UROP Project

Candidate Characteristics; Electoral Performance; Voting Behavior; Information Cues

Research Mentor: Dr. Yimeng Li, he/him
Department, College, Affiliation: Political Science, Social Sciences and Public Policy
Contact Email: yimeng.li@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators: Mr. Austin Cutler
Faculty Collaborators Email: acutler@fsu.edu

Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Open to all majors, but prefer Political Science majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

In this project, we seek to analyze the association between candidate characteristics and electoral performance in primary and general elections. Candidate characteristics such as age, gender, and race provide important information cues in addition to their party affiliation and policy positions in voter’s choice, especially in low information contests.

In this project, we first expand national and state databases on candidate information and election results at low aggregation. This step involves scraping data from state and county websites and searching newspaper databases. We then use computer programs to clean the data and build databases for subsequent analyses.

In the second part of the project, we conduct statistical analyses to determine the association between candidate characteristics and electoral performance in low and high-information environments. This step involves both simple regression analysis and advanced ecological inferences. We finally compare the results with experimental evidence in the literature.

Research Tasks: (Data Collection) Research assistants will expand national and state databases on candidate information and election results at low aggregation. This step involves scraping data from state and county websites to obtain electoral performance data. It also requires extracting from candidate bios and searching newspaper databases to obtain information on candidate characteristics.

(Data Analysis) Research assistants will conduct statistical analyses to determine the association between candidate characteristics and electoral performance. Research assistants will learn to use R to generate simple summary statistics, conduct data visualization, and run regression analyses.

Skills that research assistant(s) may need: Proficiency with Microsoft Excel. Attention to detail is critical to this project.
Preferences will be given to political science sophomores who have completed or are taking POS 1041 American National Government. Preferences will be given to students with strong academic records, evidenced in their CVs and transcripts.

Machine Learning, Internet of Things, Optimization, Tiny ML

Research Mentor: Dr. Marcos Muller Vasconcelos, He/Him/His
Department, College, Affiliation: Electrical and Computer Engineering, FAMU-FSU College of Engineering
Contact Email: m.vasconcelos@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: Electrical Engineering
Computer Engineering
Computer Science
Mathematics
Statistics
Project Location: FAMU-FSU College of Engineering
Research Assistant Transportation Required: Yes
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5-10 hours a week,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

The Internet of Things (IoT) -- a complex ecosystem that interconnects smartphones, tablets, machine-type devices, people, and mundane objects into a large-scale network -- has flooded the world with inexpensive devices that collect, store, process and communicate data at unprecedented volumes. Although the cost of sensing and storing data is relatively small, the power required to process and share data is often large and restrictive. Therefore, it is imperative to identify, process, and transmit only the most informative data. The adoption of cleverly designed data selection policies allows concurrent applications to run on limited shared resources, leading in enhanced efficiency and economic gains. In the case of IoT, even modest gains in performance mount quickly due to the massive scale of the system.

The overall goal of this project is to develop a new system architecture for the selection of the most informative data in multi-agent networks based on the novel notion of Maximum Disagreement and its application in distributed machine learning with IoT devices, as well as implementation in a combination of client-server and peer-to-peer networks. The rationale for the work is twofold: First, we will design a new distributed algorithm based on Maximum Disagreement for machine learning that operates in two layers -- a local network and the cloud infrastructure. Secondly, we will implement this new system in a real testbed using TinyML devices under strict communication constraints while ensuring privacy and robustness guarantees. Achieving these objectives could significantly improve performance and convergence speed, particularly in large-scale commercial distributed systems.

