UROP Project
Applying social behavior to improve management strategies for wild chacma baboons in Nature's Valley, South Africa
primate; behavior; conservation
Research Mentor: Dr. or Prof. Dr. Kris Sabbi, she/her
Department, College, Affiliation: Anthropology, Arts and Sciences
Contact Email: ksabbi@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Anthropology, Arts and Sciences
Contact Email: ksabbi@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: 4
Relevant Majors: Open to all majors; Especially interested in students who hope to gain experience in wild animal research in majors like biological science, anthropology, psychology and/or behavioral neurosciences.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10 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: 4
Relevant Majors: Open to all majors; Especially interested in students who hope to gain experience in wild animal research in majors like biological science, anthropology, psychology and/or behavioral neurosciences.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10 hours per week, 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: 2:00
End Time: 3:30
Zoom Link: https://fsu.zoom.us/my/ksabbi - Day: Thursday, September 3
Start Time: 2:00
End Time: 3:30
Zoom Link: https://fsu.zoom.us/my/ksabbi
Project Description
Seeking undergraduate researchers to work on a project about wild chacma baboon behavior and how we can apply behavioral methods to improve wildlife management strategies in Nature's Valley, South Africa. The research project comprises a long-term observational study of wild chacma baboons that range in and around Tsitsikamma National Park, in South Africa, and surrounding residential and agricultural areas. The primary goal of the project is to leverage specific knowledge about baboon behavior including ranging, space-use, dietary profiles, and social interactions to shape locally-led efforts to manage baboon behavior and reduce human-wildlife conflict. Throughout our work, we aim to apply behavioral evidence to directly inform and improve conservation strategy, and, in turn, directly measure the effects and effectiveness of the plans that we implement. This work is done in collaboration with an international team of researchers and local conservationists on the ground, and at academic institutions in the states. To give students a sense of our research breadth, recent scientific output includes presentations on our recent experimental intervention of adjusting waste-management to test the effectiveness of new model of wildlife-proof wastebin and estimating the impacts of baboons as seed dispersers and destroyers for local forest restoration. We also have a special focus on diet and nutrition, with two projects documenting unique species of mushroom that are eaten by the baboons, and the balance of native versus non-native plant resources consumed by baboons. Our current focus is on developing projects that analyze our long-term data on social behavior and health, especially regarding two very unique demographic and social events that have occurred in the last three years.Available roles in the project include data entry, management, and analysis (based on skill level) with opportunities for independent work that could lead to, e.g. presenting findings during a conference, developing a senior thesis, or preparing for field experiences in primatology/animal behavior. While initial research will be limited to working with existing data collected by our field team, it is possible for students to work toward a project in the field in subsequent years/summers.
Research Tasks: Primary needs include data entry, management, and preliminary analysis (depending on existing skillset).
While reviewing the literature is less of a focus at the moment, student researchers may also be asked to help support literature review and analysis on a project-by-project basis.
Skills that research assistant(s) may need: This project is open to students with little to no prior experience in research or animal behavior - so long as students do have a vested interest in the topics of behavior and applied conservation, and the motivation to learn!
Recommended skills include spreadsheet (such as Excel and Google Sheets) and analytical software (ideally with R but other programs are also very useful). Previous coursework and/or experience in statistical analyses is also incredible useful.
Mentoring Philosophy
I see my role as a research mentor as creating opportunities and then coaching students toward the skills they need to achieve their own research goals - whether that's building a foundation for graduate school, gaining fieldwork experience, or simply learning what it feels like to ask and answer a real scientific question. As a first-generation college student myself, I know firsthand how valuable that first research opportunity can be, and how hard it can be to find. I'm committed to lowering barriers that keep students from fieldwork and research.My baboon research offers a rich training ground for that work both in the field and with my lab at FSU. From the outset, my work, in partnership with the community-led conservation group Nature's Valley Trust, has been student-centered and grounded in research- and inquiry-based learning. My approach starts with establishing clear expectations tailored to each student's background and goals, then shifts toward increasing independence as they build confidence. That means hands-on training in methods and analysis early on, regular one-on-one time to work through challenges together, and, as students gain footing, room to take ownership of a question that's genuinely theirs. Students can get involved at every stage and past students have used this project for senior theses and master's research. I also coach students through disseminating their work (e.g. preparing conference presentations or posters) since sharing results is where a project starts to feel like real science. I've mentored multiple award-winning undergraduate projects that went on to publication.
Additional Information
Students can learn more about my work and outreach at my website (included above). I also included a link from a community-facing talk that I gave recently to update local residents on our research progress and plans for future work (as a note: this talk was before my appointment started at FSU so please excuse my previous affiliation).Link to Publications
krissabbi.com; https://www.youtube.com/watch?v=rKg0duu98s4&t=1sSupporting the Child Welfare Workforce: Evaluation of a Multi-Part Well-Being Initiative
Child Welfare, Workforce Well-Being, Somatic Regulation, Mindfulness, Program Evaluation
Research Mentor: Kristine Posada, she/her/hers
Department, College, Affiliation: The Florida Institute for Child Welfare, Social Work
Contact Email: kposada@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: The Florida Institute for Child Welfare, Social Work
Contact Email: kposada@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: This project may be of interest to students in social work, public health, psychology, behavioral health, nursing, human development and family science, or related fields who are interested in learning more about the experiences and well-being needs of frontline professionals and how research can inform practical workforce supports.
Project Location: The Florida Institute for Child Welfare: 2139 Maryland Circle Suite 1100, Tallahassee, FL 32303
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Fully 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:
Not participating in the roundtable
Number of Research Assistants: 1
Relevant Majors: This project may be of interest to students in social work, public health, psychology, behavioral health, nursing, human development and family science, or related fields who are interested in learning more about the experiences and well-being needs of frontline professionals and how research can inform practical workforce supports.
