Building and Documenting a Reproducible Low-Cost Open-Source Optical See-Through AR Headset for Computing Education (Work in Progress)

Students in introductory computer science courses often struggle to understand how algorithms and data structures evolve over time, as traditional flat-screen visualizations require learners to mentally track abstract state changes, limiting spatial and embodied engagement. Augmented reality (AR) offers a promising way to make these processes visible and interactive, yet existing optical see-through head-mounted displays are often too costly for widespread classroom adoption.

To address this barrier, this project focuses on building and systematically documenting a low-cost, open-source optical see-through AR headset for computing education. Inspired by Project North Star, we adapt and refine an existing open-source design with an emphasis on accessibility, reproducibility, and classroom deployment. The system incorporates modular 3D-printed structural components, commodity micro-displays and driver boards, and a repeatable optics calibration workflow based on checkerboard alignment patterns to correct distortion and misalignment.

A working hardware prototype has been constructed, and we will share detailed documentation including a reproducible bill of materials, wiring diagrams, 3D-printable models, and step-by-step assembly and calibration procedures. The calibration workflow includes representative results and troubleshooting guidance to support replication. While interactive AR software is still under development, this work establishes a transparent and replicable foundation that lowers financial and technical barriers for educators seeking to adopt optical see-through AR systems in computing classrooms.

Continue reading Ben Khant »

Plexa: Empowered AI Education

AI in education is a hot topic, and for good reason. Professors and Universities are searching for the answers of how they can prepare their students for the future, but the tools available do not provide for their needs. Existing tools fall short in at least one of a few key ways: They are not pedagogically forward, they do not respect data provenance, they are expensive and opaque. Plexa provides educators with the ability to create highly customizable lesson plans for their students to use in a controlled environment, so that they may promote AI literacy and prepare their students for careers in specific disciplines and lives in the age of AI. Chats are restricted to lesson instances; no free form chats. This structure encourages accountable usage, and keeps the focus of the tool on pedagogy. The tool is local first: all data is stored on premise, with the ability to run models within the institution’s network, or outsource compute to any provider of their choice. Plexa will always be fully free, open-source, and permission-less-ly licensed so institutions can examine/modify the code and deploy their own versions without any license related headaches or paying a cent. With this framework, I present a new way forward for what AI education can look like.

Continue reading Kellan Guinn-Bailey »

Talking AI and Talking Money
From your homework to stock picks, AI search engines can do it all. In Q3 of 2025 alone, the proportion of S&P 500 firms discussing AI during earnings calls was 62%! Regardless of industry, AI will be affecting how a business operates and functions. At the same time, managers are grappling with different views on AI, ranging from optimism to concern. In this project, we analyze corporate disclosures by reading extractions of AI discussions and classifying these extractions into costs and benefits of AI. In our findings, positive AI-related keywords tend to emphasize growth and potential—such as opportunities, expansion, and innovation—whereas negative sentiment toward AI is more often associated with words like bias, concerns, and infringement. Next, we generate textual rules that extract costs and benefits of AI from 10-Ks, 10-Qs and earnings calls and calculate AI sentiment scores for each firm. Finally, we examine the trends of the AI sentiment across time and different sectors.

Continue reading Zoey Zeng »

Establishing the Effectiveness of the OpenBCI EEG System in Identifying Physiological Markers of Healthy Brains

