UROP Project
Car or Bus? Understanding University Students’ Transportation Choices and Barriers to Public Transit Use
Transportation behavior; public transit; student mobility; parking; sustainability; travel behavior; university policy; behavioral decision-making
Research Mentor: hbejanyan@fsu.edu Hayk Bejanyan,
Department, College, Affiliation: Askew School of Public Administration and Policy, Social Sciences and Public Policy
Contact Email: hbejanyan@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Askew School of Public Administration and Policy, Social Sciences and Public Policy
Contact Email: hbejanyan@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: 2
Relevant Majors: Open to all majors. Students in Public Administration, Political Science, Economics, Urban and Regional Planning, Geography, Sociology, Psychology, Business, Statistics, or related fields may find the project particularly relevant.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Partially Remote
Approximate Weekly Hours: 7, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Number of Research Assistants: 2
Relevant Majors: Open to all majors. Students in Public Administration, Political Science, Economics, Urban and Regional Planning, Geography, Sociology, Psychology, Business, Statistics, or related fields may find the project particularly relevant.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Partially Remote
Approximate Weekly Hours: 7, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
- Day: Monday, August 31
Start Time: 2:00
End Time: 3:00
Zoom Link: https://fsu.zoom.us/j/95674055682 - Day: Wednesday, September 2
Start Time: 12:00
End Time: 1:00
Zoom Link: https://fsu.zoom.us/j/95745511330
Project Description
Transportation is an important component of the university experience, affecting students’ time, expenses, access to campus, parking demand, traffic congestion, and environmental sustainability. Although public transportation provides an alternative to private vehicles, many university students continue to prefer driving to campus.This project seeks to understand the factors that influence students' decisions to drive rather than use bus transportation and to identify changes that could make public transit a more attractive alternative.
The research will examine factors such as travel time, convenience, reliability, flexibility, bus frequency, accessibility of stops, parking availability and cost, safety, comfort, weather, class schedules, and students' perceptions of public transportation. The study will also explore whether students have accurate information about the relative costs and travel times associated with different transportation options.
The project will use a mixed-methods approach combining a review of existing research, student surveys, campus observations, and potentially interviews or focus groups. Students may also compare travel scenarios involving private vehicles and public transportation.
The broader goal is to identify the most important barriers to bus use and develop evidence-based recommendations that universities and transportation providers could consider to encourage more sustainable and efficient student transportation choices.
Research Tasks: Research assistants will participate in several stages of the research process, including:
Conducting a literature review on student transportation behavior, public transit use, and transportation choice.
Helping refine research questions and hypotheses.
Assisting with the development and testing of a student transportation survey.
Recruiting survey participants and collecting data.
Conducting structured observations of transportation patterns at selected campus locations.
Collecting information about transportation alternatives, including estimated travel time, cost, frequency, and accessibility.
Cleaning and organizing survey and observational data.
Conducting descriptive statistical analyses and, depending on the students' interests and skills, introductory regression or choice-model analysis.
Assisting with interpretation of findings.
Developing tables, figures, and visualizations.
Reviewing relevant university transportation policies and practices.
Developing policy recommendations based on the findings.
Preparing an abstract and research poster for the FSU Undergraduate Research Symposium.
Skills that research assistant(s) may need: Required:
Strong interest in research and willingness to learn; reliability and ability to meet agreed deadlines; attention to detail; ability to communicate professionally and work collaboratively; basic familiarity with Microsoft Excel or similar software.
Recommended but not required:
Previous coursework in statistics, research methods, economics, public policy, transportation, sociology, psychology, or related fields. Experience with survey research, Excel, R, Python, SPSS, Stata, GIS, or data visualization would be helpful but is not necessary.
No previous research experience is required. Students will receive guidance on research methods and project-specific tasks.
Mentoring Philosophy
My mentoring approach is based on learning through active participation in the research process. I view undergraduate research as an opportunity for students not only to assist with an existing project but also to develop their own research skills, professional interests, and confidence as researchers.At the beginning of the project, I will work with each research assistant to understand their academic interests, existing skills, and learning goals. Responsibilities will initially be clearly structured, with additional independence provided as students gain experience. Research assistants will participate in different stages of the project, including research design, literature review, data collection, analysis, interpretation, and presentation of findings.
I encourage students to ask questions, challenge assumptions, propose ideas, and take ownership of parts of the project. Mistakes are treated as part of the learning process, provided that students communicate openly and use feedback to improve their work.
We will meet regularly to review progress, discuss challenges, and connect specific research tasks to broader methodological and policy questions. I will also provide feedback on students' analytical, writing, presentation, and research skills. By the end of the project, my goal is for research assistants to understand how an initial real-world problem can be transformed into a research question, investigated systematically, and translated into evidence-based recommendations.
Additional Information
This project is particularly appropriate for students interested in solving practical problems that affect everyday university life. Research assistants will have an opportunity to contribute to a project with direct implications for transportation, parking, sustainability, student experience, and university policy.The project does not require previous expertise in transportation research. Students from different academic backgrounds are encouraged to apply. Research responsibilities may be adjusted according to each student's interests, including quantitative analysis, surveys, behavioral research, policy analysis, data visualization, or transportation planning.
I would also slightly change the conceptual framing from “Why do students prefer driving rather than taking a bus?” to “What explains students' transportation choices, and what would make public transit a viable alternative to driving?”
