Category: OSCAR

Machine Learning aided Nanoindentation to Discover Material Properties

Author(s): Jake Samuel

Mentor(s): Ali Beheshti, Mechanical Engineering

Abstract

Machine learning has been explored as a method of identifying material properties from the material’s indentation data in a process called inverse analysis. A paper by Lu Lu, et. al examines machine learning techniques that could aid this process by adding a residual connection in a neural network (MFRN) [4]. This work examines how this technique improves inverse analysis for small samples of high fidelity data. The MFRN was compared to gaussian process regression, a multi-fidelity model that is well established. It was found that adding a residual connection lowered error significantly for inverse analysis for smaller samples of data.

Audio Transcript

Hello, my name is Jake Samuel and I’m here to talk about using machine learning aided nano indentation to discover material properties. So first let me get some background. Material property testing can be a long and expensive process. It can be hard to test on materials that may be small, or if you’re using a destructive test on a thin film material, you might not want that. So another way to go about for testing material properties is using nano indentation. So nano indentation is the process of adding a small indent in a material and then you’re measuring the loading and the unloading, the force over depth. And then if we were to know the material’s microstructure and the relationship of that between its properties, we can, we can find the material properties. However, that is a, that can be quite a hard process to do rigorously. So instead, machine learning techniques have been applied to this kind of problem with pretty good success, as machine learning models are able to find patterns which can be, that might not be obvious for humans. So the machine learning model we’re going to be examining in this model is a neural network which is just composed of, as you can see here, some hidden layers which have some kind of activation function. So each of them do a little math, and then you have some number of inputs which all lead to some number of outputs and essentially functions as a black box. And you can train it over very large data sets. But the problem is that if you were to train it on indentation data, an indentation test is also, you know, it’s a test you have to run. It can take a long time to perform. And if you are in the business of data collection, you know that data can become corrupted or you can have bad data really easily, and indentation is no different. If you have a long period of testing for indentation, you are likely to have bad data if the test gets messed up. So there is a paper by Lu lu that examines how certain machine learning techniques can be improved. So an example of this is multi fidelity, where if you have, not a lot of data points, you can supplement it with some, a lot of lower quality data points. For example, for indentation, if you don’t have a lot of experimental data points, you can supplement them with, sorry, you can supplement them with some simulations. And one of the innovations that is described in this paper is adding a residual connection to improve the neural network. So you will see some math here. So I’ll try to explain it really quickly. Multi fidelity uses some kind of linear function and a nonlinear function in combination. To learn both the linear and nonlinear relationships between the high and the low fidelity data. And what Lu lu describes here is this residual connection alpha-L Y-L, which in theory should make it easier to learn from data that might already be connected. So we’re going to compare this to Gaussian process regression which is a popular machine learning algorithm. It has been used since 2001 and multi fidelity models of Gaussian process regression have existed for a long while. So you can, we can call this the standard in multi fidelity machine learning. So in the work I have done is I have compared how I’ve tried to replicate the machine learning model proposed by Lu lu and compared it with traditional Gaussian processing. So here we see on when using simple simulation data. So this is from Fem2D and the high fidelity is Fem3D. In the orange, our multi fidelity model with the residual outperforms our multi fidelity Gaussian processing quite significantly. Now for any of you familiar with machine learning, you might think that the the learning curve is a bit flat. Usually you’ll see a curve similar to a downward slope like here. And the reason for this is because since this is strictly simulation data, it is really easy for a machine learning model to learn it. Think of it as a computer that’s spitting out data would, intuitively it would be easy for a computer to learn from it. And when measuring with mean average percent error, the residual does significantly better. With almost 10% MAPE. The MFGP gets around 90% MAPE. Now doing. Replicating these results on actual experimental data gives us some interesting figures. Here we have again in orange the multi fidelity model with the residual connection. And, and as you can see it does a lot better in lower data set sizes. So up until you get high fidelity data set size of 6, which I think is like 60 or 600, I think it’s 60, 60 high fidelity data points. Our residual connection does a lot better. But it evens out to be about the same. The traditional Gaussian processing regression does do a little bit better at 0.5% MAPE while the residual connection network plateaus at 1% MAPE. So from this we can learn that using a residual connection as proposed by Lu lu seems to hold promise for learning from low size data sets and low fidelity data sets. Now this is important because it could greatly reduce costs and, if you are running into problems with data collection, it is a useful thing to know. And for the future, future work will explore how physical data from indentations. Here we have a mark of an indentation and we can learn the indentation depth and the indentation width from it, how that could potentially relate to material properties such as creep. And this is relevant because this data is a lot less, it gives you a lot less information than if you would do like get data normally from nano-indentation tests. I would like to give a big thank you to Dr. Ali Beheshti and Shaheen Mahmood for supporting me in the lab, for Dr. Karen Lee and the OSCAR program for giving me the opportunity to do my research, and thank you for watching.

