Sarah Hernandez
Affiliation confirmed via AI analysis of OpenAlex, ORCID, and web sources.
Associate Professor
Also affiliated: California Department of Transportation (2013–2015); Sam Houston State University (2024); University of California, Irvine (2013–2014); Korea Transport Institute (2009); University of Florida (2009); Alexander von Humboldt Foundation (2011); New College of Florida (2007–2010); French National Agency for Water and Aquatic Environments (2011–2012); Irvine University (2015); ORCID (2020); Stress Environnementaux et Biosurveillance des Milieux Aquatiques (2011–2012); University of California, Davis (2025)
Faculty Researcher
Research Areas
Biomedical Subjects
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Biography and Research Information
OverviewAI-generated summary
Sarah Hernandez investigates freight transportation systems, focusing on the analysis of large datasets to understand operational characteristics and inform planning. Her work has involved developing methods to classify truck industry patterns and identify multimodal freight transportation catchment areas using mobile sensor data and machine learning techniques. She has also explored the application of these methodologies to inland waterway networks, mapping AIS data for freight planning and assigning commodity dimensions to disaggregated freight flows.
Hernandez has secured significant federal funding to support her research. She is the Principal Investigator on an NSF CAREER award focused on unbiased long-range freight planning through passive sensors and workforce diversity, and an NSF I-Corps grant for advanced truck detection with lidar technology. Additionally, she serves as a Co-PI on two NSF SCC-CIVIC awards aimed at developing shared micromobility frameworks for affordable and accessible housing. Her scholarly output includes 81 publications, with an h-index of 12 and over 433 citations.
Metrics
- h-index: 12
- Publications: 81
- Citations: 449
Selected Publications
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Data-driven workforce forecasting for transportation infrastructure: A comparative analysis of deep learning and statistical time series models (2026)
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Highway-Transportation-Asset Criticality Estimation Leveraging Stakeholder Input Through an Analytical Hierarchy Process (AHP) (2025)
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Highway Transportation Asset Criticality Estimation Leveraging Stakeholder Input through an Analytical Hierarchy Process (AHP) (2025)
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Prediction of waterborne freight activity with Automatic identification System using Machine learning (2024)
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Data-Driven Methods to Assess Transportation System Resilience: Case Study of the Arkansas Roadway Network (2024)
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Real-Time Barge Detection Using Traffic Cameras and Deep Learning on Inland Waterways (2024)
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Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning (2024)
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Electric Vehicle Usage Patterns in Multi-Vehicle Households in the US: A Machine Learning Study (2024)
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Unraveling Electric Vehicle Preference: A Machine Learning Analysis of Vehicle Choice in Multi-Vehicle Households in the United States (2024)
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Board 37A: Driving Simulators as Educational Outreach for Freight Transportation (2024)
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Unraveling Electric Vehicle Preference: A Machine Learning Analysis of Vehicle Choice in Multi-Vehicle Households in the United States (2023)
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Driving Simulators as Educational Outreach for Freight Transportation (2023)
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A two-stage stochastic optimization model for port infrastructure planning (2023)
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Freight Operational Characteristics Mined from Anonymous Mobile Sensor Data (2023)
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A Two Stage Stochastic Optimization Model for Port Infrastructure Planning (2023)
Federal Grants 4 $1,614,641 total
CAREER: Towards Unbiased Long-Range Freight Planning Through Passive-Sensors and Workforce Diversity
SCC-CIVIC-PG Track A: Shared MicromobIlity for affordabLe-accessIblE houSing (SMILIES)
Collaboration Network
Top Collaborators
- Electric Vehicle Usage Patterns in Multi-Vehicle Households in the US: A Machine Learning Study
- Assessment of Crash Occurrence Using Historical Crash Data and a Random Effect Negative Binomial Model: A Case Study for a Rural State
- Impact of Truck Parking Facilities on Commercial and Industrial Land Values: A Spatial Hedonic Model
- Highway-Transportation-Asset Criticality Estimation Leveraging Stakeholder Input Through an Analytical Hierarchy Process (AHP)
- Unraveling Electric Vehicle Preference: A Machine Learning Analysis of Vehicle Choice in Multi-Vehicle Households in the United States
Showing 5 of 7 shared publications
- GIS-based identification and visualization of multimodal freight transportation catchment areas
- Assigning a commodity dimension to AIS data: Disaggregated freight flow on an inland waterway network
- Inland waterway network mapping of AIS data for freight transportation planning
- Prediction of waterborne freight activity with Automatic identification System using Machine learning
- Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning
- A two-stage stochastic optimization model for port infrastructure planning
- Prediction of waterborne freight activity with Automatic identification System using Machine learning
- Data-Driven Methods to Assess Transportation System Resilience: Case Study of the Arkansas Roadway Network
- A Two Stage Stochastic Optimization Model for Port Infrastructure Planning
- Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning
- Data-Driven Methods to Assess Transportation System Resilience: Case Study of the Arkansas Roadway Network
- Highway-Transportation-Asset Criticality Estimation Leveraging Stakeholder Input Through an Analytical Hierarchy Process (AHP)
- Real-Time Barge Detection Using Traffic Cameras and Deep Learning on Inland Waterways
- Board 37A: Driving Simulators as Educational Outreach for Freight Transportation
- Highway Transportation Asset Criticality Estimation Leveraging Stakeholder Input through an Analytical Hierarchy Process (AHP)
- GIS-based identification and visualization of multimodal freight transportation catchment areas
- Inland waterway network mapping of AIS data for freight transportation planning
- A two-stage stochastic optimization model for port infrastructure planning
- A Two Stage Stochastic Optimization Model for Port Infrastructure Planning
- Representative truck activity patterns from anonymous mobile sensor data
- Truck industry classification from anonymous mobile sensor data using machine learning
- Freight Operational Characteristics Mined from Anonymous Mobile Sensor Data
- A Hybrid Agent-Based Simulation and Optimization Approach for Statewide Truck Parking Capacity Expansion
- A two-stage stochastic optimization model for port infrastructure planning
- Prediction of waterborne freight activity with Automatic identification System using Machine learning
- A Two Stage Stochastic Optimization Model for Port Infrastructure Planning
- Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning
- Inland waterway network mapping of AIS data for freight transportation planning
- Prediction of waterborne freight activity with Automatic identification System using Machine learning
- Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning
- Electric Vehicle Usage Patterns in Multi-Vehicle Households in the US: A Machine Learning Study
- Unraveling Electric Vehicle Preference: A Machine Learning Analysis of Vehicle Choice in Multi-Vehicle Households in the United States
- Unraveling Electric Vehicle Preference: A Machine Learning Analysis of Vehicle Choice in Multi-Vehicle Households in the United States
- A Hybrid Agent-Based Simulation and Optimization Approach for Statewide Truck Parking Capacity Expansion
- Impact of Truck Parking Facilities on Commercial and Industrial Land Values: A Spatial Hedonic Model
- Prediction of waterborne freight activity with Automatic identification System using Machine learning
- Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning
- Prediction of waterborne freight activity with Automatic identification System using Machine learning
- Prediction of Waterborne Freight Activity with Automatic Identification System Using Machine Learning
- A Hybrid Agent-Based Simulation and Optimization Approach for Statewide Truck Parking Capacity Expansion
- A Hybrid Agent-Based Simulation and Optimization Approach for Statewide Truck Parking Capacity Expansion
- A Hybrid Agent-Based Simulation and Optimization Approach for Statewide Truck Parking Capacity Expansion
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