Parkinson disease (PD) is the second most common neurodegenerative disorder in the United States, affecting 1.1 million people. However, ~20% of PD patients are misdiagnosed because diagnosis often relies on subjective motor assessments by doctors. Electroencephalography (EEG) is a non-invasive, accessible tool that records neural activity using electrodes placed on the scalp, and can be used to improve diagnostics with objective neural biomarkers of PD. The cognitive neuromodulation lab bought the OpenBCI EEG system last spring, and this project sought to identify the reliability of the system. Three experiments were conducted with healthy volunteers. The data for each experiment was preprocessed using EEGLAB to isolate neural data from electrical noise. Then, MATLAB’s signal processing toolbox was used to extract the neural features. The first two experiments looked for robust neurological biomarkers of health data identified with more advanced EEG systems. With subjects alternating between eyes open and eyes closed states in the first experiment and performing thirty trials of finger tapping in the second experiment, two nonmotor biomarkers and one motor biomarker were successfully identified. The third experiment had patients perform finger tapping and spiral drawing, bilaterally, replicating motor tasks in PD assessments. With this data, three biomarkers known to differ between PD and healthy subjects were identified in this healthy cohort, consistent with the data in the literature. Having identified these biomarkers, the reliability of the OpenBCI system is verified and a comparative study between healthy subjects and PD patients will be conducted to identify novel PD biomarkers.

Continue reading Quinn Smith »

Historical Gradient of Host-Pathogen Dual Transcriptomics in White Nose Syndrome
White Nose Syndrome (WNS) is a cutaneous fungal disease caused by the fungus Pseudogymnoascus destructans (Pd) . Since its arrival in 2006, WNS has spread rapidly across North America (NA), resulting in mass mortality in hibernating bats and threatening extinction in some species. These findings aim to provide insight into how Pd pathogenesis changes over time to identify potential targets for the prevention and treatment of WNS.

Continue reading Sophia Perkins »

Unlocking Potential: The Case for Crypto Assets in the U.S. College Endowment Funds

Since 2017, crypto assets have emerged as a prominent and transformative financial
instrument globally. While major financial institutions such as BlackRock, Fidelity, and Franklin
Templeton have widely adopted these digital assets and legislation surrounding crypto holdings
has become increasingly clear, college endowment funds have remained hesitant to embrace
them. Known for their traditionally conservative investment strategies, most endowment funds
have yet to integrate crypto assets into their portfolios. To date, only a few prominent
institutions, such as Ivy League schools and Emory University, have included crypto assets in
their treasuries or invested in crypto projects as private equity.
However, this cautious approach began to shift in 2025, as endowment funds started to
seriously explore the potential of crypto assets. With their capacity to deliver high returns,
mitigate risks inherent in traditional markets, and diversify investment portfolios, crypto assets
align closely with the strategic goals of endowment funds. These goals include fostering
intergenerational equity and engaging with younger generations.
This paper will analyze the current state of college endowment fund assets, including key
investment considerations such as Environmental, Social, and Governance (ESG) factors,
propose diverse strategies for integrating crypto assets, and highlight the potential benefits of
incorporating digital assets into college endowment fund portfolios.

Continue reading William Le »

Comparing Functional and Anatomical Division of the Subthalamic Nucleus as a Predictor of Clinical Outcomes in Deep Brain Stimulation

The subthalamic nucleus (STN) is one of the most common targets for deep brain stimulation (DBS), a treatment for alleviating the motor symptoms of Parkinson disease (PD). DBS involves implanting electrodes into the STN to deliver electrical stimulation, with the goal of reducing motor symptoms and improving quality of life for patients with PD. However, its success strongly depends on where within the STN the stimulation occurs. This study aims to determine which segmentation method more closely correlates with motor symptom improvement in DBS.

40 PD patients who previously underwent bilateral STN DBS were included for analysis. Outcomes were measured as percentage improvement across rigidity, tremor, bradykinesia, and overall motor symptom. Anatomical segmentation was performed by dividing each STN into six regions using its center of mass as a reference point. Functional segmentation was derived using the Accolla atlas, which labels the STN into motor, associative, and limbic zones. The atlas was registered to each STN and then the volume of tissue activation relative to the total volume of the STN was calculated to quantify stimulation.

Results showed that functional motor zone activation weakly correlated with rigidity improvement, while other functional zones showed no significant associations. In contrast, anatomical dorsal STN stimulation significantly correlated with rigidity and distinguished responder groups. The dorsal anatomical region demonstrated stronger clinical relevance.