Project Location: The Florida Institute for Child Welfare: 2139 Maryland Circle Suite 1100, Tallahassee, FL 32303
Research Assistant Transportation Required: No, the project is remote Remote or In-person: Fully 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:
Not participating in the roundtable
Project Description
The Florida Institute for Child Welfare is partnering with a Florida child welfare organization to implement and evaluate a three-part workforce well-being initiative designed to support child welfare professionals within the realities of their day-to-day work. Child welfare professionals routinely work with children and families experiencing trauma, crisis, and complex needs while also navigating high workloads, time pressures, difficult conversations, and high-stakes decision making. These demands can contribute to chronic stress, burnout, secondary traumatic stress, and other challenges to workforce well-being.The initiative will include three interconnected areas of workforce support: somatic regulation, resilient practice with peer support, and mindfulness-based well-being. The experiences are designed to build on one another while offering practical strategies and resources that can be integrated into the realities of child welfare work.
This work builds on Regulation in Real Time, a somatic-based training that our research team piloted with child welfare professionals across three Florida circuits in Spring 2026. The training combines education about stress and nervous system responses with brief practices such as grounding, breathing, and movement. A mixed-method evaluation assessed the acceptability, appropriateness, usability, and feasibility of the training and gathered feedback about participants’ experiences using the practices in their day-to-day work. Findings from the pilot are being used to refine Regulation in Real Time as it becomes one component of the larger well-being initiative.
The broader implementation will provide an opportunity to better understand how different workforce well-being supports are experienced within a child welfare organization, how participants use the practices over time, and what we can learn to inform future implementation. There is still limited research on somatic and other well-being approaches developed specifically for child welfare professionals, particularly approaches designed to be practical within the demands and constraints of frontline work.
The UROP student will be mentored by Kristine Posada, MSW, Assistant in Research Faculty at the Florida Institute for Child Welfare. Her work centers on applied child welfare research and evaluation, with a particular interest in the experiences and well-being of frontline professionals and in how research can be used to develop supports that are practical, thoughtful, and responsive to the realities of their work.
This project may be of interest to students in social work, public health, psychology, behavioral health, nursing, human development and family science, or related fields who are interested in learning more about the experiences and well-being needs of frontline professionals and how research can inform practical workforce supports.
Research Tasks: The research assistant may assist with interviews or focus groups, transcript coding, qualitative data organization, and other research or program coordination activities related to the workforce well-being evaluation. Specific tasks may vary based on the stage of the evaluation and the student’s skills and interests.
Skills that research assistant(s) may need: - Strong organization and attention to detail: Required
- Ability to follow instructions, work independently, and ask questions when needed: Required
- Ability to handle sensitive research information with professionalism and confidentiality: Required
- Interest in child welfare, workforce well-being, social work, behavioral health, or related areas: Recommended
- Experience conducting literature searches or literature reviews: Recommended
- Previous coursework or experience with qualitative or mixed-methods research: Recommended, but not required
- Interview and focus group procedures: Training will be provided
- Qualitative transcript coding and data organization: Training will be provided
- Research data management and project documentation: Training will be provided
- Research software used by the project: Training will be provided as needed
Mentoring Philosophy
My approach to mentoring is grounded in relationship, participation, curiosity, and clear and compassionate communication. I want students to feel respected, comfortable asking questions, and meaningfully involved in the research process while understanding how their contributions connect to the larger goals of the work.Creating space for curiosity and critical reflection is also important. Research does not happen outside of context, and I value conversations that invite students to think about the assumptions we bring to our work, whose perspectives are represented, how systems and environments shape people’s experiences, and how research can remain responsive to the communities and professionals it is intended to serve.
Mentoring is something I try to approach with the individual in mind. Students bring different interests, strengths, experiences, and areas of curiosity, and I want those differences to help shape the experience. Clear expectations and thoughtful feedback can provide a foundation for learning, while still leaving room for students to explore areas of the research that genuinely interest them.
Ultimately, I hope students leave the experience with greater confidence in themselves, stronger critical thinking skills, and a deeper understanding of how their interests and contributions can connect to research that matters to them and to the communities we work alongside.
Additional Information
Our team is also actively disseminating findings from this work. We presented findings from the Regulation in Real Time pilot at the 2026 Florida Coalition for Children Conference, and a related manuscript has been submitted for publication and is currently under review. We hope to continue sharing findings through conference presentations and other dissemination opportunities in 2027.Link to Publications
Beyond the chronological age: The impact of subjective age on L2 motivation and working memory among L2 language learners aged over 60 years old
subjective age, L2 motivation, working memory,
Research Mentor: Dr Wenxiao Li ,
Department, College, Affiliation: Educational Psychology, Education, Health, and Human Sciences
Contact Email: wl20bb@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Educational Psychology, Education, Health, and Human Sciences
Contact Email: wl20bb@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
Project Location: On FSU Main Campus
Research Assistant Transportation Required: 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: 2
Relevant Majors: Open to all majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required: 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: Tuesday, September 1
Start Time: 12:00
End Time: 12:30
Zoom Link: https://fsu.zoom.us/j/2958140910
Project Description
With a mixed-method design, this study therefore investigated how age identity influenced elderly’s L2 motivation (i.e, L2 self, ought-to L2 self, and anti-ought-to self) and (perceived) working memory. A questionnaire, adapted from established frameworks (Dörnyei, 2009; Thompson, 2021; Vallat-Azouvi et al, 2012), was distributed among 120 elderly L2 learner from China and the US respectively. Later, complementary qualitative data were obtained through semi-structured interviews. Noticeably, due to the different perspective of aging in various cultures, this study also involves a culture perspective, which was emphasized in the later semi-structured interview as well.The regression analysis from the preliminary study showed that age identity outperformed chronological age in predicting both their L2 motivation and perceived working memory. The thematic analysis further indicated the crucial role of cultural factors on their motivation and approaches to manage learning-related challenges.
