Category: OSCAR

Plasmonic Metal-Infused Laser-Induced Graphene for Enhanced Photodetection

Author(s): Graham Harper

Mentor(s): Pilgyu Kang, GMU Mechanical Engineering

Abstract

Laser-Induced Graphene (LIG) is a promising platform for next-generation flexible photodetectors due to its high conductivity, scalability, and low-cost fabrication. However, its optical-to-electrical conversion efficiency remains limited by weak light–matter interaction. In this work, we enhance LIG photodetection performance through the in-situ infusion of plasmonic palladium nanoparticles into the polymer precursor prior to laser carbonization. During laser processing, the nanoparticles become embedded within the porous graphene microstructure, enabling localized electromagnetic field enhancement via surface plasmon resonance. Electrical characterization under UV illumination demonstrates improved resistance modulation and consistent ON/OFF cycling behavior in Pd-infused LIG compared to bare LIG samples. These initial results confirm plasmon-assisted photocarrier generation and highlight an effective, single-step approach to improving responsivity in flexible photodetectors. Future efforts will investigate wavelength-dependent response and additional plasmonic materials such as silver and gold nanoparticles.

Audio Transcript

Hello, my name is Graham Harper from the Mechanical Engineering Department at George Mason University. Today, I’ll be presenting my research about Plasmonic Metal-Infused Laser-Induced Graphene for Enhanced Photodetection.

Photodetectors are critical components in environmental and optical sensing systems. However, many conventional photodetectors are expensive to fabricate and lack flexibility.
Laser-Induced Graphene offers a more scalable and low-cost alternative due to its conductive porous structure and ability to be processed on flexible substrates.
The challenge is improving how efficiently it converts light into a measurable electrical signal.

One promising way to improve photodetection is by taking advantage of surface plasmon resonance.
Metal nanoparticles, such as palladium, can enhance local electromagnetic fields when illuminated, generating more charge carriers in the device.
By infusing metal nanoparticles directly into the polymer before laser conversion, the plasmonic functionality becomes embedded within the graphene structure.
Our hypothesis is that metal infused laser-induced graphene will perform better under illumination than bare laser-induced graphene.

Our objective is to fabricate laser induced graphene using a UV or CO₂ laser, characterize its structure and electrical properties, and measure photodetection performance under illumination.
The main goal is to determine whether palladium-embedded laser induced graphene produces enhanced optical-electrical response.

To create Palladium infused laser-induced graphene, a palladium-doped polymer solution is spin-coated for thickness uniformity. A laser induces carbonization to form conductive graphene that has palladium nanoparticles dispersed throughout.
Electrical contacts are added using silver paste and copper wires.
Samples are tested under a 62 mA UV laser while recording resistance changes as the light switches on and off.

Our results show a clear increase in resistance change under illumination for the Pd-infused samples.
The cycling data demonstrates consistent ON/OFF behavior with strong repeatability, confirming plasmon-assisted photocarrier generation and successful light response.

We successfully created plasmonically enhanced laser-induced graphene, palladium-infused laser-induced graphene showed stronger optical-electrical response, and the fabrication method remains low-cost and scalable.
This demonstrates that plasmonic nanoparticles provide an effective pathway to improve flexible photodetectors.

Future goals include testing silver and gold nanoparticles with stronger plasmonic response, expanding testing to more wavelengths beyond UV, conducting durability and reliability testing, and performing additional structural analysis (Raman, SEM).

Thanks to the Undergraduate Research Scholars Program, Dr. Pilgyu Kang, and the Nanomaterials Lab at GMU for their support.

Cells, Individuals, and Community College of Public Health Honors College OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR

Rest and Results: The Relationship Between Sleep, Stress, and Grade Point Average (GPA) in Undergraduates

Author(s): Michael Kaleem

Mentor(s): Ali Weinstein, College of Public Health

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Abstract

Michael Kaleem
URSP Abstract

Title
Rest and Results: The Relationship Between Sleep, Stress, and Grade Point Average (GPA) in Undergraduates

Authors: MK and AW

Background
Sleep plays an important role in college students’ cognitive functioning and overall academic success, making it a crucial area of study. However, the specific relationship between parameters of sleep and academic performance has not been well studied. In addition, college students have also reported increasing levels of stress over the past few years, and stress can affect both sleep and academic success. Therefore, the current investigation examined the associations between duration of sleep, sleep quality, and stress with academic success.

Methods
Data were collected by surveys completed by undergraduate students at a large, public university. Sleep duration and sleep quality were assessed by the Pittsburgh Sleep Quality Index (PSQI), and stress was measured with the Perceived Stress Scale. Academic success was operationalized as a self-reported GPA. Pearson correlations determined association between the variables of interest with p<0.05 set as the level of statistical significance. Results
There were 196 undergraduate students that participated (70.1% female, 36% white/non-Hispanic, 27.6% Asian/Pacific Islander, age: 18.1±0.5). Both sleep duration and sleep quality were statistically significantly related to GPA (r=0.17, p=0.02, r=-0.13; p=0.001, respectively). Therefore, as the number of hours of sleep increased and as sleep quality increased (lower number on PSQI is indicative of better sleep), GPA increased. Elevated stress levels were related to both sleep duration (r=-0.14; p=0.01) and sleep quality (r=0.40; p<0.001) but not significantly correlated to GPA (r=-0.01; p=0.92). Conclusion
This study found that sleep duration and sleep quality were positively associated with academic success. Although stress was not directly related to academic success, it was associated with both sleep duration and quality, suggesting that stress may influence academic success indirectly through its effects on sleep. Future research should explore how demographic, socioeconomic, and environmental factors influence sleep patterns and academic success to better inform strategies that support student success.

Audio Transcript

How many hours of sleep did you get last night? And do you think it affects your GPA? Sleep is something most college students sacrifice, yet it’s essential for memory, learning, and mental functioning. My name is Michael Kaleem, and our research explored the relationship between sleep, stress, and academic performance in undergraduates. We wanted to know: Could better sleep actually lead to better grades—and how does stress fit into the picture?

Sleep is more than just rest. During sleep, the brain strengthens memories, organizes information, and supports attention and problem-solving. So, in theory, students who sleep longer and sleep better should perform better academically. But college life is complex—so real data is needed to understand what’s actually happening.

Stress is one of the biggest disruptors of sleep. High stress can shorten sleep duration, worsen sleep quality, and impact mood and focus. Because stress influences both sleep and academic functioning, we wanted to understand whether stress plays a direct role in GPA—or whether its effects occur indirectly through sleep.
We surveyed 196 undergraduate students at a large public university. Sleep duration and sleep quality were measured using the Pittsburgh Sleep Quality Index, stress was assessed using the Perceived Stress Scale, and students self-reported their GPA. We used Pearson correlations to examine how these variables were related, with significance set at p < 0.05.
We found that both sleep duration and sleep quality were significantly related to GPA. Students who slept more hours tended to have higher GPAs. And students with better sleep quality—which means fewer sleep problems—also had higher GPAs. So in this sample, sleep really did matter for academic success.
Stress told a different story. Stress levels were not directly related to GPA. However, stress was strongly connected to both sleep duration and sleep quality. Students with higher stress slept fewer hours and had worse sleep quality. This suggests that stress may influence academic performance indirectly—by affecting the amount and quality of sleep students get.
Our findings show that sleep duration and sleep quality are important predictors of academic success. Even though stress didn’t directly affect GPA, it played a major role in disrupting sleep. This highlights a powerful message: helping students improve sleep habits and manage stress can support academic performance, cognitive functioning, and overall well-being.
Future research should explore how demographic, socioeconomic, and environmental factors influence sleep and academic outcomes. Understanding these differences can help universities design more effective programs to support healthier sleep, reduce stress, and improve student success across diverse populations.