That is stronger academically because you are not assuming in advance that students prefer driving. You first test whether they do, identify who prefers driving, determine why, and then estimate what could change that behavior. It gives you hypotheses that the UROP students can actually test and makes the project look much more like publishable research.
Link to Publications
https://orcid.org/0000-0001-5784-0607The Question of Palestine in the UN General Debate
Text anlaysis, Ideology, Foreign Policy, United Nations, Middle East, UN speeches, International Law
Research Mentor: Hashim Malallah,
Department, College, Affiliation: Political Sceince, Social Sciences and Public Policy
Contact Email: hm22o@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Political Sceince, Social Sciences and Public Policy
Contact Email: hm22o@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: Political science and pre-law are preferred, but not required.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Fully Remote
Approximate Weekly Hours: 5, 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: Political science and pre-law are preferred, but not required.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Fully Remote
Approximate Weekly Hours: 5, 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
When and why do leaders with different ideological orientations publicly support or criticize parties involved in conflict? I examine how left and right leaders differ in their UN General Debate discourse when they address global audiences using the Question of Palestine as a case study. While existing literature use the corpus of UNGD speeches in a variety of applications, relatively few studies classify political stance or sentiment on any global issue using speech data. To address this gap, I use a Transformer-based deep learning model to classify UNGD speeches based on their targeted stance and sentiment towards Israel and Palestine. I propose and test competing theoretical expectations about the effect of leaders’ ideology on rhetorical support for Israel and Palestine from 1947 to 2023. Using panel matching with difference-in-differences, I show that shifts to non-left governments increase attention to the Question of Palestine, whereas shifts to left governments reduce references to Israel’s right to exist and increase negative sentiment toward Israel. The findings are not solely driven by issue salience or selection into agenda topics, as they hold even in sessions when the question of Palestine is not on the agenda. The results imply that ideology shapes not only foreign policy preferences but also the attention to and expression of those preferences.In the next step of this project, I expand my classification scheme on UNGD speeches to evaluate causal mechanisms underlying support for Israel or Palestine. I will create a new handbook for hand coding that involves the following dimensions: human rights, colonialism, economic development, arms control.
Research Tasks: Hand coding UN General Debate speeches based on a handbook that include specific instructions. Students will read through speeches, learn patterns, and classify speeches based on the 4 dimensions: human rights, colonialism, economic development, arms control.
Skills that research assistant(s) may need: Attention to detail, interest in International law and international organizations!
Mentoring Philosophy
My mentorship philosophy centers on incorporating students’ ideas into my projects and giving them meaningful opportunities to contribute to the research process. I like to walk research assistants through each step of the project, allowing them to express their ideas and teaching them how we do quantitative political science research at the graduate level. My goal is to assist undergraduate students who are seeking graduate level studies in the social sciences, exposing them to how computational research can be used to answer pressing humanitarian and global issues.Additional Information
Link to Publications
https://hmalallah.github.io/HashimMalallah/Foudation Models and Agentic Systems for Multi-hazard Prediction
multi-hazard prediction, foundation models, agentic AI, spatiotemporal learning, graph learning, uncertainty quantification, scientific machine learning
Research Mentor: xc25@fsu.edu Xueqi Cheng, Mr.
Department, College, Affiliation: Department of Computer Science, Arts and Sciences
Contact Email: xc25@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Department of Computer Science, Arts and Sciences
Contact Email: xc25@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: 2
Relevant Majors: Open to all majors, preferring students with good CS and AI backgrounds.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Fully Remote
Approximate Weekly Hours: 10, During business hours
Roundtable Times and Zoom Link:
Number of Research Assistants: 2
Relevant Majors: Open to all majors, preferring students with good CS and AI backgrounds.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Fully Remote
Approximate Weekly Hours: 10, During business hours
Roundtable Times and Zoom Link:
- Day: Friday, September 4
Start Time: 2:00
End Time: 2:30
Zoom Link: https://fsu.zoom.us/j/5746622766
Project Description
Natural hazards often interact. Two or more hazards may occur in the same region within a meaningful time window, and an earlier hazard may change the likelihood or severity of a later hazard. For example, a tropical cyclone can lead to flooding, while a wildfire can increase later flood risk by changing vegetation and soil conditions. Predicting these compound and cascading events requires models that can learn relationships across different hazards.This project will study how foundation models and agentic systems can improve multi-hazard prediction. The foundation model will learn shared representations of hazard events, their surrounding conditions, and their spatial and temporal relationships. Hazard-specific components will process different forms of input data, while a shared model will estimate the probability, type, timing, and severity of subsequent hazards.
The agentic system will coordinate data, models, and evaluation tools available through PyHazards. Given an observed hazard, location, and time horizon, the agent will select suitable resources, construct a prediction workflow, run approved models, check the results, and generate a report with predictions, uncertainty, and supporting evidence. The project will model predictive relationships between hazards but will not claim that one hazard caused another based only on their co-occurrence.
The two undergraduate researchers will work on focused components of this broader project. One student will assist with model experiments and evaluation. The other will assist with agent development and testing. They will receive starter code, structured research tasks, regular technical guidance, and access to AI coding assistants. They will not be expected to build the complete system independently.
The expected outcomes include tested model and agent components, quantitative experiments, documented code, and a research report. Strong results will be prepared for submission to a workshop at a major AI conference and may contribute to a main-track submission.
Research Tasks: 1. Literature review
The students will read a selected set of papers on multi-hazard prediction, foundation models, spatiotemporal learning, and AI agents. They will summarize the research questions, methods, and limitations and discuss them during weekly meetings.
