UROP Project
*** Smart Grids + Artificial Intelligence: Powering the Future with Data and Machine Learning
Applied Artificial Intelligence (AI), Data Science, and Energy Systems (Smart Grids, Power Grids, Renewable Energy, Electric Vehicles)
Research Mentor: Ravikumar Gelli, Dr., Prof.,
Department, College, Affiliation: Electrical and Computer Engineering, FAMU-FSU College of Engineering
Contact Email: rgelli@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Electrical and Computer Engineering, FAMU-FSU College of Engineering
Contact Email: rgelli@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: 6
Relevant Majors: Electrical Engineers, Software Engineers, Computer Engineers, Computer Science
Project Location: The Center for Advanced Power Systems 2000 Levy Avenue Tallahassee, FL 32310
Research Assistant Transportation Required: Yes Remote or In-person: In-person
Approximate Weekly Hours: 5-10 hours a week, During business hours
Roundtable Times and Zoom Link:
Number of Research Assistants: 6
Relevant Majors: Electrical Engineers, Software Engineers, Computer Engineers, Computer Science
Project Location: The Center for Advanced Power Systems 2000 Levy Avenue Tallahassee, FL 32310
Research Assistant Transportation Required: Yes Remote or In-person: In-person
Approximate Weekly Hours: 5-10 hours a week, During business hours
Roundtable Times and Zoom Link:
- Day: Thursday, September 4
Start Time: 2:00
End Time: 2:30
Zoom Link: https://fsu.zoom.us/j/93292513597?pwd=NRvY5jOli8ETIUbWg7coJl1EzCgsIn.1
Project Description
This project investigates how Artificial Intelligence (AI) and Machine Learning (ML) can be applied to modern electric power systems, often called “smart grids.” As the grid integrates renewable energy, electric vehicles, and advanced communication systems, AI offers powerful tools for improving reliability, efficiency, and security. Our research focuses on developing AI-driven methods for predicting renewable generation, managing electric vehicle charging, detecting anomalies, and enhancing grid operations. Students will gain exposure to real-world datasets, energy challenges, and emerging technologies at the intersection of AI, data science, and sustainability.Research Tasks: Potential tasks include:
(1) Conducting a literature review on AI applications in smart grids, renewable energy, and electric vehicles.
(2) Working with real-world and simulated energy datasets (solar, wind, EV charging, load demand).
(3) Performing data cleaning, preprocessing, and visualization using Python.
(4) Applying and testing machine learning models (classification, regression, clustering, anomaly detection).
(5) Assisting in the development of interactive dashboards to communicate research outcomes.
(6) Supporting technical documentation and preparing figures/tables for research reports or publications.
Skills that research assistant(s) may need: Required:
Basic programming experience (Python preferred)
Willingness to learn new technical concepts
Strong curiosity and commitment to collaborative research
Recommended:
Familiarity with data science libraries (NumPy, Pandas, Matplotlib, or Scikit-learn)
Introductory knowledge of AI/ML concepts
Interest in renewable energy, sustainability, or power systems
Mentoring Philosophy
My mentoring approach emphasizes inclusivity, growth, and hands-on learning. I believe undergraduates should be treated as valuable contributors to the research team, not just assistants. I tailor guidance to each student’s background, starting from their current skill level and progressively building confidence and independence.I encourage students to:
(1) Ask questions and share ideas freely in a supportive environment.
(2) Balance technical skill-building (coding, data analysis, critical thinking) with understanding the big picture of why the research matters.
(3) Take ownership of subprojects that align with their interests, so they see the impact of their work.
(4) Gain exposure to both academic and real-world applications, preparing them for future research, graduate studies, or industry careers.
My ultimate goal is to ensure that every student leaves the project with new technical skills, a stronger sense of confidence, and a clear understanding of how their work contributes to advancing sustainable energy and AI for the public good.