College of Engineering and Computing College of Humanities and Social Science Honors College Making and Creating OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR Winners

A Robotic Cat for Examining Camera Clarity and Privacy in Human–Robot Interaction

Author(s): Alexia De Costa

Mentor(s): Eileen Roesler, Department of Psychology

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Abstract

This project presents the Bioinspired Automated Robotic Cat (BARC), a functional companion robot designed to support research in human–robot interaction and privacy-aware design. BARC features camera-based facial detection, expressive gaze behaviors, audio responses, and various soft and rigid materials to mimic a household cat. Because camera systems can enhance interaction while raising privacy concerns, the ongoing study compares peoples’ responses under two conditions: a clear, high-quality camera filter and a blurred, low-clarity camera filter. Using surveys and observation of touch behavior, the study examines how camera clarity shapes engagement and perceived privacy, informing the design of social robots that are effective while respecting user comfort.

Audio Transcript

Have you ever wondered what a robot actually sees when it looks at you?
Today, social and service robots are becoming increasingly common, and many rely on cameras for facial recognition and user engagement. But as useful as cameras are, they also raise important questions: Do they make people feel watched? Can a robot feel friendly while still respecting privacy?

These questions lie at a key intersection in human–robot interaction, that robots need perception to understand us, yet high-resolution sensing can make people uncomfortable. So I wanted to explore a central challenge: can we reduce privacy concerns without making interactions less enjoyable? And does being transparent about what a robot sees change how people feel?

To investigate this, I designed and built a robot cat from scratch called BARC, the Bioinspired Automated Robotic Cat. BARC is part engineering platform and part research tool. It can switch between two controlled camera conditions: a clear, high-quality camera filter and a blurred, low-clarity filter that still allows for partial facial detection. These interchangeable physical filters let me directly compare how different levels of sensing clarity influence interaction.

BARC is also designed to feel expressive and lifelike. It uses camera-based facial detection for gaze behavior, animated OLED eyes, a speaker for cat-like sounds, and soft and rigid materials that mimic the look and feel of a household cat. Through surveys and observations of touch behavior, my ongoing study explores how these two camera conditions shape user engagement and perceived privacy.

To create BARC, I began with feline anatomical references, studying limb placement, joint spacing, and overall proportions, to inspire the CAD model for the chassis. I laser-cut the acrylic components and assembled them using screws and tab-and-slot joints for a sturdy, lightweight frame.

At the heart of the robot is a Raspberry Pi 4, which handles perception and behavioral control.

A camera provides the main sensory input for facial detection.

Two OLED displays animate expressive eyes that track the user once a face is detected, giving the illusion of attention and social presence.

A speaker and amplifier generate a range of cat sounds, from meows to purrs to alarmed yowls.

An accelerometer-gyroscope detects movement, such as being picked up or shaken, so BARC can respond appropriately.

Servos are controlled by a PCA9685 driver, animate the limbs, jaw, head, and tail.

All behaviors are programmed in Python and organized in a state machine with modes such as Idle, Seeking Attention, Interacting, and Startled. BARC transitions between these states based on sensory input and probability, helping interactions feel natural rather than scripted.

To examine how camera clarity influences engagement and privacy perceptions, BARC serves as a fully capable research platform. Seventy-two participants are currently part of a single-blind study with two groups:

Group 1: interacts with BARC using a clear camera filter

Group 2: interacts with BARC using a blurred, privacy-preserving filter

The physical filter is noticeable, so using filters in both groups keeps the robot visually consistent. That way, any differences we see are truly due to what the robot can or can’t perceive.

Participants interact with BARC, complete a survey measuring constructs such as Perceived Sociability and Perceived Enjoyment, and then are shown a live camera feed so they can see the actual resolution of the robot’s vision. Afterward, they complete a second survey measuring perceived privacy, perceived surveillance, disturbance, and attitudes about robots.

The hypotheses are:
1: No difference in sociability, enjoyment, or touch behavior.
2: The filtered-camera group will report higher perceived privacy.
3: The clear-camera group will report higher perceived surveillance.

This interdisciplinary project connects mechanical engineering, psychology, and human-robot interaction to better understand how people perceive robotic sensing. BARC’s expressiveness, biological inspiration, and controlled camera conditions make it a powerful research platform.

By comparing clear versus filtered camera views, this research explores whether privacy concerns come from what the robot actually sees, or what users believe it sees. Ultimately, the goal is to guide the design of future social robots that remain engaging and respectful of user’s privacy

Special thanks to Dr. Eileen Roesler (Psychology) and Dr. Daigo Shishika (Mechanical Engineering) for their invaluable mentorship. Thank you to Katya Schafer for assistance with data collection, and to Dr. Karen Lee and OSCAR for their support and funding, which made this project possible.

Thank you!

College of Engineering and Computing Making and Creating OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR

Laser-Induced Graphene–Nanoparticle Platforms for Plasmonic Enhanced Photosensing

Author(s): Ali Kabli

Mentor(s): Pilgyu Kang, Mechanical Engineering

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Abstract

This project explores the potential for enhancing the performance of Laser-Induced Graphene (LIG) using metallic nanoparticles (NPs) as a platform for fabricating photosensors with enhanced sensitivity. The main question being addressed is can a Laser-Induced Graphene–Palladium nanoparticle (LIG-PdNP) nanocomposite enhance sensor sensitivity through plasmonic and interfacial effects? Research has been conducted in the past regarding the use of LIG as the functional material in a photosensor, and the rationalization behind using these metallic NPs in a nanocomposite material is to improve the sensitivity of the sensor by improving the photoresponsivity. This is due to the introduction of plasmonic effects from the NPs, which allows for the photocurrent to flow more efficiently. The main novelty behind this particular project’s approach lies in the synthesis of the nanocomposite, where classic means would have the NPs deposited on the LIG surface creating point contacts. The synthesis technique being explored here involved a one-step synthesis via precursors and a polymer substrate, which creates a “seamless interface” between the components of the functional material. This interface allows for the electrons to flow freely between the LIG and NPs, enhancing the photoresponsivity of the device. Two devices were compared, one with 0wt% of PdNPs, and another with 30wt% PdNPs in order to observe any improvements in the performance of the devices when hit with a blue laser (448.2nm wavelength). Future research regarding this project includes using NPs with higher plasmonic effects such as gold or silver, as well as refining the geometric footprint and patter of the sensor itself to increase performance further.

Audio Transcript

Hello everyone, my name is Ali Kabli and today I’m going to present to you my undergraduate research project, Laser Induced Graphene Nanoparticle Platforms for Plasmonic Enhanced Photosensing. This project was advised by Dr. Pilgyu Kang from the Department of Mechanical Engineering.

So to give a brief background and introduction, past research has been done by Dr. Kang and his group, utilizing laser-induced graphene, or LIG, as a sensing element in photosensors. Now, these sensors operate based on the premise of photosensitivity. You basically shine a laser of some known wavelength at the sensor, which will induce some photocurrent. The change in photocurrent can be observed and used for sensing purposes. We want to improve the sensitivity of these devices by introducing metallic nanoparticles, or NPs, to increase the plasmonic effects and photoresponsivity of these devices. Now, for the purposes of this project, the specific nanoparticles that were used were palladium. However, any metal that has known plasmonic effects can be used.

For the purposes of this presentation, or project, we proposed a novel nanocomposite synthesis technique, which resulted in a seamless interface between the LIG and the nanoparticles. Traditional methods would have you deposit these nanoparticles on the surface of the LIG, or whatever substrate you’re using, which results in a point contact between the particles and the bulk surface. The downside to this is the fact that that point contact doesn’t allow for the most efficient flow of electrons. However, through a one-step synthesis technique using precursors and polymer substrate, we are able to integrate these nanoparticles within the surface of the laser-induced graphene itself, allowing the electrons to flow seamlessly.