2. PyHazards onboarding
The students will learn the basic structure of PyHazards and reproduce existing examples using provided instructions and starter code. They will become familiar with its datasets, models, experiment configurations, and evaluation tools.
3. Data inspection and validation
Using prepared scripts, the students will inspect hazard data, check data quality, and verify the spatial and temporal relationships used to construct multi-hazard events. They will document missing data, unusual cases, and possible sources of bias.
4. Model experiments
The student focusing on foundation models will run controlled experiments using provided training pipelines. The student will compare shared multi-hazard representations with single-hazard baselines, test selected model components, and analyze when cross-hazard learning improves or reduces performance.
5. Agent development and testing
The student focusing on agentic systems will help define tools, prompts, and test cases for the research agent. The student will test whether the agent selects compatible resources, completes the requested workflow, reports the correct results, and avoids unsupported conclusions.
6. Evaluation and error analysis
Both students will organize experimental results, compare model and agent performance, examine failure cases, and create clear tables and figures. They will work with the mentor to determine which results support the research conclusions.
7.Documentation and research communication
The students will document their experiments and code, present progress during lab meetings, and contribute figures, results, and written sections to a final research report or conference paper.
Skills that research assistant(s) may need: Required
- Responsible and dependable. Students should complete agreed tasks and communicate early when they encounter problems.
- Hard-working and persistent. Research often involves unsuccessful experiments, debugging, and repeated revision.
- Willing to learn. Students should be open to feedback, unfamiliar methods, and new research tools.
- Strong foundations in mathematics, especially linear algebra, calculus, probability, or statistics.
- Basic understanding of artificial intelligence or machine learning through coursework, self-study, or project experience.
- Ability to work respectfully with the mentor and another student.
Recommended
- Basic familiarity with Python.
- Experience with an introductory machine learning or deep learning course.
- Interest in natural hazards, weather, climate, or scientific applications of AI.
- Experience with data analysis, PyTorch, Git, or Linux is helpful but not required.
Advanced programming experience is not required. Starter code, technical guidance, code reviews, and AI coding assistants will be available throughout the project.
Mentoring Philosophy
I view mentoring as a partnership in which students receive clear structure, honest feedback, and increasing ownership of their work. At the beginning of the semester, I will meet with each student to understand their goals, assess their current preparation, and define a focused role that matches their interests. We will agree on written goals, responsibilities, and milestones.We will hold a weekly team meeting to review progress, discuss problems, and plan the next steps. I will also meet with each student individually to provide feedback and discuss workload, learning goals, and professional development. Early in the project, I will provide selected readings, starter code, demonstrations, and close technical support. As students gain confidence, I will give them more responsibility for proposing experiments and interpreting results.
I value responsibility, curiosity, persistence, and honest communication more than prior technical experience. Students should feel comfortable asking questions and reporting failed experiments. We will treat failures as opportunities to examine evidence, improve methods, and learn.
Feedback will be specific, timely, respectful, and two-way. I will help students use AI coding assistants responsibly while ensuring that they understand and verify the work they submit. We will discuss research integrity, reproducibility, authorship, and credit at the start of the project. Students who make substantive contributions to a paper will be included as coauthors.
Additional Information
Link to Publications
https://scholar.google.com/citations?user=MWnSFPMAAAAJ&hl=en; https://labrai.github.io/PyHazards/The Gremlin’s Bedlam
Music Composition; Tuba; Concerto; Orchestration
Research Mentor: Dr. Clifton Callender, he/him
Department, College, Affiliation: Composition, Music
Contact Email: jg20w@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Composition, Music
Contact Email: jg20w@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: 2
Relevant Majors: Music, Music Theory, Music Composition, Music Education, Music Performance, or related fields. Students with strong interests in contemporary music, orchestration, acoustics, or interdisciplinary musical research are also encouraged to apply.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Partially Remote
Approximate Weekly Hours: 5–7 hours per week, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Number of Research Assistants: 2
Relevant Majors: Music, Music Theory, Music Composition, Music Education, Music Performance, or related fields. Students with strong interests in contemporary music, orchestration, acoustics, or interdisciplinary musical research are also encouraged to apply.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Partially Remote
Approximate Weekly Hours: 5–7 hours per week, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
- Day: Thursday, September 3
Start Time: 12:00
End Time: 2:00
Zoom Link: https://bio.site/tubagruber
Project Description
The Gremlin’s Bedlam is an ongoing research and creative project centered on the development of a new concerto for solo tuba and orchestra. The project investigates how a contemporary composer can expand the expressive and virtuosic possibilities of the tuba while maintaining effective relationships among the soloist, orchestra, musical form, and acoustic properties of the instrument.Research assistants will contribute to the investigative foundation of the composition by examining historical and contemporary tuba repertoire, orchestration practices, extended techniques, instrumental acoustics, and approaches to concerto writing. Particular attention will be given to how composers address balance, register, articulation, timbre, endurance, resonance, and the projection of a low-register solo instrument against an orchestra.
The research will directly inform compositional decisions in The Gremlin’s Bedlam. Students will have the opportunity to observe how scholarly and analytical research moves from repertoire study into practical artistic decisions within the development of a substantial new musical work.
Research Tasks: Research assistants may:
Conduct literature and repertoire reviews related to the tuba, orchestration, concerto writing, and instrumental acoustics.
Identify and study significant historical and contemporary works featuring solo tuba.