Research Tasks: Literature Review
Programming Tiny ML/IoT devices
Computer Simulations
Communication Networks
Data Collection and Analysis


Skills that research assistant(s) may need: Machine Learning
Wireless Communication Networks
Tinkering
Problem-Solving

Identity, contour map, paintings, passport number, print making, migration

Research Mentor: Amarachi K. Odimba, She/Her
Department, College, Affiliation: Studio Arts, Fine Arts
Contact Email: paintergalten@gmail.com
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email: ako23@fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 2
Relevant Majors: -Geography
-Printmaking
-Art History
-Painting


Project Location: On FSU Main Campus
Research Assistant Transportation Required: Yes
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5 hours,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

Contoured Identity
How can we articulate the effects that movement has on our experiences and sense of self?
My work seeks to depict and thus capture the human experience by portraying it as inherently dynamic, exchangeable, and in a constant state of flux.
By exploring the boundaries of abstraction, landscape, printmaking, texts, and figuration, my work delves into our lived experiences, investigating how forces like migration and capitalism shape human identity, sense of self, and other possibilities.
My art-based research comprises eight mixed media works which bring together elements of repetition of texts/numerals, figuration and contour maps of specific regions inspired by colonial and political history—weaving past with present.
The repeated passport numbers and juxtaposed contour maps establish the underpainting, which I employ to respond to themes of longing, belonging and refusal referencing The Black Shoals by Tiffany Lethabo King, which describes that the shoal functions as a spatial allegory for the moving and shifting space of the human. Rather than a place of safety, the intersections, overlap and disintegration is an unstable ecozone and nervous landscape where boundaries between the concept of self and human identity continually shift.
Describing the components of my work;
-The texts: These are mainly imagined passport numbers and currency serial numbers applied as patterns originally conceived from the plaid design of the Ghana-Must-Go tote bag, a bag which gained its name in 1983 following Nigeria’s expulsion of West African migrants, largely Ghanaian citizens, who had entered the country during a period of economic prosperity. Over forty years later, the bag continues to be a powerful symbol of migration worldwide and I employ it as a visual metaphor for migration and capitalism by deconstructing its patterns with text.
- The Imagery: These are drawings and paintings of fellow International students referencing the Balsall Heath photographs in Tina Campt’s Listening to Images, similar to identification photos in function and format that cannot be overseen.
- Contour maps: These maps are layered or juxtaposed to represent the multiple layers of identity shaped by experiences and environmental influences. The contour maps are selected from specific locations where the painted subjects have lived or traversed. They are generated using the QGIS software application.
From a personal and collective perspective, these elements both aesthetically and conceptually embody the politics of landscape and migration, the hierarchy of passports, landscape and currencies all of which shape our collective experience .


Research Tasks: - Data collection and generation of random passport numbers and currency serial numbers
_ Printmaking
- Reaching out to International students who are potentially subjects of paintings
-Using Softwares to generate contour maps

Skills that research assistant(s) may need: - MS Word Office
- QGIS Software application
- Printmaking
-cartography
-drawing
-Literature

-art history
-migration studies
-African history
Indigenous history
African American History
-painting
-photoshop
-writing

Sustainability, Energy measurements, MRI, Magnet lab

Research Mentor: Malathy Elumalai,
Department, College, Affiliation: National high Magnetic Field Laboratory, N/A
Contact Email: me09e@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: No
Number of Research Assistants: 1
Relevant Majors: Open to all majors- Preferred if they have interest in electrical engineering, Sustainability and data analysis.
Project Location: NHMFL, 1800 E Paul Dirac drive, Tallahassee, Florida - 32310
Research Assistant Transportation Required: Innovation hub bus (D)
Remote or In-person: In-person
Approximate Weekly Hours: 8-10hrs./week,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

The National High Magnetic Field Laboratory (NHMFL) allocates 11% of its annual budget to energy and gases and accounts for 10% of Tallahassee's total electricity usage. Following this trend, it is important to estimate the energy consumption of pre-clinical MRI and NMR scanners at NHMFL, which operates 24 NMR/MRI spectrometers, including 8 MRI scanners.

Research Tasks: (1)Work with facilities department to setup power logger for equipment's
(2) Collect energy consumption data of equipment's of individual scanner
(3) Analyze the consumption with overall standards and come up short term and long term solutions to reduce energy consumption.