So, the main question that we were answering with this research project was, can a laser-induced graphene palladium nanoparticle nanocomposite enhance sensor sensitivity through plasmonic and interfacial effects? The plasmonic effects, once again, coming from the fact that we’re using these metallic nanoparticles, and the interfacial effects coming from the seamless interface through our unique synthesis technique.

The methods and procedure for this project involved the actual synthesis of our nanocomposite using the one-step technique. Then we would fabricate the photosensor device using the synthesized nanocomposite. It should be mentioned that the scale of this sensor was 500 millimeters by 500 milliliters, which is actually quite large given the nanoscale. It’s very, very large. So that may have resulted in the data being slightly skewed, which is an improvement that we will go over at the end of this presentation. Then we collected optical data regarding the photoresponsivity of the device by hooking it up to an optical testing apparatus where we would shine a laser on and off at known intervals. The laser’s wavelength was known for the purposes of this project. We were using a blue laser, 448.2 nanometers of wavelength, and we would plot the resulting photocurrent as a function of time. The long-term goals of this project are to one day harness these nanocomposites as a platform for plasmonically enhanced PEC or photoelectrochemical gas sensors.

Now here’s just a brief snapshot of the results. We see on the left side a comparison between the photocurrent resulting from a 30 weight percent nanoparticle nanocomposite and on the right side we have the photocurrent resulting from just pure LIG. As you can see the scale on the left side is in microamps, and the scale on the right side is in nanoamps, which means that we were able to show a drastic improvement, three orders of magnitude to be exact.

In conclusion, the experiment was a huge success in proving that plasmonic effects could enhance the sensitivity of these devices. However, more work is still needed in the future. We can refine the geometry and footprint of the sensor itself so that it’s a lot smaller than 500 by 500 millimeters. We can also test other nanoparticles with known greater plasmonic effects, such as gold or silver. And we can also play around with different laser parameters, focusing the laser’s beam more, increasing the wavelength, etc.

Some acknowledgements. Of course, my advisor, Dr. Pilgyu Kang, Graham Harper, who aided in data collection on this project, and Philip Acatrinei, for being an indispensable help in data collection and in setting up the experiment itself. He actually programmed the software that we were using to collect the data. So without him, this project would not have been possible. Thank you.

OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR US, Global, and Beyond Winners

SPATIAL DYNAMICS OF LOCAL NEWS: MAPPING CITY CO-MENTIONS IN ALABAMA

Author(s): Tugce Burcu Gundogdu

Mentor(s): Myeong Lee, IST

Abstract

This study analyzes 31,004 Alabama news articles (2012–2024) to examine how cities are connected through co-mentions. Using a large language model, we extracted geographic references to build networks capturing spatial and symbolic ties. We developed a relationship typology to interpret these links. Preliminary results show that news categories shape distinct spatial patterns, offering insight into how media narratives influence regional identity and reveal the relational dimensions of news deserts.

Audio Transcript

1
00:00:07.560 –> 00:00:22.750
Tugce: Hi, everyone! My name is Tugce, I’m a third-year computer science student at George Mason, and my project, Spatial Dynamics of Local News, Mapping City Co-Mentions in Alabama, is about how local news connects cities in Alabama.

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00:00:22.880 –> 00:00:45.090
Tugce: So, when we talk about news deserts, which is a term in information science that mentions… that describes places that don’t get enough local news coverage, or don’t have enough news outlets to cover their local news, we mostly focus on places that don’t get covered. But something we notice is that news doesn’t just talk about places, it also links them together.

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00:00:45.340 –> 00:00:57.109
Tugce: For example, two cities might get mentioned in the same story because they share an event, a crime pattern, a rivalry, or a regional issue. These links tell us a lot about how local identity is shaped.

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Tugce: And they reveal a lot of information about a region’s new geography.

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Tugce: So, what we did is, we took about 31,000 Alabama news articles, ranging from 2012 to 2024, and we used an LLM to plot all the place names, and then built a co-mention network, which is kind of like a map of which cities appear together in stories.

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Tugce: We found 79,000 place mentions, 351 Alabama cities, and about 17,000 city pairings.

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Tugce: Then we looked at how often each pair of cities co-appears. This gives us an idea of the region’s news geography.

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Tugce: So, a few interesting patterns that I like to point out is Tuscaloosa was the main news hub overall, which makes sense because our news outlet is based there. And…

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Tugce: We see that Tuscaloosa is the city that gets mentioned together with a lot of other cities in news. And Birmingham becomes the center of crime-related news. So, in crime-related news, the other cities mostly get mentioned together with Birmingham.

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00:02:10.000 –> 00:02:14.360
Tugce: And Montgomery becomes the center of political and economic coverage.

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Tugce: And, not surprisingly, Auburn and Tuscaloosa are super connected in sports stories because of their history of ongoing rivalry. So, what does this all mean? So, when we look at these connections between these cities and how much they appear together in news, we get a story and an idea and a

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Tugce: local identity appears about these regions. But when news desserts happen, they aren’t just about where coverage is missing, but also where relationships are missing, because we can’t see these stories.

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00:02:49.310 –> 00:02:59.169
Tugce: So, some cities don’t just get less coverage, they rarely get linked to other places, which adds another layer of isolation for the news deserts.

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Tugce: So, thank you all for listening to my project. I would like to thank my mentors and professors for their invaluable guidance throughout this project. I am especially grateful to my mentor, Dr. Myeong Lee.

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00:03:43.680 –> 00:03:58.979
Tugce: and Dr. Jieshu Wang for their mentorship, encouragement, and expertise, which shaped the development of this research. I also really appreciate the support of George Mason University’s Oscar program for providing a great research environment.

College of Humanities and Social Science OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR US, Global, and Beyond

Artificial Influence: How Artificial Intelligence (AI) Shapes Global Geopolitics

Author(s): Larion Krivtsov

Mentor(s): Patrick Ukata, Global Affairs

Abstract

Artificial intelligence (AI) has rapidly evolved from a technological innovation into a central force reshaping global geopolitics. As states race to harness AI’s economic and strategic potential, the technology has become a defining factor in international competition, cooperation, and governance. This paper examines how AI is transforming global power dynamics by shifting influence toward actors with advanced computational capacity, vast data resources, and strong innovation ecosystems. The analysis argues that AI functions as a dual-use geopolitical lever: it intensifies strategic rivalries among major powers while simultaneously creating new opportunities for collective regulation and shared ethical standards.
AI is altering the nature of conflict by enabling autonomous weapons systems, accelerating cyber operations, and enhancing disinformation campaigns that blur traditional distinctions between war and peace. These developments challenge established security doctrines and create new vulnerabilities that demand coordinated international responses. At the same time, AI exposes significant gaps in global governance, raising questions about accountability, transparency, surveillance, and human rights that existing institutions struggle to address.
Using a qualitative synthesis of contemporary scholarship, the paper maps AI’s geopolitical effects across four domains: great-power competition, military and security transformation, global governance architectures, and regional ethical perspectives. The findings show that while AI amplifies inequalities and fuels geopolitical tension, it also offers pathways for new regulatory frameworks and multilateral cooperation.
Ultimately, the paper contends that the geopolitical future of AI will depend not on technological inevitability but on the ethical, political, and institutional choices made by human actors. Ensuring that AI advances global stability and human well-being will require governance models that balance innovation, security, and shared responsibility.

