UROP Project
Harnessing Large Language Models for Human Mobility Understanding and Prediction
AI, Large Language Models, Human Mobility
Research Mentor: Guang Wang, Dr.
Department, College, Affiliation: Computer Science, Arts and Sciences
Contact Email: guang.wang@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Computer Science, Arts and Sciences
Contact Email: guang.wang@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Open to all majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Partially Remote
Approximate Weekly Hours: 10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable
Number of Research Assistants: 2
Relevant Majors: Open to all majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Partially Remote
Approximate Weekly Hours: 10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable
Project Description
This project will utilize the language understanding and reasoning capabilities of LLMs for analysing human mobility data, especially during extreme weather conditions such as hurricanes. Understanding human mobility is very important since it can help with proactive intervention strategies such as emergency evacuation and resource allocation.Research Tasks: literature review, data analysis, experiments with LLMs
Skills that research assistant(s) may need: Python is required