Research Tasks: data analysis
Skills that research assistant(s) may need: SPSS, basic statistic knowledge preferably in relation to regression and SEM
Mentoring Philosophy
My mentoring philosophy is centered on creating a collaborative, inclusive, and mentee-centered research environment. As an international scholar with a background in second and foreign language teaching and research, I understand that students enter research environments with different academic experiences, cultural backgrounds, communication styles, and levels of confidence. Therefore, I believe effective mentoring begins with respectful and flexible communication. I aim to create an environment in which students feel comfortable asking questions, expressing their ideas, and viewing themselves as meaningful contributors to the research process.I also believe undergraduate research should be hands-on. Rather than limiting students to isolated or routine research tasks, I provide mentees with opportunities to experience multiple stages of the research process, including reviewing and synthesizing literature, developing research materials, collecting and organizing data, coding and analyzing data, interpreting findings, and preparing research for dissemination. Through these experiences, students can better understand how individual research activities connect to larger research questions and gradually develop the confidence and skills needed to work more independently.
At the same time, I want research to be an engaging and enjoyable learning experience. I therefore emphasize clear expectations, structured tasks, frequent communication, and collaboration while adjusting the level of guidance according to each mentee's experience, interests, and goals. Ultimately, my goal as a mentor is not simply to teach students how to complete research tasks, but to help them develop confidence, curiosity, and a sense of ownership in the research process.
Additional Information
Link to Publications
https://scholar.google.com/citations?user=dEIwgfgAAAAJ&hl=enInvestigating the Impact of Generative AI Use on Cognitive Offloading and Students' Epistemic Agency During Information-seeking Tasks
Generative AI, Cognitive Offloading, Epistemic Agency, Information-Seeking Behavior and Student Learning
Research Mentor: aoa24@fsu.edu AYOOLA OLUWASEUN AJAYI, Mr.
Department, College, Affiliation: School of Information, Communication and Information
Contact Email: aoa24@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: School of Information, Communication and Information
Contact Email: aoa24@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.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: Partially Remote
Approximate Weekly Hours: 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: Remote or In-person: Partially Remote
Approximate Weekly Hours: 10, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
- Day: Friday, September 4
Start Time: 12:00
End Time: 2:00
Zoom Link: https://fsu.zoom.us/j/9893834992
Project Description
This project investigates how students use generative AI tools during information-seeking tasks and how that use may influence their cognitive engagement and epistemic agency. It examines whether students rely on AI to perform tasks such as searching, interpreting, evaluating, organizing, and synthesizing information, or whether they use it as a scaffold while retaining responsibility for judgment and decision-making. Drawing on Kuhlthau’s Information Search Process and Distributed Cognition Theory, the project focuses on how generative AI may redistribute cognitive work between students, AI systems, search tools, sources, and written products. The study aims to clarify when AI-supported information seeking promotes learning and independent thinking, and when it may encourage excessive cognitive offloading or reduce students’ involvement in constructing and validating knowledge.Research Tasks: Assisting with the development and refinement of study instruments, such as interview protocols, surveys, observation guides, or information-seeking tasks.
Recruiting and scheduling student participants, as applicable.
Supporting data collection through interviews, surveys, think-aloud sessions, screen recordings, or observation of students completing information-seeking tasks.
Transcribing and anonymizing interview or session recordings.
Coding qualitative data related to students’ AI use, prompting behavior, source evaluation, cognitive offloading, uncertainty, and epistemic agency.
Assisting with quantitative data entry, cleaning, and descriptive analysis of survey or task-performance data.
Comparing students’ information-seeking processes with and without generative AI support.
Maintaining organized research records, documenting coding decisions, and assisting with data quality checks.
Skills that research assistant(s) may need: Required skills
Ability to locate, read, and summarize scholarly sources.
Strong written and verbal communication skills.
Careful organization and attention to detail.
Ability to follow research protocols and maintain confidentiality.
Basic proficiency with Microsoft Office or Google Workspace.
Willingness to learn qualitative and quantitative research procedures.
Recommended skills
Familiarity with generative AI, information-seeking behavior etc.
Experience conducting interviews, surveys, observations, or think-aloud sessions.
Experience transcribing, anonymizing, or coding qualitative data.
Familiarity with Excel, Google Sheets, or statistical software.
Experience recruiting or working with student participants.
Mentoring Philosophy
I view mentoring as a collaborative relationship grounded in mutual respect, clear communication, and a commitment to the mentee’s development. I will work with each research assistant to understand their interests, goals, strengths, and areas for growth and will provide guidance that is appropriately matched to their experience and responsibilities.My goal is to create a supportive environment in which research assistants can ask questions, learn from mistakes, and gradually take ownership of their work. I will provide clear expectations, explain the purpose behind assigned tasks, offer regular feedback, and encourage assistants to reflect on their progress. As their skills develop, I will support them in moving from structured assignments toward greater independence in literature searching, data collection, analysis, and research communication.
I also believe effective mentoring should connect technical research training with broader professional development. I will share my own experiences where helpful, model careful and ethical research practices, and encourage assistants to develop confidence in communicating their ideas. Together, we will establish achievable goals and maintain accountability while recognizing that learning often involves uncertainty, revision, and productive challenges. Ultimately, I hope each research assistant leaves the project with stronger research skills, greater intellectual confidence, and a clearer understanding of how their contributions support the study.