Analyze scores and recordings to investigate orchestral balance, register, timbre, texture, and treatment of the solo instrument.
Research conventional and extended tuba techniques and their notation.
Organize research findings, repertoire examples, and bibliographic sources.
Compare approaches used by different composers to integrate low brass soloists with large ensembles.
Assist with documenting the compositional and research process.
Participate in discussions connecting research findings with developing passages of The Gremlin’s Bedlam.
Contribute to the preparation of research findings for presentation at the FSU Undergraduate Research Symposium.
Skills that research assistant(s) may need: Required:
Curiosity and willingness to engage with unfamiliar music and research.
Reliability and ability to complete independent research assignments.
Ability to communicate findings clearly.
Recommended:
Ability to read music.
Familiarity with music theory or score reading.
Experience performing a brass instrument or studying composition.
Familiarity with orchestral repertoire.
Basic experience using academic databases, citation systems, or music notation software.
Prior experience with tuba performance is not required.
Mentoring Philosophy
My mentoring philosophy centers on giving students meaningful ownership of their research while providing the structure and guidance necessary for them to succeed. I want research assistants to understand not only what they are researching, but why their findings matter to the larger project.Students will begin by identifying their individual interests, existing strengths, and areas they would like to develop. Research responsibilities can then be shaped around those interests while contributing to the broader investigation surrounding The Gremlin’s Bedlam. I will meet regularly with research assistants to discuss findings, answer questions, establish achievable goals, and connect their research to the evolving composition.
Because creative research often involves experimentation, I want students to feel comfortable proposing ideas, questioning assumptions, and discovering that an initial approach may not produce the expected result. Those moments can become valuable parts of the research process.
My goal is for each assistant to finish the project with greater independence as a researcher, stronger analytical and communication skills, and a tangible understanding of how research can directly influence the creation of a new artistic work.
Additional Information
This project combines traditional academic research with creative practice. Research assistants will be able to follow the development of a contemporary concerto from research and repertoire analysis through compositional decision-making. Depending on the project's development and the student's interests, opportunities may also arise to observe rehearsals, review developing score materials, or interact with performers regarding the practical application of the research.Link to Publications
Distributed Fiber Optic Sensing of Temperature and Strain in Geotechnical and Materials Engineering
Fiber Optic, Geotechnical, Foundations, Pavements
Research Mentor: Scott Wasman,
Department, College, Affiliation: Civil and Environmental Engineering, FAMU-FSU College of Engineering
Contact Email: swasman@eng.famu.fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Civil and Environmental Engineering, FAMU-FSU College of Engineering
Contact Email: swasman@eng.famu.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: 1
Relevant Majors: Majors with laboratory and/or technical foundational components (sciences and mathematics)
Project Location: Engineering Campus
Research Assistant Transportation Required: Remote or In-person: In-person
Approximate Weekly Hours: 5-10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Number of Research Assistants: 1
Relevant Majors: Majors with laboratory and/or technical foundational components (sciences and mathematics)
Project Location: Engineering Campus
Research Assistant Transportation Required: Remote or In-person: In-person
Approximate Weekly Hours: 5-10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
- Day: Wednesday, September 2
Start Time: 1:00
End Time: 2:00
Zoom Link: Scott Wasman is inviting you to a scheduled Zoom meeting. Topic: Scott Wasman UROP Time: Sep 2, 2026 01:00 PM Eastern Time (US and Canada) Join Zoom Meeting https://fsu.zoom.us/j/98342058499 Meeting ID: 983 4205 8499
Project Description
Fiber optic sensing of temperature and mechanical strain in lab and field geotechnical and pavements systems is an emerging field of civil engineering. This type of sensing is very sensitive to small changes and is more cost effective than traditional sensing. Application of fiber to lab and field measurements offers a better understanding of these systems under physical and climatic stress, a primary focus of the professor. The project will involve working in the professors group to perform temperature and strain sensing of limestone, asphalt, reinforced concrete in the lab and in the field. Specific activities will be: working with samples, bonding fiber to samples, application to small models in the lab and field, using lab equipment to apply rate of strain load, data collection, data analysis, coding in Python or Matlab (if of interest), participating in research group presentations, participating in publications. The project will provide the student to work with fiber optics and learn a very new and promising technology that has applications beyond civil engineering, both large scale (>10 km) and small scale (mm), (aerospace, medical, biomedical, environmental, geology, oceanography, security, energy, power systems).Research Tasks: Literature review, experimental planning and setup, using lab equipment, data collection, data analysis, presenting results in a research group setting.
Skills that research assistant(s) may need: Required: interest in working in a lab and working with sensors, generally competent in excel, motivation to overcome challenges and communicate with professor.
Recommended: Curiosity about material behavior.
