UROP Project

Trusting the Machine? Uncertainty Avoidance and Consumer Perceptions of AI in Marketing Communication

Uncvertanty Avoidace, Risk, Consumers, Technology

Research Mentor: Sindy Chapa, She
Department, College, Affiliation: Center for Hispanic Marketing Communication, Communication and Information
Contact Email: schapa@fsu.edu
Research Assistant Supervisor (if different from mentor): Sofia Otto She
Research Assistant Supervisor Email: smo20bb@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: 4-10, 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 purpose of this study is to examine the role of uncertainty avoidance in shaping consumer acceptance of artificial intelligence in marketing communication across Latin America and the United States. The study will also evaluate the reliability and validity of a scale designed to measure uncertainty avoidance across cultures. By understanding how cultural values influence trust and attitudes toward AI, the research will contribute to both cross-cultural theory development and marketing practice

Research Tasks: Conduct literature reviews on uncertainty avoidance, culture, artificial intelligence, and marketing communication.
Search for, read, and summarize academic journal articles and industry reports.
Assist in evaluating and refining a scale designed to measure uncertainty avoidance across cultures.
Help develop survey questionnaires and research materials.
Recruit study participants and assist with survey distribution.
Organize, clean, and enter research data.
Assist with basic statistical analysis and interpretation of results.
Help prepare tables, figures, presentations, and research reports.
Attend regular one-on-one meetings with the faculty mentor to discuss progress and research findings.
Participate in research discussions and contribute ideas and questions.

Skills that research assistant(s) may need: Curiosity and enthusiasm for learning
Interest in culture, consumer behavior, marketing, communication, or artificial intelligence
Strong reading and writing skills
Ability to summarize academic articles and reports
Attention to detail and accuracy
Good organizational and time-management skills
Ability to work independently and meet deadlines
Basic computer skills, including Microsoft Word, Excel, and PowerPoint
Willingness to participate in discussions and share ideas
Strong interpersonal and communication skills
Commitment to learning research methods and data analysis

Development of STEM outreach and exhibits at the Challenger Learning Center

High Voltage, Electrical Engineering, Zero Emission Aviation, STEM Outreach

Research Mentor: cheetham@eng.famu.fsu.edu Peter Cheetham, Dr.
Department, College, Affiliation: Electrical Engineering, FAMU-FSU College of Engineering
Contact Email: cheetham@eng.famu.fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators: Alan Hanstein
Faculty Collaborators Email: ahanstein@challengertlh.com

Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Open to all majors
Project Location: 2000 Levy Ave Tallahassee Florida (Center for Advanced Power Systems), and 200 S Duval St, Tallahassee, FL 32301 (Challenger Learning Center)
Research Assistant Transportation Required: City of Tallahassee buses and FSU bus
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:
Not participating in the roundtable

Project Description

I run the high voltage lab at Florida State University's Center for Advanced Power Systems (FSU-CAPS) and have a background in electrical engineering, cryogenics, and superconducting power systems. For this year I would like to utilize the UROP students to assist in developing exhibits and STEM outreach teaching sessions to be hosted at the Challenger Learning Center. Projects we have started to develop in include a hand crank slot car track to mimic an electric aircraft "taking off" and programming tesla coils to "sing" a song. Students will help to develop content for the classes and will also assist in demonstrating concepts as part of the teaching sessions. There is also the opportunity to assist in research ongoing at (FSU-CAPS) where I can teach you how to blow stuff up with high voltage electricity.