Additional Information
This project offers research assistants an opportunity to gain hands-on experience with interdisciplinary research at the intersection of information science, education, cognitive psychology, and generative artificial intelligence. Prior experience with AI research or qualitative and quantitative methods is not required; training and guidance will be provided. Ideal applicants are curious, reliable, attentive to detail, and interested in how emerging technologies shape learning, information evaluation, and students’ decision-making. Research assistants will be expected to participate consistently in project meetings, communicate progress, follow ethical research procedures, and contribute thoughtfully to the development of the study.Link to Publications
https://scholar.google.com/citations?user=Hu4_XVgAAAAJ&hl=en&oi=aoTowards an AI-Driven Laboratory for Autonomous Assembly of van der Waals Quantum Materials
Quantum Materials, Artificial Intelligence, Nano technology
Research Mentor: zlu2@fsu.edu Zhengguang Lu, Dr.
Department, College, Affiliation: Department of Physics, Arts and Sciences
Contact Email: zlu2@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Department of Physics, Arts and Sciences
Contact Email: zlu2@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
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: In-person
Approximate Weekly Hours: 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: 2
Relevant Majors: Open to all majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Remote or In-person: In-person
Approximate Weekly Hours: 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: 2:00
End Time: 4:00
Zoom Link: https://mit.zoom.us/j/6671590879 - Day: Tuesday, September 1
Start Time: 2:00
End Time: 5:30
Zoom Link: https://mit.zoom.us/j/6671590879 - Day: Wednesday, September 2
Start Time: 2:00
End Time: 5:30
Zoom Link: https://mit.zoom.us/j/6671590879 - Day: Thursday, September 3
Start Time: 5:00
End Time: 6:00
Zoom Link: https://mit.zoom.us/j/6671590879
Project Description
Atomically thin two-dimensional materials can be assembled layer by layer to create artificial materials with properties that do not exist naturally. These van der Waals (vdW) heterostructures provide an important platform for studying quantum phenomena including superconductivity, magnetism, topology, and strongly correlated electronic states. However, fabrication of these structures still relies heavily on researchers manually identifying microscopic flakes, aligning them under a microscope, controlling contact between layers, and adjusting many experimental parameters through trial and error. This limits both throughput and reproducibility.The goal of this project is to develop the foundation of an AI-driven vdW assembly laboratory in which computer vision, automated instrumentation, and AI agents work together with human researchers to fabricate two-dimensional heterostructures. The system will use optical images to identify and characterize suitable flakes, determine their position and orientation, assist with alignment and transfer, record experimental parameters and images throughout fabrication, and ultimately learn from previous assembly attempts.
A longer-term goal is to create a closed-loop experimental platform in which an AI system can not only execute predefined procedures but also recognize uncertainty or experimental failures, suggest corrective actions, and improve future fabrication strategies.
Undergraduate researchers will participate in developing and testing individual components of this system. Depending on their interests and background, students may focus on computer vision and machine learning, laboratory automation and robotics, 2D-material fabrication, or experimental-data analysis. The project therefore provides an opportunity to work at the intersection of artificial intelligence, experimental physics, robotics, and quantum materials while contributing to the development of a new approach to scientific experimentation.
Research Tasks: Research assistants will contribute to one or more of the following components:
1. Literature review and AI-driven system design
Study recent developments in AI-driven scientific laboratories, autonomous experimentation, computer vision, and automated fabrication of 2D materials. Identify experimental steps in vdW fabrication that can be automated or assisted by AI.
2. Computer vision for 2D materials
Collect and organize optical microscope images of graphene, hBN, and other two-dimensional materials. Annotate images to create training and validation datasets.Develop or evaluate algorithms for detecting flakes and determining their size, shape, thickness contrast, orientation, and location. Quantitatively evaluate detection accuracy and reliability.
3. Automated microscope and assembly control
Develop Python-based interfaces for cameras, motorized stages, microscope focus, and other components of a vdW transfer system. Implement automated positioning, focusing, image acquisition, alignment, and tracking procedures. Establish deterministic safety limits so that automated or AI-generated commands cannot damage samples or equipment.
4. Closed-loop AI-assisted assembly
Record images, stage coordinates, temperatures, alignment parameters, and experimental outcomes during assembly. Develop methods for detecting unsuccessful alignment, loss of focus, contamination, or uncertain flake identification.Explore AI-agent workflows that analyze the current experimental state and recommend the next appropriate action while leaving hardware execution to validated control software.
5. Hands-on Nano fabrication of real quantum chip
6. Testing and benchmarking
Perform controlled tests using graphene, hBN, and related 2D materials. Compare AI-assisted and conventional manual procedures in terms of accuracy, reproducibility, time, and success rate. Document results and contribute to the development of the final UROP research poster.
The exact tasks will be matched to the student's interests and experience. A student is not expected to complete the entire autonomous laboratory during one UROP project; instead, each student will take ownership of a well-defined component that contributes to the larger platform.
Skills that research assistant(s) may need: Required:
Curiosity and strong interest in experimental science, artificial intelligence, robotics, or quantum materials. Willingness to learn new laboratory and computational techniques. Careful attention to detail and ability to document work systematically. Ability to work both independently and collaboratively.
Recommended, but not required:
Basic Python programming. Experience or coursework in physics, computer science, engineering, mathematics, or a related area. Familiarity with image processing, computer vision, machine learning, or neural networks. Experience with microscopes, electronics, robotics, motorized stages, or instrumentation. Interest in hands-on experimental work.
Students with a primarily computational background and students with a primarily experimental background are both encouraged to apply.