Audio Transcript

Hello,
In the early twenty-first century, artificial intelligence has emerged not simply as a technological breakthrough but as a transformative geopolitical force—one that is redefining how power is created, exercised, and contested on the global stage. What once belonged to research labs and commercial enterprises has now become a central pillar of national strategy. Major powers—the United States, China, and the European Union—treat AI with the same seriousness that past generations reserved for nuclear technology. It’s entirely accurate to say that AI has emerged as a powerful and influential tool in shaping global political dynamics.
This transformation raises a key question: How does AI reshape global geopolitics by altering power relations, national security, and international governance? The answer, as this research argues, lies in understanding AI as a dual-use geopolitical lever. On one hand, AI fuels strategic rivalries, widening technological inequalities, and destabilizing traditional hierarchies. On the other, it creates unprecedented opportunities for shared regulation, ethical standards, and cooperative global frameworks.
AI is redistributing power in three critical ways.
First, it rewards states and corporations with data, computational capacity, and technological expertise—not those with traditional industrial strength. The result is a new form of digital stratification that determines who leads, who follows, and who risks being left behind.
Second, AI is redefining conflict itself. Autonomous weapons systems, cyberattacks powered by machine learning, and sophisticated disinformation campaigns blur the boundaries between war and peace. Deterrence, defense, and security doctrines are being rewritten in real time.
Third, AI challenges the foundations of global governance. It raises profound questions about accountability, transparency, and ethics—questions no nation can resolve alone. International law, built for an earlier technological era, must now confront algorithms that make decisions far faster than traditional institutions can respond.
But this story is not only about rivalry. It is also about responsibility. AI forces us to reconsider what human agency means in an age of automated decision-making. It compels us to think about who benefits from technology and who might be harmed by it. And it reminds us that the future of global stability will depend not on machines themselves, but on human choices—ethical, political, and institutional.
If nations view AI only as a weapon of competition, we risk repeating the mistakes of past arms races. But if we recognize its dual-use nature—its capacity to inspire both competition and cooperation—we can harness AI to strengthen global governance, promote shared security, and advance human flourishing.
In the end, the geopolitical future of artificial intelligence will be determined not by the power of our algorithms, but by the wisdom of our decisions. Let us choose a future where AI serves humanity—rather than one where humanity becomes subordinate to its own creations.
Thank you for your attention.

Cells, Individuals, and Community College of Humanities and Social Science OSCAR

Does Immigrant Advantage for Academic Outcomes Persist in High School Similarly for Black and Hispanic Students?

Author(s): Vlera Baftija

Mentor(s): Adam Winsler, Applied Developmental Psychology

Abstract

One out of four students in U.S. schools comes from an immigrant-lead household, with 17.6 million children under 18 living with at least one immigrant parent. The ‘immigrant advantage’ posits that first-generation immigrant students often exhibit better academic outcomes than second-generation immigrant students, who exhibits better academic outcomes than non-immigrant students, despite first- and second- generation students facing socioeconomic and linguistic challenges. Prior research has documented this advantage in early education but less is clear about its persistence into high school, as results seem to vary. The current study examines immigrant advantage in grades 9 through 12 by using pre-existing data from Miami School Readiness Project, a large-scale, 18-year longitudinal study of students attending Miami Dade County Public Schools. Research questions include (1) To what extent does the immigrant advantage appear in high school academic outcomes? and (2) Are patterns of the immigrant advantage similar for Black and Hispanic immigrant students? The sample (n=4,341) includes 2,704 first-generation immigrants, 777 second-generation immigrants, and 860 non-immigrants. Outcome variables include end of year GPA in 9th and 12th grade, cumulative high school GPA, standardized math and reading test scores in 10th grade, end-of-course exam grades for Algebra 1, attendance in 9th and 12th grade, suspension, retention, and graduation. Multiple regression analyses will be run controlling for student race, poverty, ELL status, disability, and gender, with immigrant status as the primary independent variable, and then race-by-immigrant status interactions will be run to test question 2.

Audio Transcript

Hello, my name is Vlera Baftija and for my research project I am examining the immigrant advantage for academic outcomes and whether it persists in high school similarly for black and Hispanic students.

The US is known to be a melting pot, rich with diversity from cultures all over the world. There is a huge immigrant population in the states with one out of four students in public schools coming from an immigrant household. Given the significant presence of immigrant families in the US, it is important to examine the educational trajectories and experience of children of immigrants to help ensure their success and maximize their opportunity to thrive.

A first generation immigrant is when both the parent and the child are foreign born. A second generation immigrant is when the parent is foreign born, but the child is US born and a third plus generation or a non-immigrant is when the parent and child are US born.

The immigrant paradox or the immigrant advantage is the idea that first generation immigrants display better academic outcomes than second generation immigrants who display better academic outcomes than the third plus generation immigrants. This idea comes from the result of parents’ optimism and aspirations for their child success and influencing the child to exhibit academic resilience, despite socioeconomic disadvantages.

There are a few protective factors for this, which include familial values towards education, support from family and or ethnic ties, biculturalism, and bilingualism.

The literature has shown an immigrant advantage in elementary school in which first generation and second generation students generally perform as well or even better than the third plus generation students in academic measures such as standardized tests, grades, attendance, retention, and behavioral and soc emotional development.

However, when we get into the secondary level, the art makes results with some studies finding a first generation immigrant advantage. Other studies finding a second generation immigrant advantage, and some studies finding no advantage at all.

Reasons for this include aculturation tasks, adultification, parentification, helping out financially and documentation status.

Some studies have also looked at the moderation by race and the overall findings have been that the advantage is bigger for black immigrants when compared to their third plus counterparts and smaller for Hispanic immigrants when compared to the Hispanics third plus counterparts.

The current study will be examining the immigrant advantage in the Miami School Readiness Project, a large scale five cohort, 18 year log to project, consisting over 58,000 students. The gap in the literature is that there are very limited studies examining the immigrant academic outcomes past 10th grade, and excluding stuff like cumulative GPA and graduation.

My first research question is asking to what extent does the immigrant advantage appear in academic outcomes in grades 9 through 12 My academic outcomes is as follows, and I hypothesize that the immigrant advantage will be present at the start of high school, but will be smaller by 12th grade.

My second research question is asking if the patterns of the immigrant advantage in high school are similar for black and Hispanic immigrant students. I hypothesize that the immigrant advantage will be bigger for black immigrants and smaller for Hispanic immigrants when compared to their third plus counterparts.

For my participants, I will have roughly 4,341 students. I will have 2704 first generation immigrants, 777, second generation immigrants, and 863 plus generation immigrants. From the overall sample of the 58,000 students, about 80% of Hispanic, and about 20% are black.

For my independent variables, my primary independent variable will be the generation status and I will be controlling for things such as student race, poverty status, English language learner status, disability status, and gender.

My dependent variables will include end of year GPA in grades 9 and 12, cumulative end of high school GPA, standardized math and reading test scores in ninth and tenth grade, attendance in ninth and 12th, school suspension, retention, and graduation.

For my proposed data analysis plan for my first research question a multiple regression analysis will be used with the primary independent variable being the immigrant status while controlling for student race. Poverty status, ELL status, disability status, and gender. Dependent variables will be the academic outcome measures and each dependent variable will be entered one at a time in separate models.

For my second research question, I will be using a similar multiple regression model that was described for the previous question, but immigrant status will be crossed with race to include interaction terms.

These are my acknowledgments and thank you for watching. and these are the references that were used during the presentation.

