Welcome to the Smart, Equitable, Resilient Mobility Systems (SERMOS) Lab!

The SERMOS Lab is a transdisciplinary research lab led by Dr. Xilei Zhao, Assistant Professor in Civil and Coastal Engineering at the University of Florida. We invent and apply AI and data science methods to create smart, equitable, resilient mobility systems. Our transdisciplinary team is made up of transportation engineers, computer scientists, systems engineers, and social scientists. Our expertise includes:

• Data analytics and travel behavior modeling for innovative mobility (e.g., ridesourcing and micromobility)
• Modeling and planning evacuation
• Quantifying resilience for critical infrastructure systems, societal systems, and communities

Openings!

SERMOS Lab is always looking for talented students to join our team!! The openings are at all levels, i.e., undergraduate/graduate researchers, Ph.D. students, and postdoctoral fellows. To express your interest in joining our team, please email your complete CV and a short cover letter (up to one page) to Dr. Xilei Zhao (xilei.zhao@essie.ufl.edu). With our strong commitment to diversity in engineering education, research, and practice, we especially encourage minorities and women to apply.

Recent News!

• Mar 2024: Dr. Zhao (PI) won the 2024 NSF CAREER Award, entitled “CAREER: An Integrated Trustworthy AI Research and Education Framework for Modeling Human Behavior in Climate Disasters.”
• Mar 2024: Our lab’s paper, entitled “Scalable and Rapid Building Damage Detection after Hurricane Ian using Causal Bayesian Networks and InSAR Imagery,” was accepted for publication in the International Journal of Disaster Risk Reduction. 
• Feb 2024: Our lab’s paper, entitled “Modeling protective action decision-making in earthquakes by using explainable machine learning and video data,” was accepted for publication in Scientific Reports. 
• Feb 2024: Dr. Zhao gave a presentation, entitled “Fusing Small and Big Data to Advance Understanding of Hurricane Evacuation,” at the 2024 Gulf of Mexico Conference.
• Feb 2024: Our lab’s paper, entitled “Predicting hurricane evacuation decisions with interpretable machine learning methods,” was accepted for publication in the International Journal of Disaster Risk Science.
• Jan 2024: Our lab’s book chapter, entitled “Digital Technologies for Fire Evacuations,” was published by Springer in Intelligent Building Fire Safety and Smart Firefighting. 
• Jan 2024: Our lab’s PhD students gave two lectern and one poster presentations at TRB 2024! 
• Dec 2023: Our lab’s paper, entitled “A data-driven, scenario-based human evacuation model for passenger ships addressing hybrid uncertainty,” was accepted for publication in the International Journal of Disaster Risk Reduction. 
• Dec 2023: Our lab’s paper, entitled “Analyzing spatial heterogeneity of ridesourcing demand determinants using explainable machine learning,” was accepted for publication in the Journal of Transport Geography. 
• Dec 2023: Dr. Zhao was invited to give a presentation, entitled “Should we stay or leave now? Improving understanding of wildfire evacuation with large-scale GPS data,” in the TRB Webinar: Understanding Evacuation Behavior and Regional Resilience. 
• Nov 2023: Dr. Zhao (co-PI) won a Natural Hazards Center project, entitled “Transportation as a Social Determinant of Health During Hurricane Idalia.”
• Nov 2023: Our lab’s paper, entitled “Analyzing risk perception, evacuation decision and delay time: A case study of the 2021 Marshall Fire in Colorado,” was accepted for publication in Travel Behaviour and Society. 
• Oct 2023: Our lab’s book chapter, entitled “AI for Large-Scale Evacuation Modeling: Promises and Challenges,” was published by Elsevier in Interpretable Machine Learning for the Analysis, Design, Assessment, and Informed Decision Making for Civil Infrastructure. 
• Oct 2023: Our lab’s paper, entitled “Causality-informed Rapid Post-hurricane Building Damage Detection in Large Scale from InSAR Imagery,” was accepted for publication in the 8th ACM SIGSPATIAL International Workshop on Security Response using GIS 2023.
• Oct 2023: Our lab’s paper, entitled “Spatial equity of micromobility systems: A comparison of shared e-scooters and docked bikeshare in Washington DC,” was accepted for publication in Transport Policy.
• Sept 2023: Dr. Zhao was invited to give a seminar, entitled “Enhancing Fairness in AI-based Travel Demand Forecasting Models,” in the CEE department at the University of Massachusetts Amherst.
• Sept 2023: Dr. Zhao (PI) won a NIST project, entitled “Enhancing Wildfire Emergency Management (WEM) Platform with Near Real-Time Sensing Data and Deep Learning.”
• Sept 2023: Dr. Zhao was invited to give a seminar, entitled “Enhancing Fairness in AI-based Travel Demand Forecasting Models,” in the Next Generation Transportation System (NGTS) seminar series held at the CEE department at the University of Michigan.
• Sept 2023: Our lab’s paper, entitled “Shared e-scooters: User characteristics and usage patterns across four U.S. cities,” was published in Transportation Research Record.
• Aug 2023: Dr. Zhao spoke with FOX 35 Orlando to help prepare for Hurricane Idalia: https://www.fox35orlando.com/video/1271354. 
• Aug 2023: Dr. Zhao was selected to give a presentation, entitled “Micromobility Analytics and Management Platform,” in Datapalooza hosted by the AASHTO Committee on Data Management and Analytics. 
• July 2023: Dr. Zhao was invited to participate in a panel, entitled “Friend or Foe? Technology, Hurricanes, and Marginalized Communities,” in the 2023 Natural Hazards Center Workshop.
• May 2023: Dr. Zhao along with industry partner, Gravy Analytics, received the Honorable Mention in the Future of Privacy Forum Award for Research Data Stewardship for the NIST-funded wildfire evacuation research. 
• May 2023: Dr. Yiming Xu graduated from our lab with a doctoral degree in civil engineering. We wish him the best of luck in his future endeavors!