Mentoring Philosophy
Encouraging growth through challenges. Research is challenging and always a learning experience. I often work with mentees to develop their ability to learn how to learn, an important outcome that is useful in all aspects of life.Additional Information
Link to Publications
Power, Capital, and Agency in Doctoral Advising Relationships
advising; survey research; student agency; mentoring; power
Research Mentor: Charlotte M. Hayes, she/her/hers
Department, College, Affiliation: Educational Leadership and Policy Studies, Education, Health, and Human Sciences
Contact Email: cmh18cw@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Educational Leadership and Policy Studies, Education, Health, and Human Sciences
Contact Email: cmh18cw@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: 1
Relevant Majors: Open to all majors. This research would be especially relevant to education, sociology, psychology, or other social science majors, but I am happy to work with any student who is interested in the scope of this work.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Fully Remote
Approximate Weekly Hours: 5-8, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Number of Research Assistants: 1
Relevant Majors: Open to all majors. This research would be especially relevant to education, sociology, psychology, or other social science majors, but I am happy to work with any student who is interested in the scope of this work.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Fully Remote
Approximate Weekly Hours: 5-8, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
- Day: Monday, August 31
Start Time: 3:30
End Time: 4:30
Zoom Link: https://fsu.zoom.us/my/cmh18cw - Day: Tuesday, September 1
Start Time: 12:00
End Time: 1:00
Zoom Link: https://fsu.zoom.us/my/cmh18cw - Day: Wednesday, September 2
Start Time: 12:30
End Time: 1:30
Zoom Link: https://fsu.zoom.us/my/cmh18cw - Day: Thursday, September 3
Start Time: 1:30
End Time: 2:30
Zoom Link: https://fsu.zoom.us/my/cmh18cw - Day: Friday, September 4
Start Time: 3:00
End Time: 4:00
Zoom Link: https://fsu.zoom.us/my/cmh18cw
Project Description
This dissertation project examines power, capital, and agency in doctoral advising relationship within education related PhD programs. Drawing on theories of capital and power, this study creates two complimentary surveys - one for doctoral students, one for faculty advisors - to explore self perceptions of cultural, economic, social, and symbolic capital and how these perceptions are connected to advising relationships, agency, and responses to professional interactions. The full project will include three related papers: the first paper will focus on doctoral student survey responses, the second paper will focus on faculty advisor survey responses, and the third paper will examine connections across and between the student and faculty surveys to better understand how advising relationships are experienced.The undergraduate research assistant will help support the early stages of this project by helping develop the foundation for survey recruitment and survey design. One major component of this stage of the project involves building a faculty contact database from publicly available education related PhD program websites. Another major component will involve identifying and summarizing existing survey based research on cultural capital, economic capital, social capital, symbolic capital, student agency, mentoring, and advising relationships. Through this work, the undergraduate research assistant will gain experience with literature searches, survey development, sampling strategies, research organization, and the process of building a dissertation study from the ground up.
This project would be a good fit for students interested in higher education, graduate education, mentoring, sociology, student success, survey research, or social science research more broadly.
Research Tasks: The undergraduate research assistant will help with the following tasks:
1. Building a faculty contact database from publicly available education related PhD program websites to include faculty names, titles, emails, program affiliations, URLs, and relevant notes.
2. Conducting literature searches for published survey studies on cultural, economic, social, and symbolic capital.
3. Identifying existing survey measures related to student agency, advisor/advisee relationships, power, comfort raising concerns, help seeking, and advising/mentoring relationships.
4. Creating a survey measures metric that summarizes relevant scales, survey items, response options, sample populations, and reliability information when available.
5. Across all tasks: maintaining organized documentation of search strategies, sources reviewed, and decisions made during contact collection and literature review.
Skills that research assistant(s) may need: - Detail oriented and able to enter information accurately (required)
- Able to communicate clearly when questions or problems arise (required)
- Ability to work independently with guidance (recommended)
- Comfort using Excel (recommended)
- Ability to search academic databases or willingness to learn database search strategies (recommended)
- Interest in higher education, graduate education, mentoring, survey research, or social science research (recommended)
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Mentoring Philosophy
I see undergraduate research assistants as emerging scholars and collaborators. My goal is to provide structured guidance while helping the student develop transferable research skills in literature searches, survey development, data organization, research ethics, and scholarly communication. I aim to create a mentoring relationship grounded in care, transparency, reciprocity, and active listening. I want students to understand how each task contributes to the larger research process and to see themselves as meaningful contributors to knowledge production.My mentoring approach recognizes that students bring valuable lived experiences, questions, and strengths to the research process. I hope to create a space for students to ask questions, name areas they want to grow, and connect the project to their own academic and professional interests. I believe mentoring should include clear expectations, regular communication, and scaffolded opportunities for independence. I will provide training and examples at the beginning of each major task, offer feedback throughout the year, and encourage the student to reflect on what they are learning.
Through this project, I hope the student gains confidence navigating academic literature, organizing research materials, thinking critically about survey design, and understanding how research projects are developed. My goal is for the student to leave with stronger research skills, a clear sense of their own scholarly interests, and greater confidence in their ability to contribute to academic research.
Additional Information
Link to Publications
Deep Learning for Time-Series Anomaly Detection
Deep Learning; Time-Series Data; Anomaly Detection; Artificial Intelligence; Energy Systems
Research Mentor: Dr., Prof., Ravikumar Gelli, He, His, Him
Department, College, Affiliation: Florida State University/ECE Department, 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: Florida State University/ECE Department, 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: 2
Relevant Majors: Computer Science, Electrical Engineering, Computer Engineering, Data Science, Statistics, Applied Mathematics, or related quantitative disciplines. Students from other majors with an interest in AI and data analysis are also encouraged to apply.
Project Location: 2000 Levy Ave, Tallahassee, FL 32310 (Center for Advanced Power Systems)
Research Assistant Transportation Required: FSU Seminole Express provides service between the FSU main campus and the FAMU-FSU College of Engineering. Remote or In-person: Partially Remote
Approximate Weekly Hours: 5 to 8 hours per week, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Number of Research Assistants: 2
Relevant Majors: Computer Science, Electrical Engineering, Computer Engineering, Data Science, Statistics, Applied Mathematics, or related quantitative disciplines. Students from other majors with an interest in AI and data analysis are also encouraged to apply.
