UROP Project
Generative AI for Smart Cities Applications
Generative AI, Human Mobility, Data Analytics
Research Mentor: Guang Wang,
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: 3
Relevant Majors: Computer Science,
Data Science,
Statistics,
Math,
Geography,
Urban Planning
Project Location: On FSU Main Campus
Research Assistant Transportation Required: 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: 3
Relevant Majors: Computer Science,
Data Science,
Statistics,
Math,
Geography,
Urban Planning
Project Location: On FSU Main Campus
Research Assistant Transportation Required: 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 aims to harness the power of large-scale, diverse, and real-time urban data to address critical challenges in city planning, mobility, and public services. As cities become increasingly digitized, massive volumes of data, ranging from traffic flows, environmental sensors, social media, utility usage, and public transit records, offer unprecedented opportunities to understand and improve urban systems. However, effectively analyzing and visualizing these heterogeneous data sources to support timely and effective decision-making remains a significant challenge. This project aims to develop generative AI models for synthetic data generation, privacy data protection, and predictive modeling, etc.Research Tasks: Data Collection: Gather and curate diverse urban datasets, including transportation logs, air quality data, social media feeds, energy usage records, census information, and IoT sensor data.
Tool Design: Design interactive visualization tools.
Generative AI model development.
Skills that research assistant(s) may need: Data collection and analysis skills are required.
Experience in Python is required.
Familiarity with LLMs is recommended.