Cells, Individuals, and Community College of Humanities and Social Science OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR

Elementary School Gifted Program Identification and Secondary School Academic Outcomes for Black Students

Author(s): Ezra Lynch-Holland

Mentor(s): Adam Winsler, Psychology

Abstract

Gifted children show high potential to achieve but need specialized services to develop their capabilities. Black students specifically have been persistently under-identified as gifted and the efficacy of gifted programs for Black children is unknown. This psychology honors thesis will explore the impact of gifted identification on secondary school outcomes (6th through 12th grade) with data from the Miami School Readiness Project, a longitudinal study of students that attended Miami-Dade County Public Schools. Research questions include (1A) To what extent does being identified as gifted in elementary school contribute to secondary school academic outcomes for Black students?, (1B) Are positive effects mediated by elementary school academic performance?, and (2) Are the observed differences between gifted and not gifted Black students in secondary school the same for students in poverty vs. not in poverty, and for boys vs. girls?
The sample for this study includes Black students that had data for at least one year of high school (n ≈11,198). Of the sample, ~13% were identified as gifted in elementary school. Outcome data include cumulative high school GPA, standardized math and reading test scores in 8th and 10th grade, grade retention, attendance from 9th and 12th grade, school suspension, and on-time graduation. Multiple regression and logistic regression analyses will be done, controlling for initial child cognitive skills and social skills at age 4, gender, English language learner (ELL) status, poverty status, and early school performance. Results are expected to show gifted identification to be correlated with positive secondary school outcomes when compared to non-gifted students. It is expected that gifted education will show stronger positive effects for students in poverty and for boys.

Audio Transcript

Hello, my name is Ezra Lynch-Holland, and my Oscar URSP project is entitled, Elementary School Gifted Program Identification and Secondary School Academic Outcomes for Black Students. This project was done under the mentorship of Dr. Adam Winsler.
Federally, gifted children are those that display high potential for success intellectually, creatively, in a leadership capacity, or in a specific discipline. The federal government also acknowledges they need services not ordinarily provided by the school to develop these capabilities, and requires identification of gifted children. School districts tend to disproportionately over-identify students with higher socioeconomic statuses and under-identify those in poverty. When it comes to race, Black students are persistently under-identified nationally, even when they make up larger parts of the district’s population.
Black students’ education is particularly impacted by their relationships, where positive ones can act as a strong buffer against negative experiences. However, gifted Black students face isolation in gifted spaces from their non-gifted Black… and from their non-gifted Black peers, with T’s and being common in the latter. Microaggressions from both other students and teachers are present in gifted spaces in the form of underestimating their intellectual ability or belittling their interest in Black history and topics.
Black and Hispanic students tend to spend less time in gifted programs, and the improvements giftedness typically has on academic achievement are somewhat diminished in Black comparisons. Even so, it has been shown that the self-esteem of gifted Black students benefits more from gifted programs than their non-Black peers.
This study will derive from the Miami School Readiness Project dataset, or MSRP. It was a cohort sequential longitudinal study where data was collected from 2002 to 2020. Students included in the study are those that received subsidies for community-based childcare or public school pre-K, and then went on to attend Miami-Dade County Public Schools. In the larger study, the total number of students included that have data for at least one year between grades 6 and 11 is 32,885. 82% are on free and reduced lunch, and 52% are male. This study seeks to investigate if being gifted has positive academic impacts through secondary school by controlling for prior achievement and cognitive skills using school… administrative school data.
To be included in the study, a student will have had to be present for at least 8th grade and identify as Black in administrative school data. Bicep sample from the MSRP consists of 11,198 students that identified as Black, including Afro-Latina students. Around 13% of them were identified as gifted according to administrative school data. Outcomes that will be analyzed include cumulative high school GPA, standardized test scores in 8th and 10th grade, and school attendance, as well as grade retention, school suspension, and on-time graduation. Multiple regressions will be used for continuous outcomes and logistic regressions for categorical outcomes.
My research question 1A is to what extent does being gifted identified in elementary school contributes to secondary school academic outcomes and school engagement for Black students. I hypothesize that being identified as gifted in elementary school will be correlated with greater academic achievement and engagement outcomes when compared to non-gifted students.
My 1B question asks if positive effects are mediated by school, elementary school academic performance. My hypothesis is that after considering elementary school performance, being identified as gifted in elementary school will still have a higher correlation with those greater academic achievement and engagement outcomes. These mediators will be matched with their resultant outcomes for the regression models.
The research question 2 asks if the observed differences between gifted and not gifted students in secondary school are the same on the basis of poverty status and gender, as well as English language learner status. I hypothesize that boys, those in poverty, and those that aren’t English language learners will benefit more from gifts programs than their counterparts. And here are my references. Thank you.

College of Humanities and Social Science OSCAR Undergraduate Research Scholars Program (URSP) - OSCAR US, Global, and Beyond

When No Response is a Response: Predicting Survey Non-Compliance in Isolated, Confined, Extreme Analog Space Missions

Author(s): Amber Bartlett

Mentor(s): Lauren Kuykendall, Psychology

Abstract

Long-duration space exploration will place small, interdependent teams in isolated, confined, and extreme (ICE) environments, where they will face risks including communication delays, high autonomy, increased workload, team tension, and intense stress. All of these risks require research studies aimed at mitigating them, many of which take place at analog space stations. However, these analog missions, which aim to study human behavior in ICE settings, suffer from chronic survey noncompliance, which threatens data integrity and reduces the accuracy of crew monitoring. This project examines which individual characteristics predict who completes research surveys during missions at the Mars Desert Research Station, a Mars-analog habitat in Utah. Before their missions, crew members completed questionnaires assessing personality (with a focus on conscientiousness), their identification with their team, their cultural values (especially collectivism, or putting the group before oneself), and their difficulties with emotion regulation. During the mission, they were asked to complete brief daily and weekly surveys. For each person, I will calculate survey compliance as the percentage of assigned surveys completed, and I will use regression models to test whether conscientiousness, emotion regulation, team identification, and collectivism predict higher compliance. I will also test whether collectivism strengthens the link between team identification and survey completion, such that highly collectivistic crew members who strongly identify with their team are especially likely to respond. I expect that crew members who are more conscientious, better at managing their emotions, more strongly identified with their team, and more collectivistic will show higher survey compliance. The work integrates literature on ICE stressors, organizational citizenship behavior (OCB), survey methodology, and individual differences to generate actionable recommendations for designing analog-station research protocols and for operational monitoring in deep-space missions.

Audio Transcript

Hi, my name is Amber Bartlett. I’m an honors psychology student at George Mason University. My project is called “When No Response Is a Response, predicting survey non-compliance in isolated, confined, extreme, analog space missions”

My mentor is Dr. Lauren Kuykendall in the Industrial Organizational Psychology Department. So what is the big picture of my project? Long duration missions to Mars and to the moon will place very small crews into what we called isolated, confined, extreme, or ICE environments. These missions will involve tight living quarters, high workloads, autonomy, communication delays, and one of the tools we can use to track how these people are doing is through self-report surveys.

But the issue with doing research on ICE teams is the fact that the sample sizes are incredibly small, so when people skip surveys, we lose statistical power and increase the risk of error in our findings, and missingness is often not random. The people who stop answering might be the ones who are most stressed out, which means that things can be biased. So this leads to my core question, can we predict who complies with surveys before a mission? If we can identify likely non-responders ahead of time, then we can actually anticipate, model, and design around that.

So this project is a part of a collaboration between the University of Central Florida, where we’ll be using UCF’s IO Psychology PhD student Andres Käosaar’s data set from the Mars Desert Research Station. So MDRS is a Mars analog habitat where small crews simulate living on Mars. They’ll be conducting EVAs, conserving resources, and living in a confined environment.

And for this project, I will be using the data set that includes 99 individuals, 16 crew members, and a total of 761 habitat days. Most of the missions had teams of about six to eight members, and participation in Andres’ study was completely voluntary. Now because it was voluntary, I treat filling out these surveys as a type of organizational censorship behavior, and this is when people are doing small extra things at work that help their team organization, because doing his research survey was completely just to help his research.