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.

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.

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

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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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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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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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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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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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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 Making and Creating OSCAR

Translating María Zambrano’s The Tomb of Antigone

Author(s): Grace Wood

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

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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 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.

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!

Making and Creating OSCAR

Collaboration and Community: The Rise of Collective Creativity in Contemporary Christian Music since 2020

Author(s): Evan Sites

Mentor(s): Jesse Guessford, OSCAR

Abstract

For the research portion of my capstone project, I will examined the noticeable increase in collaboration among Christian Contemporary Music (CCM) artists since 2020. The CCM industry has long thrived on collaboration, but in the years following 2020, the practice has grown in both frequency and visibility. Several factors, including the rise of digital distribution, the influence of streaming platforms, and changes in worship culture accelerated by the COVID-19 pandemic, have contributed to this growth. By studying these developments, I aim to gain a deeper understanding of how collaboration serves as both an artistic and strategic tool for CCM artists and its impact on the CCM industry as a whole.

Audio Transcript

0:01
Hi, my name is Evan Sites and I am a
0:05
senior here at George Mason University.
0:09
I am currently pursuing a degree in
0:12
music technology as well as minoring in
0:15
business.
0:17
For my capstone project this semester,
0:20
the research portion specifically,
0:23
I decided to look at the Christian
0:28
contemporary music industry.
0:32
Reason being is because that is a field
0:36
of
0:38
um music that I’m very passionate about
0:40
and that I enjoy
0:44
doing as well as listening to.
0:49
What I researched this semester was the
0:52
noticeable increase in collaboration
0:55
among CCM artists since 2020.
1:00
Now, the CCM industry has long thrived
1:03
on collaboration, but I believe that the
1:08
practice has grown in both frequency and
1:11
visibility.
1:13
I believe that three things contributed
1:16
to this increase of collaboration that
1:19
we see today. Number one, the rise of
1:22
digital distribution. Number two,
1:25
increased use of streaming platforms.
1:28
Number three, worship culture changes
1:31
accelerated by the CO 19 pandemic.
1:35
I believe that I have gained a deeper
1:37
understanding of how collaboration
1:39
serves as an artistic and strategic tool
1:43
for CCM artists as well as the CCM
1:46
industry as a whole.
1:50
For this research project, I
1:52
specifically looked at four different
1:54
case studies. I looked at um a album
1:59
that Maverick City Music came out with
2:01
um a couple years ago and this album it
2:05
just represents um inclusivity,
2:08
innovation and community within the
2:09
worship um industry.
2:14
Another case study that I looked at was
2:16
a song called The Blessing. And this
2:19
song is an example of what
2:24
a researcher said in his book regarding
2:27
how digital technology has reshaped
2:30
music making in the Christian context.
2:35
The third case study I looked at was an
2:38
album by Elevation Worship and Maverick
2:41
City Music called Old Church Basement.
2:44
This album achieved massive commercial
2:46
and spiritual success. According to the
2:49
Gospel Music Association, Old Church
2:51
Basement set a new world worldwide
2:55
record for the most first day streams
2:58
for a Christian and gospel album on
3:00
Apple Music. It also won multiple
3:03
Grammys that year. The last case study I
3:07
looked at was an album by Chris Tommen
3:09
entitled Chris Tomlin and Friends. This
3:12
was a cross genre collaboration album.
3:15
It features
3:17
um multiple artists from the pop scene
3:21
as well as some country artists. Um this
3:26
album is an example of what Emma Madden
3:29
highlights in her article uh published
3:33
by NPR that highlights the recent
3:36
collaboration between CCM artists and
3:38
secular pop artists. and she frames
3:42
these partnerships as signs of the
3:45
genre’s evolving cultural position.
3:50
The broader implications of this study
3:52
show that collaboration serves as both
3:54
an artistic and strategic tool for um
3:59
CCM artists.
4:01
I foresee that digital collaboration is
4:04
going to be the new model for creative
4:06
ministries based off of the research
4:09
that I read. um during this semester.
4:13
In conclusion,
4:15
since 2020, collaboration has become a
4:18
defining force in the Christian
4:19
contemporary music scene.
4:22
It unites artists and audiences through
4:25
shared faith and creativity.
4:29
Digital platforms have defined worship
4:32
as both um something in the local and
4:35
global context. And the future of CCM
4:40
lies in community-based creativity.
4:43
Thank you.