Project Location: 2000 Levy Ave, Tallahassee, FL 32310 (Center for Advanced Power Systems)
Research Assistant Transportation Required: FSU Seminole Express provides service between the FSU main campus and the FAMU-FSU College of Engineering. Remote or In-person: Partially Remote
Approximate Weekly Hours: 5 to 8 hours per week, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
- Day: Tuesday, September 1
Start Time: 12:00
End Time: 1:00
Zoom Link: https://fsu.zoom.us/j/6540925978
Project Description
Time-series data are generated continuously by many real-world systems, including electric power systems, renewable energy resources, sensors, communication networks, and other engineered systems. An important challenge is identifying unusual patterns or events within these data that may indicate equipment problems, unexpected operating conditions, disturbances, or other abnormal behavior.This project will explore how deep learning can be used to identify anomalies in time-series data. Undergraduate researchers will begin by learning how to visualize, organize, and analyze time-series datasets and distinguish normal behavior from unusual events. They will then explore fundamental anomaly-detection approaches and progressively develop deep-learning models for detecting abnormal patterns.
Students will work primarily with power and energy system datasets while learning broadly applicable skills in Python, data analysis, machine learning, and deep learning. The project is designed for students who are beginning research, and prior experience with deep learning or electric power systems is not required. Students will receive guidance and progressively take greater ownership of the data analysis, model development, evaluation, and interpretation of results.
Research Tasks: 1) Review introductory materials and selected research literature on time-series data and anomaly detection.
2) Learn basic Python tools for data analysis, visualization, and machine learning.
3) Explore and visualize time-series datasets from power, energy, or related engineering systems.
4) Clean and preprocess data, including handling missing values, scaling, segmentation, and preparation of training and testing datasets.
5) Identify and characterize normal and anomalous patterns in the data.
6) Implement baseline anomaly-detection methods and progressively explore deep-learning approaches such as neural networks, autoencoders, or sequence-based models.
7) Evaluate model performance using appropriate metrics and investigate when and why different approaches succeed or fail.
8) Document the methodology and results and prepare a research poster for the FSU Undergraduate Research Symposium.
Skills that research assistant(s) may need: Required:
Curiosity and interest in artificial intelligence, data, or engineering; willingness to learn new computational tools; ability to work consistently and communicate progress; attention to detail and willingness to troubleshoot problems.
Recommended but not required:
Basic familiarity with Python or another programming language; introductory mathematics or statistics; prior exposure to data analysis.
Prior experience with deep learning, machine learning, anomaly detection, or electric power systems is not required.
Mentoring Philosophy
My mentoring approach emphasizes learning through progressively structured research experiences. Students will initially receive clear guidance, background resources, and manageable research tasks to help them develop the necessary technical foundations. As their skills and confidence grow, they will be encouraged to take increasing ownership of their analysis, experiments, and research questions. Regular meetings will be used to discuss progress, troubleshoot challenges, interpret results, and identify next steps. I encourage students to ask questions, experiment with different approaches, and view unsuccessful results as part of the research and learning process. My goal is for students to develop not only technical skills, but also independence, critical thinking, research communication, and confidence in their ability to conduct research.Additional Information
This project is designed to provide an accessible entry point into undergraduate research in artificial intelligence and engineering. Students do not need prior research experience or advanced coursework in artificial intelligence or power systems. Students who are curious, motivated to learn, and interested in working with real-world data are encouraged to apply.Link to Publications
My research website https://gridai.fsu.edu/Mapping Meditation-Based Interventions in Couple and Family Research
Meditation, Mindfulness, Couple and Family Relationships, Mental Health, and Literature Review
Research Mentor: Mr. RUIMENG GAO, Raymond
Department, College, Affiliation: Human Development and Family Science, Education, Health, and Human Sciences
Contact Email: rg25b@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Human Development and Family Science, Education, Health, and Human Sciences
Contact Email: rg25b@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: 1
Relevant Majors: Psychology; Human Development and Family Science; Social Work; Sociology; Behavioral Sciences; Public Health
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Partially Remote
Approximate Weekly Hours: 5, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Number of Research Assistants: 1
Relevant Majors: Psychology; Human Development and Family Science; Social Work; Sociology; Behavioral Sciences; Public Health
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Partially Remote
Approximate Weekly Hours: 5, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
- Day: Monday, August 31
Start Time: 2:00
End Time: 3:00
Zoom Link: https://fsu.zoom.us/j/99931546274 - Day: Monday, August 31
Start Time: 3:00
End Time: 4:00
Zoom Link: https://fsu.zoom.us/j/98882291589
Project Description
Meditation and mindfulness practices are increasingly used to support mental health and relationships, yet researchers vary in how they define these practices, how they are delivered, and how they may contribute to changes in couple and family relationships. This project will conduct a structured review of existing research to examine how meditation- and mindfulness-based interventions have been conceptualized and used in relational contexts.The project will explore several questions: How do researchers define and distinguish meditation and mindfulness? What types of meditation practices have been studied with couples and families? How are these practices delivered (e.g., individually or with partners, online or in person, guided or self-guided)? What theories are used to explain how meditation may influence relationships? What relational outcomes, such as relationship satisfaction, attachment, communication, intimacy, compassion, or emotion regulation, have been examined?