Research Tasks: Develop stem outreach experiments, develop course content for STEM outreach teaching sessions, complete hands-on research at FSU-CAPS

Skills that research assistant(s) may need: * Punctuality
* Intellectual Curiosity

Density-dependent pollination in a synchronously flowering, fire-stimulated herb, Pityopsis graminifolia (Asteraceae)

fire ecology, pollinators, fieldwork

Research Mentor: Fatima Alcantara,
Department, College, Affiliation: Biological Science , Arts and Sciences
Contact Email: falcantara@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Maybe one more
Number of Research Assistants: 2
Relevant Majors: Open to all majors, preference for Biology Majors
Project Location: Apalachicola National Forest
Research Assistant Transportation Required: I can drive
Remote or In-person: In-person
Approximate Weekly Hours: 8-10 hours, During business hours
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

Fire is a global phenomenon, found in almost every ecosystem, and is thought to drive ecosystem biodiversity, community composition, as well as population dynamics of plants and animals. Fire may have important effects of plant reproduction, as well as pollinator populations and behavior. Climate change and urbanization threaten fire regimes, as well as plant and pollinator populations. Thus, it is important for researchers and land managers alike to learn how fire affects pollinator communities as well as plant reproduction.

In fire-stimulated systems there are some plant species that show dramatic increases in flowering immediately after a fire. This synchronous post-fire flowering is thought to be in part caused by favorable post-fire conditions like a release from competition and a pulse of soil nutrients. However, less attention has been paid to the density-dependent, animal-mediate fitness benefits of high flower densities after fire, like pollination efficiency. Pollination efficiency is the increase of outcrossing at high flower densities due to increased apparency, constancy, or pollinator movement. Most studies conflate burn treatment with flower density, since burned areas have naturally higher flower densities compared to unburned areas. In this study, I plan to manipulate flower density in burned and unburned areas to see the effect of the interaction of density and fire on plant reproduction.

In this project, I aim to answer these questions:
1. How does burn status affect pollination success (quantity and quality of outcrossed pollen transfer) across a flower density gradient?
2. How does burn status affect the abundance and diversity of pollinators across a flower density gradient?


Research Tasks: Some activities a mentee on this project can expect would include: working outdoors in sandhill forests in relatively pleasant weather; walking a few miles per day to and within field sites; squatting and bending repeatedly while collecting data; using a butterfly net to capture insects; handling and identifying live and dead insects; accurately recording field observations; driving to field sites in either my car or yours, counting seeds and flowers in the lab or field, inputting data into excel worksheets, analyzing preliminary data, presenting a poster or presentation.



Skills that research assistant(s) may need: Required: walk several miles a day, carry 20 lbs, ability to work in heat or cold. Recommended: curious, detail oriented, able to do monotonous work.

Integrated Zero-Emission Aviation (IZEA)

IZEA

Research Mentor: Christopher Akporoghene,
Department, College, Affiliation: Florida state University, FAMU-FSU College of Engineering
Contact Email: coa24a@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, Mechanical Engineering, and Computer Engineering.
Project Location: 2525 Pottsdamer St., Tallahassee, FL 32310-6046
Research Assistant Transportation Required: Yes
Remote or In-person: In-person
Approximate Weekly Hours: 5, During business hours
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

My role in the IZEA project focuses on the design, experimental validation, and performance characterization of cryogenic power-distribution systems for electrified aircraft. I develop experimental configurations for busbars and high-temperature superconducting (HTS) cables, including the associated instrumentation, data-acquisition systems, and automated test procedures required for high-current evaluation. I also analyze the resulting electrical and thermal data to identify performance limitations and assess if the power-distribution architecture can satisfy aircraft requirements for power density, efficiency, and thermal management.

Research Tasks: Researchers can support the project by conducting literature reviews, collecting and organizing data, and performing preliminary analysis. They can also assist with preparing test equipment, documenting experimental procedures, maintaining research logs, organizing references, and creating simple plots or tables from completed experiments. As they gain experience, they can help with basic SolidWorks drawings, sensor configurations, spreadsheet calculations, and preparation of figures or summaries for presentations and weekly reports.

Skills that research assistant(s) may need: Required skills include a willingness to learn, follow safety procedures, take good notes, have research experience, and work well with others. Basic experience with hand tools, measurements, SolidWorks, mechanical assembly, or laboratory work is recommended but not required. Students should have an interest in hands-on engineering and be comfortable learning new equipment and experimental procedures.