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

R

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.

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

Pain, Medication Use and Biomarker Associations in Individuals with Polycystic Ovary Syndrome (PCOS) : Insights from the All of Us Research Program

Author(s): Jannatul Nayeem

Mentor(s): Jenny Phan, CASSBI

A

Abstract

Background:
Polycystic Ovary Syndrome (PCOS) is a complex endocrine disorder often accompanied by chronic pain, yet the biological and social determinants of this pain remain underexplored. Understanding how stress-related biomarkers and healthcare access interact in shaping pain experiences may reveal mechanisms underlying health disparities in PCOS populations.

Objective:
This study examined associations between inflammatory and neuroendocrine biomarkers (C-reactive protein (CRP), cortisol, and body mass index (BMI)) and pain burden among individuals with PCOS, while exploring the moderating role of healthcare access and insurance coverage.

Methods:
Using data from the All of Us Research Program, 2,160 adults with PCOS (identified by ICD-9/10 codes) were analyzed. Pain burden was measured through pain-related diagnoses and pain medication dosage. Biomarker distributions were winsorized, log-transformed, and analyzed via multivariate regression models adjusting for age, race, socioeconomic status, and healthcare variables.

Results:
Pain burden alone was not significantly associated with higher CRP, cortisol, or BMI levels. However, healthcare access moderated these relationships: participants with greater barriers to care exhibited elevated inflammation and BMI with increasing pain, whereas those with adequate access showed flatter or reduced biomarker trends.

Conclusions:
Findings suggest that chronic pain and stress responses in PCOS may be shaped more by social and contextual factors than biological burden alone. Enhancing healthcare accessibility and equity could mitigate stress-related physiological outcomes and improve pain management for individuals with PCOS.

Audio Transcript

0:01 Hello, my name is Jannatul Nayeem. I am a student researcher with the B&LAB, um, at George Mason. I’m working directly with, um, Dr.
0:13 Jenny, um, in her our static load study. Which is the body’s biological stress response, and how it relates to menstrual disorders and chronic pain.
0:23 Um, from that study, I wanted to dive deeper into PCOS, and look at pain medication use and biomarker. Or associations and individuals with that disorder.
0:36 Umm, for methodology, I started off by using, umm, the all of us data set, uhh, database. Umm, it has a ton of data on- individuals, uhh, with all sorts of diseases and, umm, information from their doctor visits, umm, patient records, and also, umm, some survey questions that, the program itself asks
1:06 those participants, umm, and so through that, through that database, I was able to find what 2160 individuals with PCOS, and dive deeper into, uhh, their- biomarkers, uh, specifically for this, I’m using, umm, 3 biomarkers as predictors for inflammation and stress.
1:30 I’m using BMI, C-reactive protein, and cortisol. And then, umm, for- for their outcome variable, I use pain diagnosis along with their medication usage, umm, for medication usage, umm, I accounted for, umm, how many medications they’re taking.
1:52 And, and also what the dosage was for that medication, umm, and then some co-variates, such moderators that, sorry, some co-variates that I used was age, race, uhh, and SES index, and then for moderators, umm, I looked at healthcare access, uh, specifically insurance insurance status and access to care
2:19 . there. And so, I’m going to zoom into the results that I had, umm, hopefully in the video it resumes in two.
2:33 umm, but for my results, I found that, umm, pain alone didn’t start- we predict inflammation or stress, but limited access to care did.
2:45 Individuals with more barriers, such as lack of insurance, showed higher inflammation and BMI with pain, suggesting that health equity plays a critical role in PCOS pain.
2:56 Um, while my insurance data was limited, uh, because, uh, that not many people answered those questions, um, there’s still show some support that the idea- that stress biology and pain in PCOS are influenced by social environment and not just physiology.
3:22 Um, right now, I am continuing this study, um, to- or they’re deep in my understanding and advocate for equitable pain care in PCOS populations.
3:36 Umm, and so one thing I want to focus on more is, uh, imp- moving, um, how we, uh, state these questions, because I do feel like how the, uh, question is stated about access to care and insurance status is pretty sensitive.
3:58 So how can we go about it to, change the way, um, someone feels about answering those type of questions. Um, and so yeah, that was my study.
4:09 Thank you for listening.