Mentoring Philosophy
My goal in mentoring undergraduate researchers is to help students develop from learners into increasingly independent scientific problem-solvers. Because UROP students may enter research with very different backgrounds, I begin by identifying each student's interests, strengths, and previous experience and then define an initial project with clear and achievable milestones. Students will first receive hands-on training and work closely with me and other members of the research group. As they gain experience, they will progressively take ownership of a specific component of the project and be encouraged to propose their own solutions, test ideas, analyze results, and decide what should be tried next. Regular meetings will be used not only to discuss progress but also to understand the reasoning behind experimental and computational decisions. This project is particularly well suited to learning through iteration. Machine-learning models fail, automated instruments make imperfect decisions, and experimental fabrication does not always work on the first attempt. I encourage students to treat these outcomes as information: identify why something failed, document it carefully, and design the next test. At the same time, physical experiments will use clearly defined safety procedures and validated control layers before students or AI systems interact with laboratory hardware. My objective is for each UROP student to finish the project with both a concrete research contribution and a stronger ability to formulate questions, work independently, communicate scientific results, and approach unfamiliar problems with confidence.Additional Information
Link to Publications
https://scholar.google.com/citations?user=tkQPsr8AAAAJ&hl=enRe-performing the Masquerade: Cultural Translation in a TikTok Comment Section
Yoruba masquerade; digital spectatorship; audience reception; cultural translation
Research Mentor: Lucy Nyambeki Oruta, She,Her,Hers
Department, College, Affiliation: Theatre, Fine Arts
Contact Email: orutalucy@gmail.com
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Theatre, Fine Arts
Contact Email: orutalucy@gmail.com
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
Project Location: Remote
Research Assistant Transportation Required: No, the project is remote 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: 2
Relevant Majors: Open to all majors
Project Location: Remote
Research Assistant Transportation Required: No, the project is remote 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
Re-performing the Masquerade: Cultural Translation in a TikTok Comment SectionYoruba masquerade traditions such as Egúngún are not reducible to aesthetic display alone; they activate relationships among living communities, ancestral presence, memory, movement, rhythm, and sacred space. Their meanings emerge from a larger performance environment that includes performers, witnesses, spatial arrangements, cultural knowledge, and shared cosmological frameworks. When a recording of such a performance enters a social media platform—in this study, TikTok—it is separated from much of that environment and re-encountered through the platform’s compressed visual frame, soundtrack, caption, and public comment section.
The TikTok video anchoring this study offers one example of this displacement. Commenters attempt to make the masquerade intelligible by naming it as “spirit,” “demon,” “costume,” “culture,” or “entertainment,” while others respond with explanations, corrections, ridicule, or competing claims to cultural knowledge. These exchanges matter because they do not simply document audience reactions; they participate in producing the performance’s digital meaning and afterlife. This project therefore asks: How do TikTok commenters re-perform a Yoruba masquerade by naming, fearing, explaining, correcting, and culturally relocating what they see?
The project employs an interdisciplinary digital performance historiography that combines performance-centered audience reception with corpus-assisted text analysis. Drawing from Susan Bennett’s work on theatre audiences and Caroline Heim’s concept of the audience as performer, it approaches commenting spectators as active producers of meaning. The study does not claim to represent TikTok’s entire audience; it examines the visible, self-selecting performances of spectatorship produced by users who respond publicly to the video and to one another.
The available comments associated with the video will first be organized as a small digital corpus. Where appropriate, natural language processing and computational linguistic methods will be used to locate recurring terms, collocations, naming practices, and patterns of response. These tools will support the discovery and organization of patterns rather than determine their cultural meaning or reduce the comments to automated sentiment categories.
The computational mapping will guide the selection of approximately 10–15 substantive comment threads for close performance-reception analysis. The project’s central unit of interpretation will not be the isolated comment but the spectatorial exchange: an initial interpretation followed by replies that may correct, affirm, resist, mock, or redirect it. The original video will also be examined through its movement, costume, rhythm, sound, camera framing, duration, caption, and hashtags. Within the selected threads, the research team will attend to acts of naming, expressions of fear or fascination, claims to cultural authority, corrective explanations, and the acceptance or refusal of cultural knowledge. This movement between corpus-level patterns and close reading will allow the project to remain attentive both to recurring language and to the cultural, relational, and performative contexts in which that language appears.
Diana Taylor’s archive–repertoire framework will help the research team consider what happens when an embodied practice grounded in communal and ancestral transmission becomes a digital trace surrounded by new textual performances. The video preserves a trace of the masquerade, but the comment section also rescripts its meaning for spectators removed from its original cultural and performance environment.
Ultimately, this project investigates the digital afterlife of one performance: who acquires the authority to name it, how cultural knowledge is asserted or refused, and how spectators collectively remake what they have seen.
Research Tasks: Locate and summarize 10 key sources on Yoruba masquerade, audience reception, digital spectatorship, computational linguistics, and digital historiography using a structured format: claim, method, connection, question, and quotation.
Create a timestamped performance score of the TikTok video, documenting movement, costume, rhythm, sound, camera framing, captioning, hashtags, and significant visual transitions.
Collect, anonymize, and organize the available public comments and video metadata into a small, searchable digital corpus following appropriate research-ethics practices.
Use qualitative coding and, where appropriate, natural language processing to map recurring terms, collocations, naming practices, and response patterns; use these findings to select 10–15 spectatorial exchanges for close analysis.
Prepare two or three analytical memos and create visual representations of the findings for the collaborative FSU Undergraduate Research Symposium poster.
Skills that research assistant(s) may need: Required:
Interest in performance, cultural interpretation, digital media, or language.
Careful reading, clear writing, organization, and attention to detail.
Cultural humility and respectful engagement with African performance and spiritual traditions.
Willingness to work collaboratively across disciplinary approaches.
Recommended but not required:
Coursework or experience in natural language processing, computational linguistics, corpus linguistics, computer science, data science, or digital humanities.
Familiarity with Python, R, text-processing tools, spreadsheets, or data visualization.
Interest in applying computational methods to questions of performance, cultural memory, audience reception, and digital historiography.
Coursework in Theatre and Performance Studies, African or Africana Studies, Anthropology, Religion, Media Studies, or Linguistics.
Students are not expected to possess all these skills. The project is particularly suited to students interested in bringing computational and humanistic methods into conversation.