So to understand why some people keep doing this extra work and why others don’t, I focus on four key constructs from the literature. So that’s including conscientiousness, emotional regulation difficulties, team identification, and collectivism within someone’s culture. So the knowledge gap is that analog space research already acknowledges chronic survey non-compliance and missingness.

However, individual level predictors or survey compliance and ICE teams remains undermodeled. We don’t have a clear guidance on what type of people are most likely to disappear from the data set, so my project is designed to help close that gap. So within this data set, participants completed pre-mission surveys which included measures such as conscientiousness, emotional regulation difficulties, team identification, and collectivism.

So during the mission, they received daily and weekly self-report surveys about their experience and well-being, and my main outcome is survey compliance, so this is defined as the percentage of assigned surveys each person completes over the mission. So based on this, I have five different hypotheses. First is higher conscientiousness will predict greater survey compliance.

Second, better emotional regulation will predict greater survey compliance. Stronger collectivism, stronger team identification, and collectivism moderates team ID compliance. All of this, I’m going to assume it will increase greater survey compliance.

Now with OSCAR’s help, I was able to visit MDRS in person, and these photos here show the habitat. It shows the people that I was with out there, and it really helped me understand what it’s like to be living in one of these space analog stations. So my next step is to run descriptive analysis on all of the hypotheses that I just showed you, and so that will be what I’m doing next semester.

The expected implications is that if my hypotheses are supported, this work suggests that voluntary survey compliance in ICE analogs is not random. It’s a predictable citizenship-like behavior rooted in personality, emotional regulation, and how people relate to their teams and groups. So this has several implications such as pre-mission screening, low burden monitoring, and then just identifying patterns of non-response, but also if my hypotheses are not supported, it means we should be looking somewhere else other than the OCB literature, which right now is where the main source of research is coming from when it comes to non-response and surveys.

So I want to thank my mentor, Dr. Lauren Kuykendall, Andres Käosaar, Dr. Seth Kaplan, Dr. Brielmaier, my psychology honors cohort, the MDRS director, and of course OSCAR URSP. If you would like a link to all of my resources that I’ve used, here’s a QR code for that. Thank you so much for listening.

College of Visual and Performing Arts Making and Creating OSCAR

I’m 43 and I Still Live with My Mom

Author(s): Shahroze Malik

Mentor(s): Gail White, CVPA

Abstract

This is our guiding question: Does the life of a man who knows nothing but pain and suffering hold more value than the life of a man who has known nothing but ease and bliss? Is there some vindication, some earned respect, some power or insight into the life spent in hardship over the life spent in clemency? Or is nature completely indifferent to whoever gets to live happily ever after and who gets to suffer? Does anyone even care if you lived a hard life? Can the man dying alone find contentment through all his struggles knowing the man in the room next to him has been given all the money, good looks, and talents at birth, and has his family by his side? What did the lonely man do to deserve this constant strife and what did the happy man do to deserve coddled love and blessings?

When one searches up on YouTube: “I’m 43 and I Still Live with My Mom,” thousands of search results come through of men and women voicing their struggles in their childhood bedrooms, feeling trapped in an endless cycle of self-loathing. There are so many men and women out there in the farthest corners of the internet feeling desperately behind, alone, and unwanted. These are videos of men and women who feel they can’t get ahead in life. These are people who have never won an award, never had a girlfriend/boyfriend, and never been complimented for any reason. I’m 43 and I Still Live with My Mom creates a mirror of empathy through an animated documentary, inspired from the testimonies of these people from their YouTube videos.

Audio Transcript

00:00:00:05 – 00:00:01:22
Hey, guys. My name is Rose Malik.

00:00:01:22 – 00:00:06:04
I’m working on an animated short
film funded by Oscar and it is titled.

00:00:06:04 – 00:00:09:04
I’m 43 and I still live with my mom.

00:00:09:06 – 00:00:11:09
Now, right off the bat,
you can already kind of

00:00:11:09 – 00:00:15:09
get an idea that this isn’t
the run of the mill, innocent,

00:00:15:18 – 00:00:20:02
cute, affectionate type of short film,
like probably done by a Pixar short.

00:00:20:03 – 00:00:23:05
No, this is a dark short film,

00:00:23:05 – 00:00:26:05
and it tackles really heavy subjects.

00:00:26:10 – 00:00:30:06
Now, when you search up this title, I’m 43
and I still live with my mom.

00:00:30:06 – 00:00:34:20
On YouTube, on Instagram, on TikTok,
on any video sharing service out there,

00:00:35:15 – 00:00:38:15
you will find a boatload of men and women,

00:00:39:05 – 00:00:43:02
a sea of people feeling desperately alone
all the way

00:00:43:02 – 00:00:47:15
from any corner of the internet,
uploading stories of their lives, rants

00:00:47:15 – 00:00:51:12
from their lives, talking
to anyone out there who’s willing to

00:00:51:12 – 00:00:56:07
listen about their conditions, about why
they feel so desperately behind in life.

00:00:56:07 – 00:00:57:03
Right.

00:00:57:03 – 00:01:00:22
So there’s like a serious this guy saying,
I likely die alone and angry.

00:01:01:03 – 00:01:04:02
This lady is saying 32 years old,
unemployed, single, living,

00:01:04:04 – 00:01:05:14
living with my parents.

00:01:05:14 – 00:01:07:16
This this guy is saying 35 years old.

00:01:07:16 – 00:01:10:16
Failed life over, over emotional
and socially anxious.

00:01:10:22 – 00:01:12:09
I’m 31 and have no friends.

00:01:12:09 – 00:01:14:10
I’m 23 and never had a girlfriend.

00:01:14:10 – 00:01:16:12
It’s not your fault
you’re falling behind in life.

00:01:16:12 – 00:01:18:20
I’m a 38 year old introvert
with no friends.

00:01:18:20 – 00:01:22:04
I’m 38 and most of society
would probably consider me as a failure.

00:01:22:16 – 00:01:26:01
Millions of people on this
on the internet,

00:01:26:07 – 00:01:30:09
talking and ranting,
decompressing to a camera

00:01:30:19 – 00:01:33:21
about all the all
the problems in their life that make them

00:01:33:21 – 00:01:36:21
feel worthless,
that make them feel like they’re losers.

00:01:37:05 – 00:01:37:20
Right?

00:01:37:20 – 00:01:43:11
And this person right here being ugly,
my experience has over 25 million views,

00:01:43:11 – 00:01:47:11
and it’s a cornerstone
about this type of experience

00:01:47:15 – 00:01:49:20
where people feel like
they don’t meet the standards

00:01:49:20 – 00:01:52:20
of what it takes to feel loved
or what it takes to feel valued.

00:01:52:22 – 00:01:55:16
And so they’re feeling so
alone and so behind, right.

00:01:56:21 – 00:01:57:10
As a part of

00:01:57:10 – 00:02:01:04
my research for Oscar,
I have watched all of these videos.

00:02:01:04 – 00:02:06:04
I have watched over 200, over 200 videos
and three things.

00:02:06:16 – 00:02:09:16
Three themes are mentioned by each
and every individual,

00:02:10:04 – 00:02:12:03
and that is the genetic lottery.

00:02:12:03 – 00:02:14:15
Most of these people feel horrendously
ugly.

00:02:14:15 – 00:02:17:21
They feel like
they’ve lost the gifts at birth.

00:02:18:23 – 00:02:21:23
The gifts that make you attractive, that,

00:02:22:03 – 00:02:25:16
make you feel, you know, valued
and romantic relationships.

00:02:25:16 – 00:02:28:09
They feel like they’ve lost this lottery,
right?

00:02:28:09 – 00:02:32:08
Another thing is that they feel completely
and totally isolated.

00:02:32:17 – 00:02:34:01
They feel very alone.

00:02:34:01 – 00:02:35:17
They have no friends to talk to.