Evaluating Earth Observation Foundation Models Across Urban Environments

satellite remote sensing, GeoAI, urban environments, GIS

Research Mentor: Mr. Kazi Jihadur Rashid, He/him
Department, College, Affiliation: Geography, Social Sciences and Public Policy
Contact Email: kr24x@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: Geography
Project Location: On FSU Main Campus
Research Assistant Transportation Required: No, the project is remote
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-8, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:
Not participating in the roundtable

Project Description

Earth observation satellites provide extensive information about Earth's surface. Recent artificial intelligence models can learn complex representations from these observations. However, evaluating what these models learn requires carefully selected and reliable reference data. This project investigates how emerging Earth observation foundation models represent different urban and natural environments. The research uses satellite image samples representing different types of built and natural surfaces. A major component involves identifying high-quality samples suitable for subsequent computational analysis.
Undergraduate researchers will help evaluate candidate satellite image patches from an existing labeled dataset. Students will examine whether individual samples adequately represent their assigned surface classes. They will identify mixed or unsuitable samples using established selection criteria. This process will produce a curated dataset for subsequent geospatial and artificial-intelligence analyses. Students will gain practical experience interpreting satellite imagery and working with geospatial datasets. They will also learn about urban land-surface classification and research data quality. The project provides exposure to emerging applications of artificial intelligence in Earth observation.

Research Tasks: • Reviewing literature on urban land-surface classification and Earth observation.
• Learning the Local Climate Zone classification framework.
• Evaluating the quality and representativeness of candidate samples using a standardized protocol.

Skills that research assistant(s) may need: Required:
• Interest in remote sensing, geography, urban environments, or GeoAI.
• Strong attention to visual and spatial details.
• Ability to follow consistent data-quality procedures.
• Willingness to learn new geospatial tools and concepts.
• Ability to work independently after receiving guidance.
• Effective communication when questions or problems arise.
Recommended but not required:
• Introductory experience with GIS or remote sensing.
• Familiarity with satellite imagery or aerial photographs.
• Experience with ArcGIS Pro, QGIS, or similar GIS software.

Mapping and Improving the CAPS Project Lifecycle

Process Improvement, Systems Engineering, Project Management, Knowledge Management, Research Operations

Research Mentor: Mr. Matthew Bosworth,
Department, College, Affiliation: Center for Advanced Power Systems, N/A
Contact Email: matt@caps.fsu.edu
Research Assistant Supervisor (if different from mentor): Mr. Naqash Ali
Research Assistant Supervisor Email: na22j@fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 1
Relevant Majors: Open to all majors, particularly students interested in engineering, project management, business processes, information systems, technical communication, or organizational improvement.
Project Location: On FSU Main Campus
Research Assistant Transportation Required: Yes
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:
Not participating in the roundtable

Project Description

This project examines how research and testing work moves through the Center for Advanced Power Systems (CAPS), from an initial stakeholder request through project planning, technical execution, and delivery of results. The student will study how CAPS defines the scope of work, develops budgets and statements of work, matches projects with faculty expertise and laboratory capabilities, assigns responsibilities, and transfers information between administrative and technical personnel.
The project will also examine common steps used to perform and document technical work at CAPS, including modeling and simulation, hardware-in-the-loop testing, verification and validation activities, data management, and technical reporting. Using selected projects as examples, the student will create maps of the current process, identify unclear responsibilities, missing information, repeated work, and difficult handoffs, and recommend practical improvements. Potential outputs include improved process maps, responsibility matrices, intake checklists, decision guides, and standard handoff or reporting templates.