Mentoring Philosophy
My mentoring philosophy begins where my scholarship does: with the moment doubt becomes inquiry. I call my approach T.R.A.C.E.—Trust, Reciprocity, Accountability, Curiosity, and Experimentation. Like this project, which follows the digital traces through which performance acquires meaning, mentorship requires attending to the questions and experiences through which a student becomes a researcher.Trust means creating a respectful environment in which mentees can acknowledge what they do not know, examine assumptions, and ask questions without performing expertise. Reciprocity recognizes that mentoring is an exchange: I bring experience in theatre, performance, pedagogy, and historiography, while a mentee may bring computational, linguistic, cultural, or lived knowledge.
Accountability begins by identifying each student’s goals and strengths and creating a manageable plan for the five-hour weekly commitment. Each mentee will own a defined part of the project and receive clear expectations, regular feedback, and opportunities for revision.
Curiosity means remaining with uncertainty long enough to formulate better questions. Our meetings will be spaces of collaborative inquiry where sources, interpretations, and methods can be tested rather than accepted automatically. Experimentation means treating a source that leads nowhere, a coding category that collapses, or a computational method that requires revision as information rather than failure.
Ultimately, I want mentees to leave able to communicate across disciplines, take ownership of their intellectual contributions, and recognize how their own ways of seeing shape the knowledge they produce.
Additional Information
This project is a pilot for a larger digital historiography of African performance and is especially suited to students interested in the intersections of performance, language, culture, and technology. Work will be paced within the five-hour weekly commitment, with regular meetings and structured guidance in performance analysis, qualitative coding, and ethical digital research.Students are not expected to enter with every skill. A student with experience in natural language processing or computational linguistics may contribute to corpus mapping, while a student from the humanities may take greater ownership of contextual research and close analysis. These forms of knowledge will be brought into conversation throughout the project.
Findings will be presented at the FSU Undergraduate Research Symposium and may contribute to a future conference paper, scholarly article, or expanded digital project. Student contributions will be appropriately credited, with possible co-authorship determined by the nature and extent of each student’s intellectual contribution.
Link to Publications
Development of High Magnetic Field Compatible Ultra-low Temperature Thermometers
Low Temperature, Physics, Cryogenics, Programming
Research Mentor: Andrew Woods,
Department, College, Affiliation: Maglab, N/A
Contact Email: awoods@magnet.fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Maglab, N/A
Contact Email: awoods@magnet.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: Physics, Engineering, Computer Science
Project Location: Maglab, 1800 E Paul Dirac Dr, Tallahassee
Research Assistant Transportation Required: Tallahassee city buses service the lab. Remote or In-person: Partially Remote
Approximate Weekly Hours: 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: Physics, Engineering, Computer Science
Project Location: Maglab, 1800 E Paul Dirac Dr, Tallahassee
Research Assistant Transportation Required: Tallahassee city buses service the lab. Remote or In-person: Partially Remote
Approximate Weekly Hours: 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: 2:00
End Time: 4:00
Zoom Link: https://fsu.zoom.us/j/9345851986
Project Description
With the increased focus on quantum computing, which often needs a combination of low temperature and high magnetic fields, there is increased need for robust thermometry in this challenging regime. I aim to develop fast thermometers based on quartz tuning forks that are compatible with temperatures down to 10 mK and fields in excess of 40 T. The technique has been validated experimentally, and therefore this project would focus on improving implementation, including designing and prototyping new enclosures and electrical circuits, designing and verifying measurement software, and working with partners in industry and academia to deploy prototypes and publish initial results.Research Tasks: Data Collection, Data Analysis, Hands on construction, CAD design and 3D printing, Software Development and testing, Scientific Writing, Collaboration with Industry.
Skills that research assistant(s) may need: Python Programming Experience (Recommended)
AI Prompt Development (Recommended)
Hobby electronics experience (soldering etc.) (Recommended)
Hobby 3D Design and Printing (Recommended)
Not all are required by a single candidate.
Mentoring Philosophy
An undergraduate student who joins my group owns a real piece of the research that is a calibration, a sensor mount, a data analysis pipeline, something small enough to finish in two semesters, but with an answer nobody knows yet. I choose the specifics of the project only after asking what the student wants from the experience: graduate school, industry, medical school, or just to find out.Ownership creates accountability, and accountability is where durable skill forms: reproducible analysis and version control, a notebook someone else could follow, an uncertainty estimate before a number is trusted. I value this because it skills like that will be valuable throughout a career in virtually any field. Most of these students will not end up as cryogenic physicists; I would rather they leave with habits that serve them wherever they go.
Early attempts rarely work, and I say so at the start. A week lost to a sign error teaches something I could not have taught, so I treat it as part of the work rather than a setback. My part is to answer questions with questions where that helps, with direct experience where it does not, and to be candid about my own false starts.
Additional Information
Link to Publications
Google Scholar Publication Library: https://scholar.google.com/citations?user=3Ni9uFYAAAAJ&hl=enPreconditioned Machine Learning Algorithm for Variational Problems in Scientific Computing
Partial Differential Equations; Variational Problem; Deep Learning; Neural Networks; Optimization; Python
Research Mentor: Mr. Shu Liu, He/Him
Department, College, Affiliation: Department of Mathematics (Applied & Computational Mathematics), Arts and Sciences
Contact Email: sl25bn@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Department of Mathematics (Applied & Computational Mathematics), Arts and Sciences
Contact Email: sl25bn@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: Mathematics, Applied & Computational Mathematics, Computer Science, Statistics, Physics, or any STEM major with an interest in programming.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: 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:
Not participating in the roundtable
Number of Research Assistants: 1
Relevant Majors: Mathematics, Applied & Computational Mathematics, Computer Science, Statistics, Physics, or any STEM major with an interest in programming.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: 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:
Not participating in the roundtable
Project Description
Many important problems in science, engineering, and finance can be formulated as variational problems involving partial differential equations (PDEs)—that is, finding functions that minimize an energy or objective functional. Variational problems arise widely in materials science, quantum mechanics, optimal control, fluid dynamics, and engineering. When these problems involve many variables, classical numerical methods can become prohibitively expensive due to the “curse of dimensionality.” A promising alternative is to represent the unknown function using neural network surrogation and solve the variational problem by optimizing neural network parameters. This project develops effective preconditioned optimization methods that make neural-network approaches more accurate, efficient, and reliable for high-dimensional PDE variational problems. The key idea is to design optimization algorithms that exploit the geometry of the underlying variational objective, resulting in a better-conditioned loss landscape and more stable training.The UROP research assistant will contribute primarily on the computational side: learning the basics of variational formulations of PDEs and neural-network solvers, implementing and running benchmark experiments, visualizing and comparing different optimization strategies on test problems of varying dimensions. No prior research experience is required.