00:02:35:17 – 00:02:39:00
This, to talk to about this,
no family that they can trust.

00:02:39:05 – 00:02:42:08
So they turn to YouTube
to express their darkest,

00:02:42:08 – 00:02:47:00
most vulnerable parts of themselves,
and they find almost more relief

00:02:47:11 – 00:02:51:04
and having strangers support them
than their own friends and family.

00:02:51:23 – 00:02:55:19
And the last thing is, they all, all of
these people feel like they’re outcasts.

00:02:56:05 – 00:02:59:06
All these, these were not the popular boys
and girls at school.

00:02:59:13 – 00:03:03:07
These people were not valued because
of their looks, because of their talents.

00:03:03:12 – 00:03:06:11
They were relatively ignored
pretty much all their lives.

00:03:06:11 – 00:03:08:06
And they’ve always felt like there

00:03:08:06 – 00:03:11:01
they were different,
that there was something wrong about them.

00:03:11:01 – 00:03:13:20
And they had no shelter.
They had no people.

00:03:13:20 – 00:03:16:00
They had no tribe to go to. Right?

00:03:17:08 – 00:03:17:23
So our

00:03:17:23 – 00:03:20:23
our short film tackles all of these themes

00:03:21:20 – 00:03:24:19
and what it is in a synopsis,
in a sentence.

00:03:24:23 – 00:03:27:18
Our short film
is this and his last attempt

00:03:27:18 – 00:03:30:22
to feel loved, a hopeless romantic builds

00:03:30:22 – 00:03:34:19
a life size wind up doll to dance with
for the rest of his nights.

00:03:35:07 – 00:03:37:06
And that’s the project we are pursuing.

00:03:37:06 – 00:03:41:06
That’s what we’re animating in 3D
animation based on original 2D

00:03:41:06 – 00:03:42:06
concept art.

00:03:42:06 – 00:03:45:06
And that’s what we’re going to do
for this project.

00:03:45:07 – 00:03:49:00
Over the past few months,
I’ve worked on creating a Polish script

00:03:49:02 – 00:03:53:13
for this short film, and we have tested
the script at various writing classes

00:03:53:13 – 00:03:56:14
at George Mason University and writing
groups at George Mason University.

00:03:57:05 – 00:04:03:01
From the script,
we have created a series of original rough

00:04:03:01 – 00:04:06:16
concept art, and it starts off

00:04:07:00 – 00:04:11:11
very rough with various rough drawings
trying to, execute the idea,

00:04:11:21 – 00:04:14:22
trying to get a sense of the character,
trying to get a feel

00:04:14:22 – 00:04:18:21
for all the moods
and themes of of the short film.

00:04:19:00 – 00:04:25:01
And then from this rough concept art,
we have created final, beautiful,

00:04:25:05 – 00:04:28:11
gorgeous
sketches for our final short film,

00:04:28:11 – 00:04:32:04
and we are going to take these sketches
and animate them in 3D.

00:04:32:14 – 00:04:37:20
Now, as you can imagine, all of this work,
this is three months of original,

00:04:38:01 – 00:04:41:01
hard human talent at work.

00:04:41:02 – 00:04:45:00
No AI is used in any of these designs
in any of these drawings.

00:04:45:00 – 00:04:49:13
This is all original ideas
at full display,

00:04:50:05 – 00:04:54:14
and we are proud of all the ideas
of all the conclusions that we’ve reached

00:04:54:14 – 00:04:58:22
from the script in order
to start production in the 3D side.

College of Humanities and Social Science Making and Creating OSCAR

Translating María Zambrano’s The Tomb of Antigone

Author(s): Grace Wood

Mentor(s): Ricardo Vivancos-Pérez, Foreign Languages

I

Abstract

Abstract
This project endeavors to create the first complete English translation of María Zambrano’s play The Tomb of Antigone (La tumba de Antígona, 1967). In this play-essay hybrid, Zambrano opens a philosophical dialog with Sophocles to offer a new interpretation of his Greek tragedy while illustrating her own experiences and ideas surrounding the Spanish Civil War. Using her philosophical construct of delirium, Zambrano creates Antigone’s stream of consciousness as she comes to her end. As the text demonstrates originality in its interweaving of genres to discuss the issues of Zambrano’s time, a translation of this work would foster new interpretations and discussions about Zambrano and Spanish culture with English speaking scholars in both the philosophical and literary disciplines.
To achieve this end, the mentor and student consulted various texts to understand the cultural, historical, and literary traditions of Spain during the time Zambrano was writing as well as the author herself, which led to the translation of the play’s prologue. The twelve-part play was then split into four sections that will be translated in two-week increments after which the mentor and student will convene to discuss the draft. Once the rough draft is complete, both the student and mentor will review and revise to create a more polished version. This project will result in a polished draft of the translation that will be sent to the María Zambrano Foundation in Vélez-Málaga to obtain permission to seek an academic publisher.

Audio Transcript

Have you ever walked into a bookstore and picked up a book and seen not one, but two sets of authors on the cover? The second set usually belongs to a group of people called literary translators. These men and women have taken up the extraordinary task of translating great works by Cervantes, Dante, and Tolstoy into English so that readers like you and I get a chance to enjoy their work. Hi, my name is Grace Wood, and in this video, I am going to show you my first attempt at trying to join these great men and women to become a literary translator. During my study abroad experience in Granada, Spain, I became familiar with the work of one Maria Zambrano, a famous 20th century Spanish philosopher and writer. Upon returning to the United States, I realized that much of this writer’s work has not been translated into English, thus barring scholars and the public from getting to enjoy her work. After doing some research and consulting with a faculty mentor, my independent study and URSP project was born. Over the course of an academic year, I endeavored to create the first complete English translation of Maria Zambrano’s play, The Tomb of Antigone, or La Tumba de Antígona, in Spanish, with the help of my mentor, Dr. Ricardo Vivancos-Pérez.
In this play-essay hybrid, Zambrano opens a philosophical dialogue with Sophocles to offer a new interpretation of his Greek tragedy, while illustrating her own experiences and ideas surrounding the Spanish Civil War. Sophocles’ original play tells the story of a young girl who wants to obtain burial rites for her brother who fought on the wrong side of the war. When her request is refused, she attempts to bury him on her own and is sealed into a tomb alive as punishment for being caught. Instead of Antigone committing suicide in the tomb like Sophocles intended, Zambrano instead uses her philosophical construct of delirium to create Antigone’s stream of consciousness as she waits for death. Antigone’s musings on life, death, faith, and brotherhood shed light on Zambrano’s own thoughts about the divided brotherhood surrounding the Spanish Civil War. As the text demonstrates originality and its interweaving of genres to discuss the issues of Zambrano’s time, a translation of this work would foster new interpretations and discussions about Zambrano in Spanish culture with English-speaking scholars in both the philosophical and literary disciplines.
So how do you go about translating a play? Well, first, I had to get the lay of the land to understand what Zambrano was thinking at the time she was writing the play. Starting in spring 2025, I consulted various texts gathered by my mentor to help me understand the cultural, historical, and literary traditions of Spain in the 20th century, as well as biographical and autobiographical works on the author herself. As both a fiction writer and a Spanish speaker, I had to understand her writing style, as well as her message and intentions in order to create the most faithful version of the play possible. At the end of the spring semester, I successfully translated the play’s 15-page prologue, which provides the context necessary to understand the play itself.
During this semester, we split the 12-part play into four sections with 3 parts each. I would translate one section every two weeks, after which I would meet up with Dr. Vivancos-Pérez to discuss the draft. In these meetings, we would discuss where I had not quite grasped some of the more archaic or literary Spanish being used and also work through passages I had trouble translating on my own. At the end of November, I successfully translated the entire play, resulting in a 75-page draft. Looking forward, my mentor and I will review and revise the draft to create a more polished version, which will be sent to the Maria Zembrano Foundation in Veles Malaga to obtain permission to seek an academic publisher, as they hold the copyright to her work. Once this text is published, English speakers around the world will be able to engage with this dramatic text and promote interdisciplinary discussions about Spanish culture through her work. Authors deserve to have their voices heard, especially in countries that don’t speak their native language. In time, I hope that Maria Zambrano will be the first of many authors I can give voice to in the English-speaking community. Thank you.