Research Tasks: • Learn about CAPS laboratories, technical capabilities, personnel, and common project types.
• Review existing project documents such as stakeholder requests, budgets, statements of work, test plans, data records, and reports.
• Work with the research team to select representative projects for study.
• Conduct structured discussions with faculty, engineers, laboratory staff, project managers, and administrative personnel.
• Map how a project moves from the initial request through planning, execution, reporting, and closeout.
• Document the people involved, their responsibilities, major decisions, required information, and handoffs between groups.
• Examine how modeling and simulation, hardware-in-the-loop testing, verification and validation, data analysis, and reporting fit within the larger project process.
• Identify delays, repeated work, unclear responsibilities, communication gaps, and places where project knowledge may be lost.
• Compare current CAPS practices with methods from systems engineering, project management, and process improvement.
• Develop practical recommendations and help test selected improvements.
• Create process diagrams, summary tables, presentation materials, and sections of the final report.


Skills that research assistant(s) may need: Required
• Interest in how technical projects are planned, managed, and completed.
• Good organization and attention to detail.
• Clear written and verbal communication.
• Ability to listen, ask questions, and summarize how people perform their work.
• Basic experience with Word, Excel, and PowerPoint or similar software.
• Ability to handle project information carefully and follow confidentiality requirements.
• Willingness to learn process mapping, systems engineering, and research methods.
• Ability to work independently and reliably with a research team.
Recommended, but not required
• Coursework or interest in engineering, business, project management, information technology, communication, or operations.
• Experience creating flowcharts or diagrams using Visio, Lucidchart, PowerPoint, or similar tools.
• Familiarity with research laboratories, technical projects, data organization, or process improvement.
• Experience using spreadsheets to organize and compare information.
No previous experience with CAPS processes or process-improvement methods is required; training and guidance will be provided.

Detecting Meal and Exercise Events from Continuous Glucose and Wearable Sensor Data

Type 1 diabetes; continuous glucose monitoring; wearable sensors; machine learning

Research Mentor: Prabin Timilsina,
Department, College, Affiliation: Department of Mechanical & Aerospace Engineering, FAMU-FSU College of Engineering
Contact Email: pt23@fsu.edu
Research Assistant Supervisor (if different from mentor): Dr. Taylor Higgins
Research Assistant Supervisor Email: th22u@fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 1
Relevant Majors: Students from all majors with an interest in programming, data analysis, or digital health are also encouraged to apply.
Project Location: 2525 Pottsdamer Street, Tallahassee, FL 32310-6046 (FAMU-FSU College of Engineering)
Research Assistant Transportation Required: There are bus routes serving the College of Engineering (Innovation Route).
Remote or In-person: Partially Remote
Approximate Weekly Hours: 6-8 hours per week, Flexible schedule (Combination of business and outside of business. TBD between student and research mentor.)
Roundtable Times and Zoom Link:

• Day: Friday, September 4
  Start Time: 12:00
  End Time: 3:00
  Zoom Link: https://fsu.zoom.us/j/95303725357

Project Description

People with type 1 diabetes rely on continuous glucose monitors and insulin pumps to help maintain blood glucose within a safe range. However, everyday events such as meals and exercise can cause rapid changes in glucose levels, and these events are not always recorded or announced on time. Automatically recognizing when a meal or exercise event is likely occurring could reduce missed or delayed event announcements and ultimately support more personalized diabetes management.

In this project, we will investigate whether meal and exercise events can be identified using longitudinal diabetes and wearable-sensor data. We will begin with publicly available and/or simulated datasets containing signals such as continuous glucose measurements, insulin delivery, physical activity, heart rate, and recorded behavioral events. The research assistant will help organize and synchronize these data, visualize patterns surrounding known meal and exercise events, and implement baseline machine-learning approaches for event detection.

Our longer-term goal is to develop two complementary modeling approaches: one that learns an individual's typical patterns of when meals or exercise occur, and another that recognizes short-term physiological and behavioral patterns suggesting that an event may be occurring in real time. We will also investigate whether models personalized to an individual perform better than models trained across multiple individuals. This work will provide a foundation for future personalized, context-aware diabetes technologies.

