UROP Research Mentor Project Submission Portal: Submission #1335 | Center for Undergraduate Research and Academic Engagement

Submission information

Submission Number: 1335

Submission ID: 21271

Submission UUID: c1d384c6-b1ed-4cc2-8c02-409885bc3cc5

Submission URI: /urop-research-mentor-project-submission-portal

Submission Update: /urop-research-mentor-project-submission-portal?token=Bhp0lmjWVkFtqp4uQLzCbbGRUJCtE7Df1IGb60FqdK4

Created: Fri, 08/22/2025 - 07:08 PM

Completed: Fri, 08/22/2025 - 07:08 PM

Changed: Mon, 08/25/2025 - 11:10 AM

Remote IP address: 71.203.104.26

Submitted by: Anonymous

Language: English

Is draft: No

Webform: UROP Project Proposal Portal

Submitted to: UROP Research Mentor Project Submission Portal

Research Mentor Information

Primary Research Mentor Name Oscar Chuy

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Contact Email (FSU Email if affiliated) chuy@eng.famu.fsu.edu

Position Title Faculty

FSU College (if applicable) FAMU-FSU College of Engineering

FSU Department or Non-FSU Organization Affiliation Electrical and Computer Engineering

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Additional Research Mentor(s)

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Overall Project Details

Title of the Project Activity Identification Using Deep Learning

Project Keywords AI, machine learning, sensor technologies, embedded systems, and biomedical applications

Are you currently looking for research assistants? Yes

Number of Research Assistants Needed 2

Relevant Research Assistant Major(s) Electrical and Computer

Project Location: FAMU-FSU College of Engineering

If the project location is off campus, does the research assistant(s) need to provide their own transportation? Yes

Please select the choice that most accurately describes your expectations for the research assistant(s): In-person

Approximately how many hours a week would the research assistant(s) need to work? 5-10

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 As the elderly population continues to grow, understanding their daily activities has become increasingly important for designing supportive technologies that promote independence. This research project focuses on recognizing human activities—such as walking, sitting, or reaching—by analyzing data collected from various sensors.
Students will work with sensors such as accelerometers and cameras to gather data and apply deep learning techniques to detect and classify different activities.
Through this research experience, undergraduate students will gain hands-on skills in:
• Basic electronics and sensor setup
• Data collection and preprocessing
• Deep learning for activity recognition
This is a great opportunity for students who are interested in AI, machine learning, sensor technologies, embedded systems, and biomedical applications.

Research Tasks Literature review, data collection, programming (python), data analysis, and deep learning implementation.

Skills that research assistant(s) may need: Basic programming, Interest in AI TensorFlow or PyTorch, Interesest in Sensors and Data Analysis.

Mentoring Philosophy I believe undergraduate research is a chance for students to grow into independent problem-solvers. My role as a mentor is to guide, not micromanage. I provide the tools, feedback, and support needed, but I expect students to take ownership of their learning and drive their own progress.

I encouraged student to
• Take initiative and explore solutions on their own
• Learn from challenges and setbacks
• Ask thoughtful questions and seek out resources
• Communicate clearly and manage their time responsibly

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Are you interested in participating in the UROP Research Mentor Roundtable? No

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UROP Program Elements

Mentor Handbook, FAQs, and Communication Yes

UROP Performance Evaluation Yes

Materials Grant Yes

UROP Poster Presentation Yes

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Year 2025

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