College of Arts and Sciences Three Minute Thesis

2023 Participants

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Alexa Lambros

1st Place

The Role of Adversarial Allegiance in Atkins v. Virginia Cases

Atkins v. Virginia (2002) held that an intellectually disabled (ID) individual cannot be sentenced to death. The Atkins standard determines ID using three criteria: an IQ at or below 70, impaired adaptive functioning, and onset of disability before age 8. In these cases, current IQ is determined using one of various standardized intelligence tests, which have high interrater reliability in non-adversarial settings. However, the concept of adversarial allegiance suggests that even when using theoretically objective measures, evaluators may be inclined to reach conclusions supporting their retaining party. The current study examined the outcome of Atkins-eligible capital cases recorded in NexisUni to determine if different aspects of expert testimony in these cases were associated with adversarial allegiance. Prosecution experts reported higher average IQ scores, raised more concerns about malingering or low effort, and were more likely to testify that the defendant was not ID than defense experts, suggesting adversarial allegiance effects. The influence of adversarial allegiance could result in biased determinations of the presence or absence of ID in such capital cases. To reduce the possibility of adversarial allegiance, it may be necessary for Atkins evidentiary hearings to require neutral experts in place of adversarial experts. Other possible solutions include the formal adoption of best practice guidelines.

Praveer Tiwari

Physics and Astronomy

Equation of State Inside Neutron Stars

Neutron stars are one of the densest objects in the sky. It stores more mass than the sun's mass within a radius roughly equal to the distance between Pullman and Moscow. This makes it a unique laboratory to study the interaction between basic particles of nature under extreme pressure. The composition of these stars varies as we go close to their center and some regions are dominated heavily by neutrons. Researchers are still unsure about the exact composition of the interior regions and are developing theories to explain the observations. We are at the crossroads of multi-messenger astronomy and neutron stars are right at the center of it. Astrophysical observations from gravitational waves from colliding neutron stars by LIGO collaboration are corroborated by signals in the electromagnetic region. This is the essence of multi-messenger astronomy. These observations should be consistently combined with advances in earth-based experiments and quantum mechanical calculations to develop a coherent picture of neutron star interiors. This is where my research comes in. I use machine learning and Bayesian statistics to develop models and frameworks that take the uncertainties from experimental observations and theoretical calculations and combine them with those of astrophysical observations to constrain the mass and the radius of neutron stars. This in turn helps us unravel the secrets of neutron star interiors.

Paula Kimmerling

Mathematics and Statistics
People's Choice

Quantum Walks on Dutch Windmill Graphs

The computers we know today are so advanced that we can hold them in our hand, and they handle a staggering variety of problems efficiently. We must imagine quantum computers as being at the evolutionary stage of computers from the 1950’s. The hardware is still small-scale and the problems a quantum computer can tackle are limited, but the promise remains that just as classical computers began to outpace humans, quantum computers can outpace classical ones on certain problems. We must determine which mathematical structures are most ideal for transferring information in a quantum computer.

Behind both the physics and computer science needed to implement quantum computers, there is mathematics: studying the behavior of matrices and structures called “graphs” which govern how the quantum computer will evolve over time when we press “start”. Quantum computers are also probabilistic in nature, requiring thousands of repeated computations to say with a given confidence that an answer is likely correct. One could ask, “what is the average probability that information transfer will occur between two nodes?”

Our work builds on [1] but focuses on the long-term behavior of a new set of graphs. After generating data -- averaged probability matrices -- and proving conjectures about properties of those matrices, we can conclude which graphs are better at keeping information localized and which structures are better at transferring information some distance to other nodes.

[1] Coutinho, G. et. al. (2018) “A New Perspective on the Average Mixing Matrix”, The Electronic Journal of Combinatorics 25(4).

Yin Ru Chen

School of Politics, Philosophy, and Public Affairs

Gender Mainstreaming in Taiwan

Gender Mainstreaming (GM) has been implemented in Taiwan for over 15 years. Nevertheless, although feminists once believed that gender equality could be greatly improved if the government adopted GM, the program results lacked examination, and the impacts did not reach feminists’ expectations. This research examines program design and program outcomes and finds that GM has not been defined and designed properly. These issues further led to outcomes and impacts that were not as expected. The possible causes are stakeholder unfamiliarity with GM and the political-cultural context.

The stakeholders involved in the GM program design did not clearly define critical concepts for program implementation and identified a workable program rationale. Furthermore, Since Taiwan is a newly democratized country and the democratization is compressed, the government’s mindset cannot catch up with the dramatic institutional changes. While Taiwan has long been infiltrated with Confucianism, hierarchical and patriarchal thoughts have dominated the society. In addition, since Taiwan was newly democratized, it could be expected it would take time to change the authoritative context within the government. In conclusion, it was hard for the government to design an efficient program because of the lack of knowledge about GM and the unsupported cultural and political context.

