UROP Project

AI Agents (Agentic AI), Ocean Search and Rescue (computer vision), AI Retrieval Augmented Generation

MLab, computer vision, AI Agents, RAG
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Research Mentor: Dr. Jonathan Adams,
Department, College, Affiliation: Information, Communication and Information
Contact Email: jladams@fsu.edu
Research Assistant Supervisor (if different from mentor): Mr. Benhur Ravuri
Research Assistant Supervisor Email: bravuri@fsu.edu
Faculty Collaborators: Mr Odin Moja
Faculty Collaborators Email: omoja@fsu.edu
Looking for Research Assistants: Yes
Number of Research Assistants: 3
Relevant Majors: We prefer students with some technical interest and ability or experience with coding or using a command line interface. Interest in computer systems, artificial intelligence, project planning and publishing basic research are the skills we develop in the MLab.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Yes
Remote or In-person: Partially Remote
Approximate Weekly Hours: 6-8, 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

The MLab has researched and developed techniques for generating synthetic media. Our research has explored various ways to create ‘deep-fakes’ of objects that are hard to photograph or more often, are not sufficient in number to train a computer vision model. The MLab can generate images, labeled and ready for training. If you decide to apply, and ultimately participate, there are a wide variety of opportunities to explore the use of synthetic media in AI training, or for projects that focus on object classification. Research also relies upon the development of AI Agents to complete some of our work, and as the topic of research..
The lab hosts a variety of students (doctoral, master's and undergraduate) and because alumni of the MLab are welcome to continue working on research we also host some students who have decided to continue after UROP concludes. Interested students should understand that participating in the lab means you are a self-starter who works well in small groups of like-minded students, with graduate students and professors who can assist you with your chosen project.
Working knowledge of Python (or other language) programming language is preferred. One of the primary functions of the lab is to encourage research related to the use of Artificial Intelligence agents, and supporting students who desire to publish their works. Since the beginning of 2020, we have produced 8 student-led research papers that have been accepted by international conferences.
We are interested in coders, CS, Engineering, Statistics, and 3D artists who can model different subjects.


Research Tasks: Every student has the opportunity to plan a project of their choice. For example, MLab teams have written literature reviews, conducted technical studies with AI algorithms, conducted AI performance comparisons, and have sought to understand the relationship between AI tools and their impact on learning. We are looking for ideas as well, and are open to value-added ideas.

Skills that research assistant(s) may need: Required: Experience with computer languages, statistics, math, demonstrable ability to learn programming.
Recommended: Communication skills, analytic skills, willingness to take chances.

Mentoring Philosophy

Teamwork and collaboration are fundamental to our lab's success. To illustrate this, consider the Peloton - a group of professional cyclists working in perfect coordination. In this fascinating display of teamwork, cyclists take turns leading the pack, each giving their maximum effort at the front until exhaustion sets in. When the lead rider tires, they fall back to the rear of the group, while another cyclist moves forward to take the lead position.
The Peloton creates a wind vortex (draft) that benefits the entire group. As riders retreat from the lead position, they can recover while being pulled along by this draft, requiring minimal effort. This rotation continues, with each team member taking their turn at the front before falling back to recover.
This collaborative approach demonstrates why even the strongest individual cyclist cannot outperform a well-coordinated Peloton. Similarly, in the MLab, our strength lies in our collective effort. Each member contributes by alternating between leading projects and supporting others' initiatives, fostering a culture of mutual respect and collaborative achievement.
As your mentor, I'm here to guide and support your journey. The MLab provides a safe environment where trial and error are not just accepted but expected. You're encouraged to take risks, learn from mistakes, and grow through experience, knowing that guidance and assistance are always available.

Additional Information

Interviews are by appointment only. Pease use the following link to set up your time:
https://calendly.com/jladams-fsu/urop-mlab-meetings-clone
Roundtable times and Zoom links All Zoom meetings use the following:
https://fsu.zoom.us/j/92291767534
Monday (9/8) 13:00; 13:30; 14:00; 14:30; 15:00; 15:30; 16:00
Wednesday (9/10) 13:00; 13:30; 14:00; 14:30; 15:00; 15:30; 16:00
Friday (9/12) 13:00; 13:30; 14:00; 14:30; 15:00; 15:30; 16:00

Link to Publications

https://mlab.create.fsu.edu/research/