Research Tasks: • Conduct a literature review on meal detection, exercise detection, and behavioral inference using glucose and wearable-sensor data.
• Help identify and document appropriate publicly available diabetes time-series datasets.
• Organize, clean, and synchronize time-series signals collected at different sampling frequencies.
• Implement and evaluate simple baseline classification models.
• Maintain clear documentation of data-processing and analysis procedures.
• Present findings through a research poster, presentation, and potentially contribute to a scientific manuscript.

Skills that research assistant(s) may need: Recommended: Basic programming experience in Python, MATLAB, or a similar language; familiarity with data analysis, statistics, or machine learning; experience working with spreadsheets or tabular data.

Required: Strong organization skills, willingness to learn independently, attention to detail, and reliable communication. The student should be comfortable troubleshooting problems and documenting their work.

Prior experience with diabetes, biomedical data, wearable sensors, or advanced machine learning is not required.

Music Textbook Projects Research

music, world music, music pedagogy, ethnomusicology

Research Mentor: Dr. Dr. Michael Bakan, he/him
Department, College, Affiliation: Musicology, Music
Contact Email: mbakan@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators: Dr. Dr. Abby Rehard she/her
Faculty Collaborators Email: arehard@fsu.edu

Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Open to all majors, though some knowledge of music is essential.
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:
Not participating in the roundtable

Project Description

I am currently involved in the relatively late-stage research and development phases of two independent textbook projects, both scheduled for copyright year 2028 publication:

1. Music: Context, Sound, and Meaning (1st ed., with Oxford University Press)
2. World Music: Traditions and Transformations (5th ed., with McGraw-Hill)

Both books will be published either exclusively or primarily in digital formats with abundant linked media (Spotify and YouTube playlists, interactive listening guides, online musical illustrations, chapter "Musical Guided Tours, etc.") Also, both are written principally for entry-level undergrad liberal/general studies courses for non-music majors, so are designed to be engaging and accessible for that readership.


Research Tasks: Manuscript and proof pages proofreading and fact checking; testing and development of online links to embedded musical and video examples; testing and development of online interactive activities, test banks, index, and other student and instructor resources.

Skills that research assistant(s) may need: REQUIRED: Strong proofreading skills, English language fluency and good writing/reading skills, detail oriented, and an interest in music, culture, history, and the intersections between them in global perspective.

RECOMMENDED: good basic tech skills working with online platforms like Spotify and YouTube; technical facility and creative vision for developing online learning resources like interactive listening and video viewing guides and lecture PowerPoints; photography skills and basic equipment; musical background and training of some kind.

Investigating Virus-Host Cell Interactions During the Nuclear Translocation of HIV-1

Lentivirus, HIV-1, Capsid core, Uncoating, Virus Nuclear Translocation

Research Mentor: Dr. Satya Prakash Singh, Satya
Department, College, Affiliation: Biological Science, Arts and Sciences
Contact Email: ssingh7@fsu.edu
Research Assistant Supervisor (if different from mentor): Dr. Ashwanth Francis Dr. Francis
Research Assistant Supervisor Email: acfrancis@bio.fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 1
Relevant Majors: Biology
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: In-person
Approximate Weekly Hours: 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