Azdren Coma


Exploring the Dimensions of Support for Climate Mitigation and Adaptation

Climate change affects us all, but marginalized communities are more greatly impacted. Mitigation focuses on reducing emissions and getting more attention and funding, while adaptation seeks to minimize the impacts of climate change and typically focuses on equity for marginalized groups. Political ideology and orientation is the strongest predictor of support for climate mitigation. Democrats' support for mitigation efforts is generally high, whereas Republicans largely show less support. Republicans are, however, generally more supportive of climate adaptation efforts on par with Democrats. This project examines support for mitigation and adaptation through a survey and an experiment.

Evelien Deelen


Illness, Animals, and Reading Minds

Many human diseases originate in animals, and transfer to us through human-animal contact. These zoonotic diseases have devastating effects on human life, both at the local and global level. At the same time animals are extremely important for human existence. Worldwide there are over 300 million working animals, over a billion pets, and over 80 billion food animals. We cannot simply eliminate them all to avoid disease risk, or prohibit people from interacting with them. So what can we do to prevent the next pandemic?

The answer lies in people’s minds. My dissertation is about understanding how animal owners and caretakers determine if an animal is sick, and if, when, and how they should provide treatment. Their first response (or lack thereof) has the potential to heal, shorten, or worsen animal sickness, and as a result, prevent or promote disease outbreak and spillover into human lives. However, what it means to people, for an animal to be sick, is extremely subjective.

People’s perceptions of sickness depend on their subjective understandings of what it means to be healthy, and what they consider deviations from this norm. These understandings are different all around the world, because they are patterned by cultural norms, beliefs, and practices. How people interpret and respond to disease is cultural, rather than universal. What it means to people to be a healthy human or animal in one culture, may be completely different in another.

This is where my project comes in. I have developed a set of methods to, metaphorically speaking, get into the minds of animal caretakers, and systematically record and analyze their cultural beliefs. Understanding people’s subjective views of animal illness; the steps they take to address it; and the reasons guiding their actions, allows us to offer appropriate help in ways that fit, rather than collide, with people’s worldviews. This culturally sensitive approach, I believe, is the key to prevent future pandemics, and to ensure a healthier future for humans and animals alike.

Md Mahedi Hasan

Mathematics and Statistics

Change Point Detection on a Dynamic Network Using RDPG

Network data is frequently used in real-world applications like the power grid network, the climate network, cyber security, etc. Any sudden or unusual changes on these networks often indicate a potential risk or systemic dysfunction. For quick action and decision-making, it is essential to identify these changes as soon as they occur by managing the likelihood of false alarms in the network. I'm creating an algorithm for my Ph.D. that will enable me to identify those odd changes in network systems as soon as they occur. Our technique is more accurate and computationally faster at detecting any changes in the network system than the current approaches. Additionally, our approach can be applied to other fields where data originates from networks or graphs, such as drug development studies, gene interaction networks, etc.

Amanda Hussein

School of Languages, Cultures, and Race

Memory in the Master’s House

Museums and monuments in combination with certain genres of literature and film exist as public narratives. History and memory form two public narratives of monuments and certain genres of literature and film. Each piece possesses a history of how/why the author created it. In addition, each piece memorializes something or someone, perhaps even a concept itself. The greater questions associated with history and memory are: Whose history? Whose memory? Who narrates? Who is included and excluded? Who chooses which history and memory are included? What does this mean regarding value and importance? The purpose of this analytical paper using historical narrative and memory is to examine race and gender of how selected museums and monuments/literature and film, in the Dominican Republic and the United States, function as symbols of “colonized consciousness”, acts of resistance, or both. By using this analysis, an important and crucial discussion will examine the formation of race, gender, and national perspective. The subsequent implications will inform the value/nonvalue and importance/nonimportance of minorities within historical narrative.

Arpita Sinha


The Glamorous Working Body: Fashion Modeling in India

My research critically examines modeling labor to assess the position of female fashion models (henceforth, models) as workers in the Indian fashion industry through issues such as industrial structure, working conditions, and health & hygiene. Contrary to popular perceptions, modeling in India (as is the case in many other countries), is a highly precarious job with questionable working conditions and volatile income, systemic industry-wide issues which have been exacerbated by the COVID-19 pandemic. Models, like actors and athletes, quite literally make their bodies the medium of their work. The centrality of the body to the profession necessitates that to understand modeling labor one must account for the body as something that has to be trained, groomed, maintained, and disciplined. My analyses will show how the more models self-regulate and self-monitor their bodies and identities vis-à-vis the ideals of the industry, the more they are rewarded.

This research aims to critically understand how essential factors such as gender, labor, health, and job sustainability constitute the precarious professional and personal existence of female fashion models in India. This is a novel locale of research with a hitherto unexplored research focus and will thus be a significant contribution to the current body of scholarship in the area.