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Our next fall deadline is October 15, 2023 11:59pm PT. Apply today to lock in your spot!

10-session deep dive into a research topic of your choice

6-week research project with an expert and peers who share your passion

A career discovery experience with 3 expert mentors in your chosen fields

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First I will introduce the subject matter, which is transactional tax. This tax is implemented through houses of transactions and takes 0.2% of the value of the transaction. Then I will hypothesize the effects of the tax on each relevant sector of the monetary economy. There are four major sectors of the economy with sub sectors within. At the end of discussing each sector, I will conclude the paragraph with my predicted effect of the transaction tax. During this, high-frequency trading will especially be scrutinized as I predict it will be the only specific element of the economy that will be heavily impacted by such a tax, as its very model is dependent on minimal profit. Note to add impacts on stability and the graph. After that, I will highlight the effects of the tax in the real world and economy; specifically the people, businesses, banks, and country. The people would benefit greatly from this tax change. Businesses would largely benefit as well unless involved in a major supply chain, which I will highlight. Banks would be very against it, as their business is centered around transactions. The country, as in the fed and government, would appreciate the tax greatly. Feasibility is also a big issue, as I predict many banks would be extremely against such a major tax reform. I will cite past changes and the amount of influence banks have in today’s world. I will also acknowledge that this tax is not entirely predictable, like all other reforms. Use chaos theory and other “laws” that have to do with predictions. Finally, I will conclude by highlighting the potential this tax has to reshape our society.

Economics, Statistics, Data Science, Natural Language Processing, Labor Economics, Industrial Organization, Antitrust, Economics of Education,  AI/ML, Text Analysis, Macroeconomics

How does a 0.2% payment tax affect individual sectors of the monetary economy?

Law, Economics (and the intersections thereof); Intellectual Property

Climate change is important
Schools consume electricity and heating in an unique way 
I.e. students inhabit during the day, not over summer
Heating and cooling accounts for 50% of energy used in schools
Schools consume x% of nationwide electricity
Electricity contributes to x% of global/national emissions
Decarbonizing schools is a good proxy for determining how best to decarbonize the world
In this study, we investigate how to decarbonize both electricity and heating/cooling.
For electricity, we consider a solar + storage plant and determine the cost of such  a system for meeting 100% of demand, as well as lower percentages.
For heating/cooling, we consider various technologies including heat pumps, electric furnaces, NG boilers, geothermal, and solar thermal.
Based on our analysis, we identified the proper size of a solar + storage plant, and decided on optimal heating/cooling technology to minimize costs while meeting demand, and eliminating carbon emissions.
These results are important for medium-scale buildings such as schools, as well as serving as a proxy for larger decarbonization efforts.
Broader perspectives: given the large contributions of electricity and heating to CO2 emissions, this work helps identify pathways to reduce emissions in a cost-effective way.


Renewable energy (solar), heat transfer, computational materials science

How can we decarbonize a school?

The student is working to improve marketing and growth strategies for a startup selling automatic faucets. 

Entrepreneurship, Startups, Venture Capital, Business, Project Management, Neurobiology. I will coach you on creating a pitch deck for your startup idea and will connect you to funding opportunities in my network.

Developing Growth Strategies for Startup 

Facial asymmetry is a superficial aspect of human appearance with complex origins. This literature review examines and evaluates the most significant causes of facial asymmetry—from genetics to lifestyle and the aging process. Although these factors are intricately interrelated, lifestyle and environmental factors affect the development of the facial asymmetry more than genetics. Lifestyle habits alter originally genetically symmetric faces or contribute further to genetically asymmetric faces. Despite not pertaining fully to neither genes nor environment, aging also affects facial asymmetry. Although facial asymmetry seems solely external, it is important to study facial asymmetry because it may have far-reaching implications that can be utilized practically. It is known to influence interpersonal and societal treatment, due to the conflation of facial symmetry and attractiveness and thereby better treatment. It could also result in interesting uses in health care and diagnoses because of its potential indications on health and well-being, yet it requires further research.

Neuroscience, Neurodegenerative diseases, Psychology, Cancer biology, Cancer therapeutics, Cellular & Molecular Biology, Scientific communication

What are the Causes, Implications, and Uses of Facial Asymmetry?