Skills that research assistant(s) may need: Interest in sustainability (required) , electronics background(required) and data analysis (recommended).

language learning, learning apps, Duolingo

Research Mentor: Mariana Talpau Joos, Mira
Department, College, Affiliation: Educational Psychology and Learning Systems, Education, Health, and Human Sciences
Contact Email: mmt18d@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: No
Number of Research Assistants: 1
Relevant Majors: Education; Modern Languages; Media and technology; Psychology; Instructional Design.
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,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

Title of the study in progress: Students’ perceptions of Duolingo engagement, gains and transfer to the L2 classroom
Mobile technology, specifically app-based learning has been increasingly acknowledged as a reliable learning support specifically in informal out-of-class settings. However, whether and how students bridge app-based and classroom learning remains largely unexplored. Compounding insights from several theoretical and conceptual frameworks (e.g., complexity theory, student engagement, and proactive language learning theory), this study seeks to answer the question of how Duolingo-based out-of-class engagement transfers to the classroom via learners’ proactive behaviors. Building on the existing scholarship on the transfer of learning, I extend the conceptualization of transfer as adaptive, and I seek to explore nature of engagement, gains and transfer to language classroom settings. Recruited participants are college students who use Duolingo weekly and take a college course in the same language and at the same level to satisfy their language requirements. I plan to collect and analyze multiple quantitative and qualitative data sources in three time-points over one semester. First, I conduct non-intrusive classroom observations of the focal participants. Second, the participants complete a brief experience sampling survey during or immediately after each of the three observed L2 classes. Lastly, semi-structured in-depth interviews capture forms of engagement across the app and the classroom setting. Conceptual and methodological complexity theory tools (e.g., time trajectories) and grounded theory (e.g., constant comparative analysis) are used for data analyses. In the way of a hypothesis for this study, I expect to capture the participants’ interpretations of experiences and key behaviors with the Duolingo app and classroom learning regarding their proactive engagement (cognitive, affective, behavioral, agentic).

Research Tasks: Data transcription; data coding; data analysis.

Skills that research assistant(s) may need: Interest and beginning skills in qualitative data.
Interest and awareness of learning apps.
Interest in language learning, applied linguistics, psychology of language learners.

Excavator, buck design, optimization, sensor

Research Mentor: Dr Juyeong Choi, Juyeong
Department, College, Affiliation: FAMU-FSU College of Engineering, FAMU-FSU College of Engineering
Contact Email: jchoi@eng.famu.fsu.edu
Research Assistant Supervisor (if different from mentor): Ms. Maral Nazemi Maral
Research Assistant Supervisor Email: mn22a@fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: Yes
Number of Research Assistants: 4
Relevant Majors: Civil Engineering, Mechanical Engineering, Industrial Engineering
Project Location: FLVC (1753 W Paul Dirac Dr, Tallahassee, FL 32310)
Research Assistant Transportation Required: Yes
Remote or In-person: In-person
Approximate Weekly Hours: 6 to 8 hours per week,
Roundtable Times and Zoom Link: 3:30 PM to 4:00 PM on September 4, September 5, and September 6.

https://fsu.zoom.us/j/94170250488

Project Description

Amidst the escalating challenges posed by natural and man-made disasters, one of the most dire situations is the entrapment of individuals under debris from collapsed structures. The urgency to maximize survival rates necessitates swift and efficient rescue operations. To address this, this project aims to evaluate and optimize the design of excavator buckets to enhance their efficiency in rescue scenarios. To be more specific, in simulated rescue operation scenarios, student volunteers will operate small-scale excavators equipped with varying bucket designs in attempts to unearth a 3D printed human figure while measuring both the rescue time and the accumulative pressure given to the figure throughout the operation. Drawing from these findings, the bucket design will be iteratively refined, with the ultimate goal of establishing an excavator bucket design that harmoniously blends speed with the delicate precision required for safe rescue operations. Through this endeavor, the project seeks to bridge the gap between technological advancements and their practical deployment in life-saving activities, potentially revolutionizing post-disaster rescue operations.