Continue reading Deana Marchuk »

Development of a Laboratory Methodology to Manufacture Tailings
Recent failures of tailings storage facilities have demanded a greater understanding of the behavior of tailings. However, characterization of tailings properties can be challenging due to limited access to representative samples. Hence, this study aimed to develop a methodology to recreate tailings in the laboratory that reproduce field characteristics. To accomplish this goal, we performed self-learning on the topic, laboratory investigation, and analysis of the samples created. Various geotechnical and mechanical properties of soils were studied to gain an understanding of the properties that would be tested and examined. Material characterization, sample preparation, and sample testing standards were reviewed and then applied to Ottawa sand and bentonite clay. These standard materials are accessible and readily available for laboratory use, which would allow for easy replication of the methodology created. Additionally, these materials have characteristics, for example, plasticity and shear strength, that, when mixed, would resemble field tailings. As a result of the work, a preliminary observation is that Ottawa sand has a large grain size and may not be the appropriate material for the final tailings sample, as tailings usually have a very fine grain size. Further research showed that it is possible to obtain silt-sized soils by crushing Ottawa sand, which would allow us to make a sample that is similar to field tailings and still maintains other tailings properties. Future research includes investigation of the silt-sized soil and bentonite clay mixtures to find the proper ratio of these materials to recreate tailings and then their strength properties.

Continue reading Olivia Janas »

Nutrient Loading Reduction Capability in Aged Green Roofs

As climate change accelerates, intense rain events have been persistent, damaging communities in unprecedented ways. Green roofs are a type of sustainable infrastructure that has been implemented on top of modern buildings to mitigate the effects of climate change. However, the presence of nutrients important to plant life, such as nitrogen and phosphorus, in stormwater runoff can deeply damage nearby waterways through eutrophication. This research focuses on the capabilities of the four green roof test plots atop Academic East to reduce stormwater volume, how the green roof may affect nutrient loading in stormwater runoff, and how changing plant cover may affect these parameters. To do this, the green roof testing lab found in Academic East was restored and redesigned for side-by-side analysis of the test plots. Although the project could not be fully completed in one summer, it was found that the restored green roof, with no additional changes, considerably reduced stormwater volume, peak flow rate, and ammonium mass loading for one large storm event. For this same storm event, nitrate and phosphate mass loading in the runoff appeared to increase. In the future, more research focusing on the effects of changing plant cover plans needs to be done.

Continue reading Gabriella Santos Meltzer »

Environmental Degradation and Food Systems in Ghana: Gold Mining & Synthetic Pesticides

This research examines the relationship between environmental degradation and food systems in Ghana. While existing studies explore the effects of gold mining on farmers (Gilbert and Albert 2016; Agariga 2021; Kwang and Blagogie 2025), little attention has been given to how these impacts extend to market vendors and transporters. Even fewer studies analyze food and land through a sociocultural lens. My research addresses these gaps by asking: How do environmental degradation practices—specifically gold mining and chemical use—affect food production, distribution, and security in Ghana? And how does the decline of arable land reshape cultural food identity (Parasecoli 2014)? To explore these questions, I used qualitative interviews, policy analysis, and a review of existing scholarship. Over three months, I conducted 35 semi-structured interviews (20–60 minutes each) with small-scale farmers, cash crop farmers, and market vendors in Cape Coast, Agona, Kumasi, Obuasi, Busia, Tarkwa, Ho, and Mankessim. This approach centered local perspectives while capturing the broader structural context (Gyan and Mfoafo-M’Carthy 2021; Thow et al. 2021; Ahmed et al. 2021). Findings indicate that while mining has long been part of Ghanaian society, its mechanization under British colonial rule intensified environmental harm, disrupting food production and distribution and deepening food insecurity. Those in lower economic tiers—farmers, Indigenous miners, and non-mining community members—bear the greatest burdens. Chemical use reflects unequal access to quality inputs and pressures to maximize cash crop yields, degrading land and risking health. Participants also expressed concern over cultural loss as farmland diminishes, though some resist by revitalizing traditional agricultural practices.

Continue reading Da’Mirah Vinson »