Research Tasks: All the tasks can be done remotely if the student has access to a computer. The tasks that a student can make vary depending on the background and interest of the student. The main goals include:
1. Guided literature review: read accessible introductions to deep-learning-based PDE solvers and know how these solvers work.
2. Develop preconditioned optimization algorithm that enhance the performance of the deep variational problem solvers.
3. Implement Python codes and test benchmark experiments on target equations. Make comprehensive comparison with existing approaches in solvers’ accuracy, computing time and memory consumption.
Skills that research assistant(s) may need: Required:
1. Calculus I–III and basic mathematical reasoning.
2. Some programming experience in any language, and willingness to learn Python.
3. Curiosity, reliability, and willingness to commit 5-7 hours per week.
Recommended (not required)
1. Linear algebra; Exposure to differential equations.
2. Python with NumPy/Matplotlib; any exposure to PyTorch or machine learning.
Mentoring Philosophy
My goal is for the student to experience the full arc of computational research — from reading and understanding a method, to implementing and testing it, to communicating the results. The first semester is deliberately scaffolded: the student begins with a curated reading list and hands-on Python/PyTorch tutorials, then reproduces one small benchmark experiment end-to-end. In the spring, the student takes ownership of a well-defined mini-project whose results feed directly into the group's ongoing research.I will meet with the student biweekly for progress discussions. During these meetings, the student is expected to present progress in the project, discuss any encountered difficulties, and establish objectives for the upcoming weeks. Between meetings we communicate over emails. The student will have access to the group's GPU computing resources, and strong contributions may lead to co-authorship on a publication or to a subsequent honors thesis. Above all, I aim to create an environment where questions are encouraged, mistakes are treated as part of learning, and the student finishes the year with concrete skills in scientific machine learning.
Additional Information
Link to Publications
https://lslsliushu.github.io/publications/Generative AI-Powered Virtual Reality Museum for Interactive STEM Learning
Generative AI, Virtual Reality, Artificial Intelligence, 3D Modeling, Human-Computer Interaction, Unity, Unreal Engine, Extended Reality (XR)
Research Mentor: Dr. Migara Dr. Migara Amarasinghe,
Department, College, Affiliation: Department of Electrical and Computer Engineering, FAMU-FSU College of Engineering
Contact Email: migaraa@eng.famu.fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators: Dr. Bernadin Dr. Shonda Bernadin
Faculty Collaborators Email: bernadin@eng.famu.fsu.edu
Department, College, Affiliation: Department of Electrical and Computer Engineering, FAMU-FSU College of Engineering
Contact Email: migaraa@eng.famu.fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators: Dr. Bernadin Dr. Shonda Bernadin
Faculty Collaborators Email: bernadin@eng.famu.fsu.edu
Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Computer Engineering, Electrical Engineering, Computer Science, Information Technology, or related STEM disciplines. Students from other majors with an interest in VR, AI, 3D modeling, Graphic Design or immersive learning are also encouraged to apply.
Project Location: FAMU-FSU College of Engineering
Research Assistant Transportation Required: Yes Remote or In-person: Partially Remote
Approximate Weekly Hours: 10 hours, 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: 2
Relevant Majors: Computer Engineering, Electrical Engineering, Computer Science, Information Technology, or related STEM disciplines. Students from other majors with an interest in VR, AI, 3D modeling, Graphic Design or immersive learning are also encouraged to apply.
Project Location: FAMU-FSU College of Engineering
Research Assistant Transportation Required: Yes Remote or In-person: Partially Remote
Approximate Weekly Hours: 10 hours, 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
This project investigates the use of generative artificial intelligence (GenAI) and virtual reality (VR) to create interactive and immersive environments for STEM education. Building upon an existing VR AI Museum developed using Unity/Unreal Engine and Meta Quest, the research will explore new approaches for presenting AI concepts through interactive virtual exhibits, AI-generated content, and intelligent virtual experiences.Undergraduate researchers will contribute to the design, implementation, and evaluation of new museum experiences. Potential research directions include integrating generative AI into virtual exhibits, developing interactive AI-guided experiences, designing educational VR activities, and evaluating how users interact with and learn from AI-enhanced immersive environments.
The project will provide students with hands-on experience at the intersection of artificial intelligence, virtual reality, human-computer interaction, and STEM education. Research outcomes may contribute to demonstrations, undergraduate research presentations, and future scholarly publications.
Research Tasks: Conduct literature reviews on generative AI, virtual reality, human-computer interaction, and immersive STEM education.
Develop and modify interactive VR environments and exhibits using Unity/Unreal Engine.
Explore methods for integrating generative AI and intelligent virtual agents into the VR museum.
Design interactive educational activities and AI-focused museum experiences.
Develop or integrate 3D assets, user interfaces, and VR interactions.
Conduct experiments and usability studies to evaluate user interaction, engagement, and learning.