This research aims to investigate the environmental impact of using drones for delivery services compared to traditional delivery methods. With the increasing demand for faster and more efficient delivery services, there has been a growing interest in using drones as an alternative means of delivery. However, the environmental impact of using drones for delivery remains largely unexplored. This study will compare the environmental impact of using drones for delivery to traditional delivery methods, considering factors such as carbon emissions, energy consumption, and noise pollution. Furthermore, the study will explore how the use of drones for delivery can be optimized to minimize their negative environmental effects, such as through the use of renewable energy sources, optimizing flight paths, and reducing the weight of cargo. The findings of this study will provide insights into the potential environmental benefits and challenges of using drones for delivery and offer recommendations for optimizing their use to reduce their environmental impact.

user-oriented design, 3D modeling, electric vehicles (e.g. drones, e-boards/bikes), robotics and applied computer science (e.g. IOS apps)

What is the environmental impact of using drones for delivery services compared to traditional delivery methods, and how can the use of drones be optimized to minimize their negative environmental effects?

Neutron-rich isotopes are extremely important for the improved understanding of nuclear structure and reactions. The neutron drip line has currently not been probed past a proton number of 8, and knowledge of where it lies helps answer the question of what combinations of nucleons can form a nucleus. Neutron-rich nuclei form exotic structures such as neutron skins and halos, and are not accurately described by current models such as the shell model. The improvement of current models and development of new models for describing the behavior of neutron-rich nuclei is essential for the field of nuclear physics.

How are nuclei organized?
What nucleon combinations can form a bound nucleus?

Nuclear physics, nuclear astrophysics, particle physics, compact objects (neutron stars, black holes etc), data analytics, AI/ML

Rare Isotopes, Heavy Elements, & the Boundaries of Nuclear Physics

This research paper aims to examine the factors influencing girls' enrollment rates in rural Karnataka, South India. This study begins by providing a comprehensive understanding of the historical context and the evolution of the problem to the present day. This paper explores the reasons behind the persistent lower enrollment rates for girls, including household chores, child marriage, parental expectations, and poverty. This paper then discusses the initiatives undertaken by the government and civil society to address this issue and evaluates their involvement. The paper then concludes by highlighting the importance of girls' education for society’s development and overall well-being. 


French and Francophone Studies, International Relations, Politics, and French Language

 Examining the Underlying Factors Contributing to Low Girls' Enrollment in Rural Karnataka, India

This project is focused on the four major types of leukemia and what treatments we use, as well as the future of research in this field. Understanding leukemia requires a breakdown of blood cell lineage and immune system function, particularly white blood cells. Leukemia is driven when the production of these cells in bone marrow goes awry. We use a whole arsenal of treatments for leukemia, from standard chemotherapy and radiation to newer adaptive immunotherapies. Leukemia is also uniquely suited to bone marrow transplant as a curative measure, which is a form of stem cell therapy. Finally, we will be looking into where the research is taking us, and what the prognosis may look like in 10, 20, or 50 years.

Medicine, Neuroscience, Drugs & Pharmacology, Chronic Pain, Cellular Molecular Biology

Current Treatments and Future Directions in Leukemia

With the recent release of the public CARMENES radial velocity (RV) datasets, and the ongoing downlinking of TESS photometry, known exoplanets can be more precisely characterized. Here, we analyze six exoplanets across three stellar systems using unpublished data from the aforementioned surveys  to gain a deeper understanding of the planets' physical properties. By incorporating new RVs over a long baseline, as well as additional high-precision photometry, we can recover all six planets, constrain their orbital parameters, and provide insight into the potential for habitability on each of these worlds, as well as round out the individual system architectures. We also offer a more informed estimation for which planets will be valuable for future atmospheric follow-up observations.

Astrophysics, Astronomy, Exoplanets, Python programming

What factors determine the habitability of exoplanets and how can we assess their potential to support life?

This comprehensive study aims to understand the gut-brain axis, elucidating its critical role in various physiological functions, including absorption, immunity, and homeostasis, and its relation to neurocognitive dysregulation. We reveal how gut physiology serves as a vital feedback system, with disruptions potentially leading to adverse effects on neural and mood phenotypes, including psychological dysregulation. This research provides a deeper understanding of the intertwined nature of the gut microbiome and cognitive function, exposing an extraordinary level of interconnectivity across human physiological systems and its implications for cognition. Notably, it underscores potential common genetic underpinnings between gastrointestinal and psychiatric disorders, indicating a link between poor gut health and mental disorders such as anxiety, depression, and cognitive decline. Our findings highlight the critical role that the structural and functional characteristics of the gastrointestinal tract play in maintaining mental well-being. Specifically, we focused on the impact of alterations due to Helicobacter Pylori, celiac disease, and short gut syndrome. These insights highlight the importance of advancing our knowledge of the gut-brain axis and the need for future research. This includes exploring the effects of diet on gut health, developing innovative treatment strategies, and investigating the potential of emerging technologies in the pursuit of more effective and personalized interventions for these complex conditions. We hope such endeavors will significantly enhance the quality of life for individuals affected by these conditions and promote overall mental well-being.