College of Engineering and Computing OSCAR

A Machine-Learning Approach for Studying Disinfectant By-Products (DBPs)

Author(s): Isaac Amouzou

Mentor(s): Ben Seiyon Lee, Department of Statistics

Disinfectant byproducts or DBPs for short are chemical compounds that form when disinfectants in water (ex: chlorine) react with natural organic matter. Chronic DBP exposure can cause significant negative health effects, such as bladder cancer, colon cancer, and pregnancy complications. DBP exposure is difficult to measure so a surrogate is needed to model DBP exposure. In the previous spring we developed statistical models that could accurately model the relationship between specific DBPs (selected using a feature selection method called lasso regression), categorical variables and toxic DBP classes when taking into account the public water system of origin. This project developed a classification framework for detecting at-risk public water systems using a machine learing method known as feed-forward neural networks. We also created an interactive tool for allowing anyone regardless of prior experience to explore the data used for the project, perform predictions using the previously developed models on the DBP classes, and evaluate the models with the DBP classes using either ICR data that contained data from over 13,000 measurements from 295 different public water systems or from data given by the user.

hello I am Isaac Amouzou and this is my project a machine learning approach for studying disinfectant byproducts or dvps disinfectant byproducts or chemical compounds that form when disinfectants in water react with natural organic matter some negative health effects that can come from chronic disinfectant byproduct exposure are bladder cancer colon cancer or pregnancy complications highly disinfectant water sources can lead to DBP exposure to ensure drinking water safety it is imperative that DBP levels and public water sources be properly monitored

dbp exposure is difficult to measure directly so surrogates have been used for example trihalomethanes or THMs are easier to measure and it was believed that THM concentrations are proportional to concentrations of other dbp classes a past study examined the link between THMs and a dbp class Haloacetonitriles or Hans the data consisted of over 9500 measurements from 248 Public Water Systems the result was that thms could only explain 30% of the variance in HANconcentrations

previously in Spring We examined four DBP classes using statistical models for this current project our goals were to create a framework to classify at-risk Public Water Systems given a DBP threshold using machine learning methods and to create a publicly available interactive tool to explore our data to generate and download predictions and evaluate model performance our data is from the information collection request database from the Environmental Protection Agency the data set contains over 13 000 measurements from 295 Public Water Systems

this is our framework for classifying at-risk Public Water Systems for class the classification we use a neural network model in this section we prepare the data to be processed and passed into the neural network for classification here we created a threshold to classify at-risk water systems and to prepare the DBP target class haa9 a specific threshold we used here was 72 micrograms per liter and we did 1.5 standard deviations off that limit so any public water system that is above 72 minus one and a half standard deviations will be classified as at risk and any below will be classified as save here we split the data into training and validation sets this is done because when we want to train our new network model we want to split up the validation sets so we can train with the specific training set and then only validate with data that hasn’t been seen before

here we want to prepare our data loader and batch data and batching is essential for stochastic gradient descent or SGD because the model updates its perimeters after processing each batch instead of updating after processing the entire data set this introduces Randomness in the update process and can lead to faster convergence and better generalization

this is the structure of a feed forward neural network a feed fowardr neural network is consisted of an input layer one or more hidden layers and then to an output layer each layer in the neural network will consist of a neuron which is a node that can take input and pass output a neuron also performs a computation with weights and biases before passing the computation through an activation function which is a function that adds non-linearity to a neural network which helps it the model learn complex relationships some common activation function are relu tanh or softMax here is the training and validation procedure for our neural network

here’s our neural network structure we have 326 inputs and two outputs with where the two outputs are either at risk which is represented by one meaning above the threshold or zero which means not at risk or below the threshold we have one hidden layer of 164 neurons and we have selected railroad as our activation function

here are the metrics we will use we have Precision which is sometimes known as positive predictive rate it is a measure for evaluating how well a model is at classifying positive or in this case at risk Public Water Systems and as well as recall which is sometimes known as true positive rate which is a measure for evaluating situations when for all cases where the data or at-risk Public Water Systems can be identified as positive and how accurate the model is at classifying them as positive

here we have an Epoch which is a single pass through the entire training data set and in the process of turning this model we have we use 18 epochs this is the final evaluation section and here we have a recall score of 0.72 of 72 percent the Precision score of 0.79 or 79 in an accuracy score of 0.83 or 83 which is just checking out how accurate a model was at classification

this interactive tool was made using R shiny the first panel shows a map of the Public Water Systems being used here on the all tab this denotes all public water systems for each DBP class when hovering over a specific marker you will be able to see the average concentrations of these DBP classes the public water system ID and the public water system name when you click on a marker you’ll be presented with a link to the EPA water system report on the public the specific public water system as well as the icr water system report

when you select a DBP from the drop down you it will you’ll be shown all public water systems that reported that specific DBP level and it will denote how close they are to a risk threshold with red being above the risk threshold yellow being within one standard deviation of the risk threshold and green being more than one standard deviation away from the risk threshold

on the predict panel if you have data that you would like to generate predictions for you can upload it as a CSV file like so and the dashboard will automatically remove any rows that have missing DBP or categorical values you can select which model you would like to predict with as well as which DBP class you would like to predict and generate your predictions here you can see the predicted value of the DBP class HKS or haloketones and the actual value although to generate predictions you do not need the actual value and if you want to download the data you can just simply click this button and download it as well

on the evaluation panel similarly you will also have to select a model that you wish to evaluate as well as which class you would like to evaluate the model on and again I’ll select hello ketones and you have two options here if you have data that you wish to test the model on yourself you can input the data as well as a similar process before and I’ll also remove any missing rows this time you actually will need the actual the class value in order to evaluate how well the model performs you’ll still have to click the evaluate button and you will get these metrics that appear the average prediction error is the average difference between the predicted DBP and the actual DBP the average percentage prediction error is the average percentage difference between the predictions and the actual DBP MSE or mean squared error is assesses the average square difference between the observed and predicted values rmsc is the square root of MSE so it’s called root mean squared error and while MSE measures the units that are the square of the target variable rmsc measures this in the same units as the target variable and here adjusted r squared is the proportion of the DBP class with the model can explain and I could also evaluate to see that a linear mix model as well if I wanted to use the icr data I can input seed which allows for random selection and reproducibility of results I can also input the training proportion which is how much of the data set the model will use for training so in this case 0.7 or 70% of the data will be used for training and I can evaluate here

the metrics are going to be the same but instead they are calculated on a test set which is kept separate from the training set here we also again have the test average prediction error which is the average prediction error on the test set the average percentage prediction error on the test set as well and MSE and RMSE on the test set too the new metrics we have here are a conditional r squared which is the proportion of the DBP class and in this case HKS are haloketones that the model can explain and the margin r squared which is the proportion of the DBP class that the fix effects or variables without taking into account public water system levels can explain and this is an interactive tool that you can use to explore the data as well as predict and evaluate the models using the models using neural networks we have created a framework to classify water systems that fall above or below a risk threshold we have created an interactive tool that will allow the users to examine the data that was used predict with and evaluate using the models and we have we will we plan to continue to develop and improve our classification framework and interactive tool we also plan to implement imputation to take into account the missing records for certain DBP classes

and these are citations and thank you for listening to my presentation