The goal is to develop a clearer map of how meditation has been studied within couple and family research and identify gaps that may inform future research and intervention development. The project is expected to involve literature searching, study screening, organization and coding of research articles, and synthesis of findings. Results may contribute to a research poster and potentially a future scholarly manuscript.
Research Tasks: The research assistant will participate in multiple stages of a structured literature review. Tasks may include:
Conducting literature searches using academic databases (e.g., PsycINFO, PubMed, Google Scholar)
Screening article titles, abstracts, and full texts based on established inclusion and exclusion criteria
Organizing articles and maintaining a literature database
Extracting and coding information from selected studies, including definitions of meditation/mindfulness, intervention type, population, delivery format, duration/frequency, theoretical framework, relational outcomes, and measures
Collaboration on discuss articles, resolve coding questions, and refine the review process
Assisting with identifying patterns and gaps across the literature
Assisting with preparation of a UROP research poster and, depending on project progress, a scholarly manuscript
Skills that research assistant(s) may need: Required:
Attention to detail and organizational skills
Ability to work independently and meet deadlines
Willingness to learn research skills
Recommended:
Ability to read and understand academic articles
Interest in meditation, mindfulness, mental health, or couple and family relationships
Previous research or literature review experience (not required)
Mentoring Philosophy
My mentoring philosophy emphasizes collaboration, mutual respect, open communication, and growth. I believe that although mentors and mentees have different levels of research experience and responsibilities, both bring valuable perspectives to the research process. As a mentor, I hope to provide guidance based on my research experience while also respecting students' voices, ideas, interests, and creativity.I view mentoring as a balance between providing structure and encouraging independence. At the beginning of the project, I will provide more direct guidance and training to help the research assistant develop foundational research skills and understand the goals and expectations of the project. As their skills and confidence develop, I hope to gradually provide greater independence and ownership of their work. I encourage students to ask questions, propose new ideas, and respectfully challenge existing assumptions rather than simply follow instructions.
I also value transparent and direct communication. I hope to create an environment where expectations and feedback can be openly discussed and where mistakes are viewed as opportunities for learning rather than something to fear. At the same time, I believe growth often requires appropriate challenges, accountability, and willingness to move beyond one's comfort zone. Ultimately, I hope that our mentoring relationship allows us to learn from one another while helping the student develop the confidence, independence, creativity, and research skills necessary for their future academic and professional goals.
Additional Information
Link to Publications
https://digitalcommons.acu.edu/etd/893/Building Belonging: Relationship Education and Mental Health Prevention in Emerging Adulthood
Relationships, Mental Health, Emerging Adulthood, Social Connectedness, Prevention
Research Mentor: Sam Yu, He/Him/His
Department, College, Affiliation: Human Development and Family Science, Education, Health, and Human Sciences
Contact Email: shy25@fsu.edu
Research Assistant Supervisor (if different from mentor): Dr. Lenore McWey (Co-Advisor) She/Her/Hers
Research Assistant Supervisor Email: lmcwey@fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Human Development and Family Science, Education, Health, and Human Sciences
Contact Email: shy25@fsu.edu
Research Assistant Supervisor (if different from mentor): Dr. Lenore McWey (Co-Advisor) She/Her/Hers
Research Assistant Supervisor Email: lmcwey@fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Open to all majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Number of Research Assistants: 2
Relevant Majors: Open to all majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
- Day: Monday, August 31
Start Time: 12:00
End Time: 1:00
Zoom Link: https://fsu.zoom.us/j/9997165131 - Day: Wednesday, September 2
Start Time: 2:00
End Time: 3:00
Zoom Link: https://fsu.zoom.us/j/9997165131
Project Description
Emerging adulthood is a time of major change as young adults navigate new relationships, greater independence, and important life decisions. During this period, strong relationships and a sense of belonging can play an important role in supporting mental health and reducing feelings of loneliness and isolation.This project explores how romantic relationships, friendships, and other social connections can support emerging adults' well-being. It will also examine how research on healthy relationships and social connection can be translated into practical relationship education and public resources. The broader goal is to help emerging adults build meaningful relationships, strengthen their sense of belonging, and promote well-being before mental health concerns become more serious.
Research Tasks: Undergraduate research assistants will support multiple stages of the research and public scholarship process. Tasks may include:
- Conducting literature searches on relationships, sense of community, social connection, emerging adulthood, and mental health prevention.
- Reviewing and summarizing research on how romantic relationships and friendships may support well-being and reduce loneliness and isolation.
- Data analysis around what the current allocation of funding goes to for supporting young adults (i.e., on college campuses, etc.)
- Assisting with identifying key themes and patterns across studies.
- Evaluating how relationship and mental health research is communicated to the general public.
- Translating research findings into clear, accessible language for relationship education and public scholarship.
- Participating in regular research meetings to discuss findings, receive feedback, and develop research and professional skills.
- Contributing to potential research presentations, posters, reports, or other scholarly and public-facing products.
Skills that research assistant(s) may need: Required:
- Attention to detail and organization
- Reliability and ability to meet deadlines
- Ability to work collaboratively
- Willingness to learn
Recommended:
- Previous research or literature review experience
- Familiarity with APA
- Interest in relationship education, prevention, or public scholarship
Mentoring Philosophy
My mentoring philosophy centers on creating a supportive and collaborative environment where students feel comfortable learning, asking questions, and developing confidence in their abilities. I hope to meet students where they are, help them identify and unlock their own passions, and provide opportunities to connect research with their academic, professional, and personal interests.Teaching and mentorship have always been passions of mine, but I also view mentoring as a two-way learning process. Students bring new perspectives, questions, and ideas that can strengthen my own thinking and the quality of our work. I believe research is stronger through collaboration, as bringing together different perspectives can refine ideas and improve how findings are communicated and disseminated.