Collect, organize, and analyze experimental data.
Document research findings and contribute to research posters, demonstrations, technical reports, and potential publications.
Skills that research assistant(s) may need: Required:
Interest in artificial intelligence, virtual reality, or immersive technologies.
Willingness to learn new software and research methods.
Ability to work independently and collaboratively.
Recommended but not required:
Programming experience in C#, C++, Python, or a similar language.
Experience with Unity or another game engine.
Familiarity with generative AI or machine learning.
Experience with Blender, 3D modeling, or digital content creation.
Experience with Meta Quest or other VR/XR platforms.
Prior VR or AI research experience is not required. Students who are motivated to learn these technologies are encouraged to apply.
Mentoring Philosophy
My mentoring approach focuses on hands-on learning, independence, and continuous growth. I believe undergraduate researchers learn best when they understand the larger purpose of a project while also taking ownership of a clearly defined part of the research.I work with students to identify their interests and strengths and connect them with meaningful research tasks. Students will receive guidance and technical support while being encouraged to experiment, ask questions, propose their own ideas, and learn from challenges and unsuccessful attempts.
I also emphasize regular communication and achievable milestones so that students can see their progress throughout the project. As students gain experience, I gradually encourage greater independence and responsibility. My goal is for each student to leave the project with stronger technical and research skills, experience communicating research results, and confidence in their ability to contribute to future research projects.
Additional Information
Link to Publications
https://drive.google.com/file/d/19XSFkt3ypj2eCBKvtQuDdkljqWhxCb9J/view?usp=sharingMFA Thesis: Memory, Material, and the Changing Body
Ceramics, Sculpture, Memory, Disability, Materiality, Feminism
Research Mentor: lc25h@fsu.edu Libby Couch, she/her
Department, College, Affiliation: Fine Art, Fine Arts
Contact Email: lc25h@fsu.edu
Research Assistant Supervisor (if different from mentor): she/her
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Department, College, Affiliation: Fine Art, Fine Arts
Contact Email: lc25h@fsu.edu
Research Assistant Supervisor (if different from mentor): she/her
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:
Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Fine Arts preferred, but open to all majors. Ceramic experience preferred
Project Location: On FSU Main Campus
Research Assistant Transportation Required: There are buses from the main campus to the Carnaghi Art Building Remote or In-person: In-person
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: 2
Relevant Majors: Fine Arts preferred, but open to all majors. Ceramic experience preferred
Project Location: On FSU Main Campus
Research Assistant Transportation Required: There are buses from the main campus to the Carnaghi Art Building Remote or In-person: In-person
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: Friday, September 4
Start Time: 7:00
End Time: 8:00
Zoom Link: Reschedule - Day: Wednesday, September 2
Start Time: 7:00
End Time: 7:30
Zoom Link: https://us06web.zoom.us/j/85417426635?pwd=E7WIIzmvwaooBxVRUwvdNga7UyHDYb.1 - Day: Wednesday, September 2
Start Time: 7:30
End Time: 8:00
Zoom Link: https://us06web.zoom.us/j/85417426635?pwd=E7WIIzmvwaooBxVRUwvdNga7UyHDYb.1 - Day: Wednesday, September 2
Start Time: 5:30
End Time: 6:00
Zoom Link: https://us06web.zoom.us/j/85417426635?pwd=E7WIIzmvwaooBxVRUwvdNga7UyHDYb.1
Project Description
This project is part of my ongoing MFA thesis research in Studio Art at Florida State University. The project investigates the relationship between embodied experience, memory, and the ways bodies are understood, perceived, and remembered. Drawing from research on mood-congruent memory and feminist approaches to embodiment, I will explore how the conditions of the present body influence what can be remembered and how bodily experiences are shaped by cultural expectations and perceptions of the body. Through ceramic reflecting pools, cast forms, glaze experimentation, printmaking, and decals, I investigate how material processes can evoke the instability, distortion, and incomplete accessibility of memory. I am also using 3D scanning to capture faces and ecological formations and translating these scans into clay forms, exploring how digital representations of bodies and landscapes can become physical objects. An undergraduate research assistant will contribute to scholarly and artist research, systematic material testing, documentation, and the development of an organized research archive.Research Tasks: Test ceramic materials and glazes (This involves learning to apply glaze to ceramic pieces and firing them in a kiln.)
Assist with art studio fabrication, installation, and documentation
Research medical journals and scholarly publications pertaining to thesis research
Skills that research assistant(s) may need: Required:
Strong attention to detail and organization
Willingness to conduct research and read academic or artist-written sources
Ability to document and organize research findings
Recommended:
Interest or experience in studio art, ceramics, sculpture, photography, art history, psychology, disability studies, or related fields
Chemistry or geography background may help with glaze testing, but is not required.
Experience with academic research and summarizing sources
Mentoring Philosophy
I approach mentoring as a collaborative process built on curiosity, communication, and mutual respect. My goal is for the research assistant to develop an understanding of what studio-based research can look like while also identifying their own interests and strengths within the project.I previously taught high school ceramics for three years, and my background in education has taught me the importance of meeting students where they are, providing appropriate support, and gradually encouraging greater independence. I want the research assistant to feel comfortable asking questions, proposing ideas, and taking intellectual and creative risks as they develop their research skills.
I believe that experimentation, revision, and failure are essential parts of both creative research and a growth-oriented learning process. In the studio, an unsuccessful material test can be just as informative as a successful one because it provides evidence about what does not work and can lead to new questions, approaches, and discoveries. I want to create an environment where students understand that mistakes are not evidence of failure as a researcher or artist, but opportunities to evaluate, adapt, and continue learning.
I want the student to leave the experience with more than knowledge of ceramics or contemporary art. I want them to understand how artists use research, experimentation, observation, and reflection to develop ideas, and to feel confident applying those methods to their own academic and creative work.