the theoretical foundation of personalized wayfinding information systems that can effectively minimize the cognitive load of first responders on the individual level. This scientific research contribution thus supports emergency response wayfinding, which will save lives and potentially reduce economic losses during disasters.


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Cognition-Driven Display for Navigation Activities (Cog-DNA): Personalized Spatial Information System Based on Information Personality of Firefighters

National Institute of Standards and Technology (NIST)

June 2018 to May 2021

PI: Dr. Eric Jing Du, Co-PI: Dr. Patrick Suermann

This project proposes and tests an innovative concept called Spatial Information Personality (SIP), a cognitive profile of information-taking preference and behavioral patterns at the individual level. SIP of firefighters will be tracked by quantifying individual reactions to different types, quantities, and display methods of information during virtual reality based fire training. The collected SIP data of individual firefighters can be integrated as a necessary part of their personal files.


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Systematic Approach for Estimating Construction Contract Time: A Guidebook (NCHRP 08-114)

National Cooperative Highway Research Program (NCHRP), Transportation Research Board (TRB), National Academy of Science

August 2018 to April 2020

PI: Dr. David Jeong, Co-PI: Dr. KC Choi

This research aims at developing a comprehensive guidebook encompassing procedures, methods, and tools for determining contract time that can work for a wide spectrum of highway infrastructure projects.  A systematic approach and a risk-based methodology will be employed to provide reliable contract time estimation methods over the project delivery process.


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Non-intrusive Elderly Smart-home Healthcare System for Monitoring Short-term and Long-term Anomaly in Daily Activity Patterns

Korea Agency for Infrastructure Technology Advancement (KAIA)

March 2017 to December 2019

PI: Dr. Ryan Ahn

this research designs a smart home monitoring platform of elderly people’s daily activities to improve their health. The proposed platform will continuously monitor and evaluate daily activities of the elderly, and identify the occurrence of emergent situations (including accidents) and the decline in physical and cognitive functions.


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Uncovering Potential Risks of Wind-induced Cascading Damages to Construction Projects and Neighboring Communities

U.S. National Science Foundation (NSF)

January 2017 to December 2019

PI: Dr. Youngjib Ham

This project will create and validate a new streamlined Imaging-to-Simulation framework to prevent wind hazard events from causing catastrophic damage to construction projects and neighboring communities.


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A Natural Language Based Data Retrieval Engine for Automated Digital Data Extraction for Civil Infrastructure Projects

U.S. National Science Foundation (NSF)

September 2016 to December 2019

PI: Dr. David Jeong

This research proposes a novel approach for a fast and unambiguous reuse of digital models for the civil infrastructure industry by developing an automated data retrieval engine capable of recognizing user information from their natural language queries (e.g., words, phrases, questions) and extracting the desired data from heterogeneous digital datasets by employing the recent advances in Natural Language Processing (NLP) techniques, machine-learning based semantic measure methods to develop the data retrieval system.


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Revealing Hidden Safety Hazards using Workers' Collective Bodily and Behavioral Response Patterns

U.S. National Science Foundation (NSF)

January 2016 to December 2019

PI: Dr. Ryan Ahn

The objective of this research is to examine whether, how, and to what extent workers' collective bodily and behavioral response patterns identify recognized/unrecognized hazards for the purpose of enhancing safety performance in construction environments.


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Real-Time Feedback-Enabled Simulation Modeling of Dynamic Construction Processes

U.S. National Science Foundation (NSF)

January 2016 to December 2019

PI: Dr. Amir Behzadan

The objective of this research is to examine whether, how, and to what extent workers' collective bodily and behavioral response patterns identify recognized/unrecognized hazards for the purpose of enhancing safety performance in construction environments.


Low-Cost In-The-Moment Bio-Signal Interventions to Promote Students’ Public Speaking Skills in a Virtual Learning Environment

Engineering Information Foundation (EiF)

September 2018 to August 2019

Co-PI: Dr. Amir Behzadan

This study will examine how wearable devices and virtual reality (VR) can be used to provide low-cost personalized public speaking interventions. The developed VR interface simulates a public speaking environment with audience of varying degrees of attentiveness, engagement, and perceived positivity or negativity. Experiments are conducted with various types of audience and context settings to monitor physiological indices and speech patterns, integrate bio-signals for speech assessment, and generate data-driven real-time feedback.


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Development of Granular Road Asset Management System

Iowa Highway Research Board (IHRB)

June 2017 to August 2019

PI: Dr. David Jeong

The goal of this research project is to develop a comprehenzive granular road asset management system for local counties.  Historical performance data will be used to develop reliability equations and curves for granular roads in difference operating conditions to support systematic decisions on maintenance and resurfacing needs in the future.


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Optimizing Maintenance Equipment Life Cycle for Local Agencies

Iowa Highway Research Board (IHRB)

June 2017 to August 2019

PI: Dr. David Jeong

The goal of this research project is to provide proper guidance for local agencies in determing the most cost-effective decisions throughout the life cycle of a variety of maintenance equipment used by local agencies.  An equipment life cycle cost management framework and its tool will be developed.  A practical guide on what types of equipment data should be collected at what frequency will be developed for continuous improvement of the decision aid tool.


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Collaborative Research: Transforming Teaching of Structural Analysis through Mobile Augmented Reality

U.S. National Science Foundation (NSF)

August 2017 to July 2019

PI: Dr. Amir Behzadan

The objective of this collaborative project is to transform existing teaching pedagogy in structural analysis by designing and testing a mobile augmented reality (AR) platform that superimposes the visuals of the textbook with interactive computer generated 3D models of structures under load. In doing so, the potential of AR for improving learning and increasing student engagement in the learning process is systematically assessed.


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Effective Production Rate Estimation and Activity Sequencing Logics Using Daily Work Report Data (Phase - II)

Montana Department of Transportation (MDT)

October 2018 to June 2019

PI: Dr. David Jeong

As part of modernization efforts for contract time determintation, the Phase I developed data driven production rate estimation models for controlling work items of highway projects.  The goal of the Phase II is to develop construction sequence logics for major types of MDT projects using historical data available in daily work reports in order to enhance the MDT's current contract time determination procedures.


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IBSS: Participatory-Ensemble Modeling to Study the Multiscale Social and Behavioral Dynamics of Food Security

U.S. National Science Foundation (NSF)

August 2014 to January 2019

Co-PI: Dr. Eric Jing Du

This project aims to enhance understanding of the critical societal problem of food security and will communicate potential solutions to decision makers by developing tools that synthesize qualitative and quantitative information from geography, sociology, decision science, and sustainability science as well as cross-disciplinary knowledge on food insecurity.


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EAGER: Interaction of Smart Materials for Transparent, Self-Regulating Building Skins

U.S. National Science Foundation (NSF)

December 2015 to August 2018

PI: Dr. Zofia Rybkowski

This project seeds the exploratory development and testing of the interdisciplinary core-team’s collaborative project challenge—a transparent, self-regulating building skin that interacts with its environment using smart materials and is scalable and applicable for both new and existing buildings.