HIV-1 belongs to the genus Lentivirus, a group of retroviruses characterized by a prolonged incubation period before disease manifestation in their hosts. Lentiviruses, including HIV-1, simian immunodeficiency virus (SIV), equine infectious anemia virus (EIAV), and feline immunodeficiency virus (FIV), infect a variety of mammalian species, including humans and non-human primates. Following entry into the cytoplasm of a target cell, HIV-1 undergoes reverse transcription to generate a DNA copy of its RNA genome. This viral DNA is subsequently transported into the nucleus, where it integrates into the host genome, establishing a stable and productive infection.
Although numerous viral and host factors involved in HIV-1 infection have been identified, many aspects of the molecular mechanisms governing viral replication and nuclear translocation remain poorly understood. In the Kasha Laboratory, we employ a range of molecular and cellular biology approaches to investigate the mechanisms of HIV-1 infection. Our research utilizes fluorophore-labeled chimeric viruses to visualize the uncoating process and nuclear translocation of individual viral particles in living cells using advanced fluorescence microscopy techniques. By examining viral trafficking and replication dynamics at different time points and subcellular locations, particularly in the absence of key host factors or in the presence of antiviral compounds, we gain valuable insights into the cellular pathways that regulate HIV-1 infection. These studies contribute to a deeper understanding of virus-host interactions and may reveal novel therapeutic targets for antiviral intervention.

Research Tasks: Mammalian cell culture
Fluorescence and live-cell microscopy
Molecular cloning
Reverse transcription PCR (RT-PCR)
Agarose gel electrophoresis
SDS-PAGE
Western blotting

Skills that research assistant(s) may need: Interest in learning molecular biology techniques and about viruses
Team work, participate in various lab activities
Knowledge to use MS Word and Power Point

Vision-Language-Action Models for Robotic Assembly in Modular Construction

Modular Construction; Robotics; Vision-Language-Action Models

Research Mentor: Roshan Panahi, Dr.
Department, College, Affiliation: Civil and Environmental Engineering, FAMU-FSU College of Engineering
Contact Email: rpanahi@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: Computer Science; Electrical Engineering; Mechanical Engineering
Project Location: Walter Smith Architecture Building, 1938 S. Martin Luther King Jr. Blvd., Tallahassee, FL 32307-4200
Research Assistant Transportation Required: Yes
Remote or In-person: In-person
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: 2:30
  Zoom Link: https://fsu.zoom.us/j/99225339098
• Day: Tuesday, September 1
  Start Time: 1:00
  End Time: 1:30
  Zoom Link: https://fsu.zoom.us/j/93987059441

Project Description

What if you could order a home customized to your preferences and have it manufactured and delivered to your site? This is the vision behind mass customization in modular construction. Modular construction is a construction method in which building components or modules are manufactured in a controlled factory environment and then transported to the project site for installation. Although this approach offers significant benefits in productivity, quality, and construction speed, producing highly customized homes in a factory remains challenging. Changes in design may require adjustments to production processes, tooling, workflows, and worker tasks. The workforce must also quickly understand and adapt to new designs, which can reduce productivity and increase the risk of errors. Robotics can help address some of these challenges by assisting workers with repetitive, labor-intensive, or frequently changing construction tasks. However, conventional industrial robots typically require task-specific programming, making frequent reprogramming for customized production costly and time-consuming. Recent advances in vision-language models (VLMs) and vision-language-action (VLA) models provide new opportunities for more flexible robotic systems. These models can enable robots to interpret visual information, understand natural-language instructions, and translate those instructions into actions. Therefore, this research aims to investigate the use of VLMs and VLA models to enable a robotic arm to perform construction-related pick-and-place and assembly tasks with minimal task-specific programming.

Research Tasks: (a) Use ChatGPT, Claude, or a similar AI tool to: (1) generate code that instructs the robotic arm to pick up an object and place it at a specified location; (2) generate Python-based computer vision code to detect a piece of lumber in a video; and (3) detect the center point of the lumber and control the robotic arm to pick up the object using the detected coordinates.
(b) Learn about vision-language-action (VLA) models through online videos and other educational resources.
(c) Test the developed models in the lab using the robotic arm and provided software, and assist with data annotation, writing, and presentations as needed.

Skills that research assistant(s) may need: Familiarity with Python programming. Prior experience with robotics projects is highly encouraged. Strong interest in robotics and artificial intelligence (AI). Self-motivated, disciplined, and willing to learn independently. Ability to attend in-person lab sessions for approximately 5–10 hours per week.