UROP Research Mentor Project Submission Portal: Submission #1030

Research Mentor Information
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Primary Research Mentor Name: Guang Wang
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Contact Email (FSU Email if affiliated): guang.wang@fsu.edu
Position Title: Faculty
FSU College (if applicable): Arts and Sciences
FSU Department or Non-FSU Organization Affiliation: Computer Science
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Additional Research Mentor(s)
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Research Assistant Supervisor (if different from above): {Empty}
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Overall Project Details
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Title of the Project: Urban Big Data Analytics and Visualization for Smart Cities
Project Keywords: Big Data, AI, Visualization, Smart Cities
Are you currently looking for research assistants?: No
Number of Research Assistants Needed : 2
Relevant Research Assistant Major(s):
Open to all majors


Project Location:: On FSU Main Campus
If the project location is off campus, does the research assistant(s) need to provide their own transportation?: No, the project is remote
Please select the choice that most accurately describes your expectations for the research assistant(s):: Partially Remote
Approximately how many hours a week would the research assistant(s) need to work?: 10
Roughly what time frame do you expect research assistant(s) to work?: Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Overall Research 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, sustainability, 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 research project will develop a comprehensive urban big data analytics and visualization framework that integrates spatiotemporal data mining, machine learning, and interactive visualization techniques to support smart city applications. Specifically, the project will:

Design scalable data pipelines to collect, clean, and integrate multimodal urban data streams;

Develop advanced analytics models to detect patterns, predict urban dynamics, and identify anomalies in domains such as mobility, energy consumption, housing, and public health;

Create intuitive, user-centered visualization tools that enable policymakers, city planners, and community stakeholders to explore insights, simulate scenarios, and support evidence-based decision-making.

Research Tasks:
Literature Review: Conduct a comprehensive review of recent advancements in urban informatics, smart city initiatives, big data analytics, and interactive visualization tools.

Data Collection: Gather and curate diverse urban datasets, including transportation logs, air quality data, social media feeds, utility usage records, census information, and IoT sensor data.

Data Analysis: Apply statistical and machine learning methods to discover patterns, trends, and anomalies in urban dynamics (e.g., traffic congestion, pollution hotspots, energy usage patterns).

Visualization Design and Implementation: Design user-friendly, interactive dashboards and visual analytics tools tailored to different user groups (e.g., city officials, community leaders, researchers).

Skills that research assistant(s) may need::
Data collection and analysis skills are required.
Experience in Python is required.
Familiar with ArcGIS (recommended).


Mentoring Philosophy:
My mentoring goal is to encourage every student to learn something. Based on my previous mentoring experiences, I think all students are talented and my role as a teacher is to guide them to knock on the correct door. To this end, my mentoring philosophy concentrates on encouraging students to ask questions. I treat all students with respect and maintain academic fairness. In addition, I strive to create a friendly learning environment and make students feel comfortable and supported. I think students can improve their performance after they know what they do not know, and a very effective way is by asking questions, so I usually encourage students to ask questions.

Please provide a link to your publications, a video clip, or a website for your research project (if applicable):: guangwang.me
Please add any additional information here (if applicable)::
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Are you interested in participating in the UROP Research Mentor Roundtable?: No
Roundtable times and Zoom links:
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UROP Program Elements
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Mentor Handbook, FAQs, and Communication: Yes
UROP Performance Evaluation: Yes
Materials Grant: Yes
UROP Poster Presentation: Yes

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Year: 2025
update url: https://cre.fsu.edu/urop-research-mentor-project-submission-portal?token=WTx0cdmYwKU4TDMyH3fM_EPfKGtWDMcEG9-XJdm7nK8