Ultimately, I hope students leave the experience with stronger research and communication skills, greater confidence in their interests, and an understanding of how research can extend beyond academia to educate and support communities.
Additional Information
I am particularly interested in public scholarship and translational research, bridging the gap between what we learn through research and how that knowledge is used in everyday life. I currently work with a public scholarship team that translates evidence-based relationship research into accessible resources for broader audiences.As a Marriage and Family Therapy PhD student, I hope to explore how research on relationships, belonging, and well-being can be translated into practical resources for both emerging adults and the therapists who work with them. This may include educational materials that therapists can use to support conversations with clients about relationships, social connection, and building supportive communities.
More broadly, I am interested in how relationship research can inform education, prevention programs, and community efforts that help young adults build meaningful relationships and feel more connected to the environments around them. Ultimately, I hope this work contributes to a larger conversation about how research can be used to better support emerging adults as they navigate relationships, mental health, and the transition into adulthood.
Link to Publications
https://myrelevate.comBuilding AI-Ready Datasets for Power and Energy Systems
Artificial Intelligence; Data Engineering; Power Systems; Energy Systems; Machine Learning
Research Mentor: Dr., Prof. Ravikumar Gelli, He, His,
Department, College, Affiliation: Florida State University, 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: Florida State University, 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: 2
Relevant Majors: Electrical Engineering, Computer Engineering, Computer Science, Data Science, Statistics, Applied Mathematics, Information Technology, or related disciplines. Students from other majors with an interest in data and artificial intelligence are also encouraged to apply.
Project Location: 2000 Levy Ave, Tallahassee, FL 32310. Center for Advanced Power Systems (CAPS)
Research Assistant Transportation Required: FSU Seminole Express provides service between the FSU main campus and the FAMU-FSU College of Engineering. Remote or In-person: Partially Remote
Approximate Weekly Hours: 5 to 8 hours per week, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Number of Research Assistants: 2
Relevant Majors: Electrical Engineering, Computer Engineering, Computer Science, Data Science, Statistics, Applied Mathematics, Information Technology, or related disciplines. Students from other majors with an interest in data and artificial intelligence are also encouraged to apply.
Project Location: 2000 Levy Ave, Tallahassee, FL 32310. Center for Advanced Power Systems (CAPS)
Research Assistant Transportation Required: FSU Seminole Express provides service between the FSU main campus and the FAMU-FSU College of Engineering. Remote or In-person: Partially Remote
Approximate Weekly Hours: 5 to 8 hours per week, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
- Day: Tuesday, September 1
Start Time: 1:00
End Time: 2:00
Zoom Link: https://fsu.zoom.us/j/6540925978
Project Description
Power and energy systems generate large amounts of data from sensors, simulations, smart meters, renewable energy resources, weather measurements, communication systems, and other sources. However, raw data are often incomplete, inconsistent, noisy, poorly labeled, or stored in formats that are difficult to use directly for artificial intelligence and machine learning.This project will explore how raw power and energy system data can be transformed into high-quality, AI-ready datasets. Undergraduate researchers will learn how to collect, organize, clean, visualize, label, and document different types of engineering data. Students will investigate common data-quality problems such as missing values, inconsistent timestamps, measurement errors, duplicated records, incompatible formats, and insufficient metadata.
The project will also explore how dataset design affects the performance and reliability of downstream AI and machine-learning applications. Students will work with real or simulated power and energy datasets while developing broadly applicable skills in Python, data analysis, data engineering, visualization, and responsible dataset preparation.
No prior experience in artificial intelligence, machine learning, or electric power systems is required. The project is designed as an accessible introduction to research for first-year and early undergraduate students.
Research Tasks: 1) Review introductory materials on datasets, data quality, and the role of data in artificial intelligence and machine learning.
2) Explore power and energy datasets from simulations, sensors, renewable energy systems, weather sources, or other publicly available resources.
3) Use Python-based tools to organize, visualize, and understand different types of data.
4) Identify data-quality problems such as missing values, duplicate records, inconsistent timestamps, outliers, noise, and incompatible data formats.
5) Develop and test procedures for data cleaning, synchronization, normalization, labeling, and transformation.
6) Organize datasets into consistent structures suitable for machine-learning and deep-learning applications.
7) Develop metadata and documentation describing the dataset, variables, units, sources, processing steps, and limitations.
8) Evaluate dataset quality and investigate how different data-preparation choices affect simple AI or machine-learning models.
9) Document the research process and prepare results for presentation at the Undergraduate Research Symposium.
Skills that research assistant(s) may need: Required:
-- Interest in artificial intelligence, data, or engineering
-- Willingness to learn programming and data-analysis tools
-- Attention to detail
-- Ability to organize information carefully
-- Willingness to communicate progress and work consistently
Recommended but not required:
-- Basic familiarity with Python, MATLAB, Excel, or another computational tool
-- Introductory programming experience
-- Basic mathematics or statistics
-- Experience working with spreadsheets or structured data
Prior experience with machine learning, deep learning, data engineering, or electric power systems is not required.