Neuroscience, Neuroanatomy, Microbiology, Cellular Biology, Genetics and Genomics, Cancer Biology, Medicine

Deconvoluting the Gut-Mind Interactome: How Structural and Functional Disruptions to the Gastrointestinal Tract Seed Neurocognitive Dysregulation

The student will be writing a review paper as well as creating her own website on her research. The paper will discuss how childhood experiences with weather influences perceptions of weather. Importantly, perceptions of weather play a critical role in the pathway between objective weather conditions and behavior. In addition to reviewing this literature in her paper and proposing future directions, Renata will create an interactive website for visitors to examine their own perceptions of weather and how it might impact their behavior. This is a “real world” application of this research, which is a very exciting direction!

social psychology, person perception, inequality, socioeconomic status, social network analysis, text analysis, mental health, well-being,

Impact of perceptions of weather on weather experience and wellbeing consequences

We are creating an algorithm to parse and clean data from XML 990 forms provided by the IRS. Once we group data tags into categories that reflect the charities performance, we can observe the trends that are present when charities are acting suspiciously. We don't know what we will find for sure yet, but until we are able to use logical deductions to find trends, there is no way to say for sure whether or not there are correlations between 990 form changes and suspicion levels. We first need to analyze the percent changes of various categories year by year.

Analytics, Data Science, AI, Machine Learning, Economics, Econometrics, Business, Statistical Programming, Geospatial Analytics

How to group charity ledgers based on suspicion by training data from public 990 forms.

This essay investigates the relation between ideology and aesthetics in two WWII films, made pre and post-9/11. This essay will also discuss how video games and films systematically desensitize consumers to the suffering of both allied and enemy soldiers, culminating in a modern world where war is seen as periodic and constant. Finally, the essay will link depictions of enemy combatants to the othering of the non-white, non-american people.

Comparative Literature; Film Studies; Literary Analysis; Cultural Studies; Francophone, Anglophone and Arabophone Literature & Cinema; Postcolonial Theory

The depiction of WW2 in Pre and Post-9/11 Media

One in every one hundred children are diagnosed with Autism Spectrum
Disorder (ASD) and since its discovery, in 1911, scientists have been trying to acquire
more information in order to help those with this developmental disorder.

This article analyzes and reviews different neuroimaging modalities
(fMRI) that can help identify trends in patients diagnosed with ASD. Through
analyzing images, multiple case studies, and reviewing new technologies that can help improve treatment and diagnosis.

We also elaborates on how genetics and environmental factors can
play a role in how ASD can be treated and viewed through a societal aspect. While many improvements have been made in order to bring more awareness of this disorder, and this article elaborates on the progression of how Autism is; diagnosed, treated, and viewed.

Neuroscience, neuroimaging, signal processing, data science

Literature

In Divya's project, she will focus on utilizing several different datasets to better understand how the effects of global climate change on humans. In one dataset, she will first understand the impact of global climate change on food scarcity. To do this, she will understand how the different environmental changes due to global climate change such as temperature affects crop growth and how this may affect the future of agriculture. In another dataset, she will continue to explore the projections of these temperature and weather changes to better anticipate these changes and research ways to either circumvent these changes and/or prepare for these changes. By completing this project, Divya will increase our holistic knowledge of the impacts of global climate change and advocate for the need for action.  

Machine learning for clinical applications, Protein engineering, Immunoengineering, Cancer immunotherapy, Medicine, Biology, Computer Science

Using machine learning to understand the effects and prepare for global climate change

Angelica is working on a literature review and survey describing menstrual irregularity in female athletes. She is reading about biological, environmental, and mental health factors which effect menstrual cycle patterns. She is also surveying women aged 14-30 about their experiences with menstruation and exercise. She is interested in awareness of menstrual irregularity among this population.