Research Tasks: Operating remote control excavators on different rescue activities, collecting, cleaning, processing the data collected from small-scale experiments, printing different bucket designs with 3D printers, and performing a literature review

Skills that research assistant(s) may need: Programming [recommended], 3D design [recommended]

Health Informatics, Data Science, Machine Learning, AI

Research Mentor: Dr. Zhe He,
Department, College, Affiliation: School of Information, Communication and Information
Contact Email: zhe@fsu.edu
Research Assistant Supervisor (if different from mentor): Dr. Balu Bhasuran He, Him, His
Research Assistant Supervisor Email: bb23u@fsu.edu
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: No
Number of Research Assistants: 3
Relevant Majors: Computer Science, Information Technology, Premed, Biology, Biochemistry, Psychology
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: Partially Remote
Approximate Weekly Hours: 5,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

The research in the eHealth Lab directed by Dr. Zhe He is meticulously designed to foster health education, empower patient self-management, enhance the efficiency of healthcare delivery, and elevate the standards of clinical research by leveraging the power of big health data. Employing user-centered and participatory approaches, we are dedicated to developing AI-powered health delivery platforms and tools that are as innovative as they are inclusive. Our machine learning and natural language processing expertise enables us to extract actionable insights from complex healthcare systems, thereby informing medical decision-making and exploring the nuances of clinical trial participation. Research areas include: Our specialized research areas span across Biomedical and Health Informatics, Clinical Research Informatics, Consumer Health Informatics, as well as Knowledge Representation and Biomedical Ontologies. We are also deeply engaged in advancing the fields of Biomedical Natural Language Processing, Machine Learning, and Health Data Analytics with a multidisciplinary approach.

Research Tasks: Assist with on-going biomedical and health informatics projects: (1) literature review; (2) data collection; (3) annotation; (4) preparing manuscripts for academic journals and conferences.

Skills that research assistant(s) may need: Python (recommended)
MS Excel (required)
R (recommended)
MS Word (required)
MS PowerPoint (required)
Interview (required)

plant protein; edible film; food science

Research Mentor: Leqi Cui,
Department, College, Affiliation: Florida State University, Education, Health, and Human Sciences
Contact Email: lcui2@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: No
Number of Research Assistants: 1
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,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

This project will develop natural plant protein-based films for packaging purposes. The use of natural biopolymers (e.g., protein) to replace synthetic plastic packaging will help mitigate the issue of plastic pollution. The selected candidate will learn the basic protein structure-functionality relationships and investigate how processing steps influence the packaging properties of the resulting films.

Research Tasks: conduct experiments; data collection; data analysis

Skills that research assistant(s) may need: Recommended: knowledge of protein structure

food science; spinach; digestion; chemistry

Research Mentor: Leqi Cui,
Department, College, Affiliation: Florida State University, Education, Health, and Human Sciences
Contact Email: lcui2@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: No
Number of Research Assistants: 1
Relevant Majors: STEM majors
Project Location: On FSU Main Campus
Research Assistant Transportation Required:
Remote or In-person: In-person
Approximate Weekly Hours: 8,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

This project will mimic human digestion process using the in vitro digestion protocol. The selected candidate will learn to use Liquid chromatography–mass spectrometry (LC–MS) to study the bioactive compounds in spinach, including identification and their metabolism.

Research Tasks: conduct experiments; data collection; data analysis

Skills that research assistant(s) may need: Recommended: analytical chemistry; HPLC

Economic history, technology, innovation

Research Mentor: William Cockriel, He/His
Department, College, Affiliation: Economics, Social Sciences and Public Policy
Contact Email: william.cockriel@fsu.edu
Research Assistant Supervisor (if different from mentor):
Research Assistant Supervisor Email:
Faculty Collaborators:
Faculty Collaborators Email:

Looking for Research Assistants: No
Number of Research Assistants: 3
Relevant Majors: Open to all majors, economics preferred
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,
Roundtable Times and Zoom Link: Not participating in the Roundtable

Project Description

This is an effort into digitizing historical records that document federal and state expenditure on road building during the early years of automobile adoption. The resulting data could easily be used to create maps and figures documenting how a new government policy in 1916 affected the local building and funding of roads. Data will even be connected to motor vehicle registration data to see the effect of roadbuilding on automobile adoption.

Research Tasks: Data collection: Manual data entry from images
Data analysis: creating graphs and heatmaps (with mentor assistance)

Skills that research assistant(s) may need: Required: Typing, minor working knowledge of computer use (excel)