Anthropology, Medicine, Social Science, Qualitative Research, Ethics

Menstrual Irregularity in Female Athletes

The spy balloon that flew across the U.S. in February 2023, posed a serious security threat. US intelligence officials have said this balloon tried to gather intelligence by monitoring sensitive military sites and as a result the U.S. government began more closely scrutinizing its airspace to better categorize aerial objects and detect threats. However, the airspace is filled with a myriad of aerial objects, making the problem of classifying and risk determination very challenging. The purpose of this research is to develop a machine learning model to classify an aerial object based on the threat they pose. Currently, there are no known single datasets that contain both old and newer aerial objects such as drones, planes etc, nor datasets have labels to associate  risk of the objects. The goal of this project is twofold: 1) We create a new comprehensive dataset that contains traditional & newer aerial objects. We label the objects into high, medium, low and no risk based on the threat markers on the aerial objects. 2) We use MobileNetV2 CNN classification algorithm to validate the dataset and provide accuracy results. Advancements in this space can potentially help intelligence agencies and security analysts to quickly assess developing scenarios and provide a reliable risk for observed aerial objects.

Social Sciences, Computational Social Sciences, Social Media, Graph Analysis, Depression on Social Media, Cyberbullying on Social Media, Hate Speech and Fake News Detection, Digital Epidemiology, Natural Language Processing, Artificial Intelligence, Machine Learning, Data Science, Threat Intelligence, Internet Security, Denial of Service Attacks, Network Traffic Analysis, Computer Science, Computer Networks

Threats Detection in Aerial Objects: A Machine Learning Approach

The dramatic increase in quality of natural language generation from large language models, popularized by ChatGPT, has made many wonder about statistical differences between naturally generated and artificially generated text. To constrain our problem, we considered fairy tales as these texts have existed for centuries. To explore statistical differences, we focused on the distribution of words according to their parts of speech. We generated a novel corpus of 101 fairy tales “authored” by ChatGPT. We compared this against 209 fairytales written by the Grimm Brothers and made available freely online. We performed appropriate preprocessing and computed total variation distances for individual fairytales within and between authorship conditions. We found out that in fact, the distribution of parts of speech in ChatGPT fairy tales is significantly different from the distribution of parts of speech in Grimm fairy tales.

data science, computer science, computational linguistics, natural language processing, web scraping (Twitter) and analytics, probability theory, statistics, calculus

Part of Speech Distributions for Grimm Versus Artificially Generated Fairy Tales

The United States is one of the largest consumers of energy in the world, but this energy comes from a wide variety of sources. In addition, this energy consumption varies from state-to-state and from sector-to-sector, meaning that no one model would tell us the full story of the energy distribution in the United States. The goal of this project was to analyze this data, using various techniques to develop our understanding of the nature of the data we were provided with. To effectively analyze the data, we created three groups of data: individual energy sources, energy by state, and energy by sector. Our analysis showed us that energy sources, like coal, appeared to be decreasing in consumption, that states could be grouped in clusters in order to predict production of coal from consumption (coal was the main energy source we analyzed), and that other aspects of the energy distribution (consumption and expenditure, for example) were almost perfectly correlated.

Analyzing the Distribution of Energy Sources in the United States

The number of sunspots in a given year changes as the sun goes through solar cycles, with peaks happening at regular intervals. When these peaks are plotted, a curve appears, similar to the oscillating sinusoidal wave. Because of its oscillatory nature, predictions of future sunspot values could be found since it is safe to assume that the number of sunspots would always follow a pattern. However, a simple, ordinary sine function, or any algebraic function for that matter, would not allow us to plot and predict future data points due to the complexity of the curve at hand. This led us to the hypothesis that in order to predict the future number of sunspots, models that involve autoregressive and moving average components (namely the ARIMA model) would be the most effective. In order to measure effectiveness, the mean-squared error (MSE) would be used, with a lower value (closer to 0) meaning better fit. The reason why we chose these sophisticated models was because these models took into account prior data points and their trends and seasonality to predict future data points. This essentially meant that this model would predict based on prior points, not on a fixed point or equation, like the sine curve. After plotting all of these models and finding the MSE for each, we drew the conclusion that the ARIMA model proved to produce the most accurate curve, with a MSE of only 460, as compared to the MSE that the best sine curve could produce: 21 million.

Predicting the Number of Sunspots Per Month and Per Quarter Using ARIMA Models

Even though all viruses seem to be very
similar to each other, they have many differences that set them apart and place
them into different categories. This research paper will focus on the viruses that
affect bacteria, animals, and plants. Before diving into the effects on humans, the
review paper will give a small overview of animal, bacterial, and plant viruses. The
paragraphs following that will talk about the similarities and differences between
them. The conclusion will explain to the readers how the information listed above
affects them and what they can do to lessen the damage of viruses in their lives. To
make it easier for the younger population to understand this topic, I will make a
children’s comic book. The children’s book will show the main ideas stated in the
research paper using cute characters for it to be easy to read and comprehend.

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