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Our next winter deadline is December 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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In modern-day society, there is access to numerous sources to learning databases for various topics on the web for free, but is there always a helping hand to help get you started? For certain complex but beautiful topics like Quantum Computers and Quantum Algorithms, trying to get a grasp and understand them might seem difficult, but it really isn't! The goal of this project is to help fulfill achieve a student's passion for learning a topic like this, in the form of a video tutorial series on youtube! The tutorial series dives deep into a series of substantial questions. Why is Quantum Computing more efficient than Classical Computing? What does it mean for a quantum computer to be “faster” than a classical computer? What types of algorithms can run faster on a quantum computer than on a classical computer? We plan to prove these claims of the increased efficiency of Quantum Computing by studying Deutsch’s Algorithm, one of the first Quantum Computer Algorithms developed.



Efficiently, the tutorials solidify the understanding of Quantum Algorithms by developing an understanding of Quantum mechanics and its description of physical systems. Now to integrate my Computer Science passions into this project, the video tutorials implement the learning of Quantum Algorithms through the programming language Python in the Google Collab IDE,  and I go through various step-by-step processes of coding certain Quantum Algorithmic Simulations.  Conveniently, the person watching the series doesn't need to have a pre-requisite knowledge of Quantum Mechanics or Python, just a growth mindset, as everything gets taught from the scratch! As a result, this aspect brings uniqueness to this project intending to help others learn such an interesting subject through the scope of computer science!

Quantum and Strong-field Physics, Modeling and Simulation, Computer Science, Applied Mathematics

Learning Quantum Computing with Python!

Mihir has been investigating the effect of COVID-19 on the efficiency of lungs. he has recently found that the Carnot efficiency increases due to a fever. Mihir will look into the mechanisms for body temperature increasing due to COVID-19. he will also develop a more sophisticated model of the lungs as a heat engine and compare the work output to the work required to promote oxygen uptake by the bloodstream. 

mechanical engineering (thermodynamics, heat transfer, fluids). entrepreneurship (cleantech, social enterprise).

Mihir is putting this together.

A brief overview of the clinical trials, applications, and challenges involved CRISPR/Cas-9 Technologies with several diseases, including genetic diseases like sickle-cell amenia and Leber Congenital Amaurosis (LCA) and Cancers such as Leukemia and Lung Cancer.

Genetics, Microbiology.

Medical Applications of CRISPR/Cas-9 Technologies

This paper examines how certain indicators can determine one’s susceptibility to Chronic Fatigue Syndrome. By looking at age, occupation, physical and biological factors, a relation to how CFS can possibly develop is being found(?). With the confirmation of certain factors, such as heavy workload, adding to one’s everyday fatigue, a closer look can be made into how it can transform into a syndrome that is characterized with severe fatigue and constant, extreme pain. We performed statistical analysis on data from a large survey conducted by the General Social Survey, and newly identified biomarkers that reveal CFS within a patient.

Comp Sci - AI/ML, Law, Software Engineering

How can certain indicators determine one’s susceptibility to chronic fatigue syndrome?

This paper explores the qualities that make a planet habitable and how these qualities can be combined to produce or prevent a habitable environment for a planet. We consider two planetary systems — TRAPPIST-1 and Kepler-62 — and develop a metric to rank the habitability of their respective planets. The host stars of each planetary system are compared to assess the habitability of each planetary system as a whole. Our outline for a habitable planet is one that would be able to sustain liquid water, has reasonable environmental conditions, and has the presence of molecules known to sustain life. Previous research on the topic has determined a range of values for specific categories that would make a planet habitable or allow for liquid water. This includes planet radius, stellar radius, planet density, effective temperature(Teff), and equilibrium temperature(Teq). We use data from the NASA exoplanet archive, as well as various other archives and sources from the literature. After determining the importance and impact that each category has, we will decide upon a ranking of the planets in each system based on habitability. The most habitable planets will be further explored through comparisons with Earth, research on the atmosphere of these planets, etc.

Planetary Astrophysics, Stellar Spectroscopy, Exoplanets, Interstellar Objects, Planet Nine, Solar System Science

An Examination of Habitability in Exoplanet Systems

Every year, 100,000 police-reported car accidents are caused by drowsy driving in the US. 800 of those crashes results in death. Having an automated system for detecting drowsy driving would significantly reduce the number of accidents and save lives. In this project, my goal is to create a fast and reliable machine learning algorithm for the classification of drowsy vs alert drivers. First, we develop an image classification algorithm in python and train it on hundreds of images of individuals in all levels of alertness. Next, we test the algorithm and report the confusion matrix. This will give us the accuracy, the number of false positives and negatives, the sensitivity, and the specificity. Finally, based on these criteria, we will optimize the training process to increase accuracy and decrease the number of false positives and negatives during testing. The results of this project will contribute to safety on the road.

Biotech and bioengineering, writing papers (any type), Engineering (especially Mechanical & Biomedical), Medical Device, Physics, Data Science, Programming, Code writing, Machine Learning, Image Processing, Mathematics

Machine learning algorithm for classification of drowsy vs alert drivers

My project is about the impact that Covid-19 has had on anxiety and depression in adolescents ranging from 13-19 years old in the Puget Sound region. The severe impact of Covid-19 has largely increased the amount of individuals suffering from anxiety and depression due to the isolation they felt during Covid-19. The way I will be conducting my research is by sending out a survey to a large variety of people, that has a valid scale that pertains to the area of research in this project. My survey will capture the severity of the anxiety and depression that the subjects have experienced over the past year. They would then answer the survey and I would then gather all the collective information on an excel spreadsheet that I could analyze further. After analyzing the data I would come to a conclusion that I would portray in an informative video or research paper.

Clinical Psychology, Comparative Psychotherapies, Survey Research

The Impact of Covid-19 on Adolescent Anxiety and Depression

Security and safety on the internet is knowledge that anyone should have in the age of everything being connected. This includes safe browsing, encrypting traffic, reducing your footprint, and also keeping your devices safe. 

Daniel is going to explore setting up his own VPN to obscure his network traffic and get an understanding of what a VPN does to his traffic.

Next, he will explore how to reduce his internet footprint by various means from browser extensions to ad blocking, to limiting what browsers can glean from his activity.

Daniel will also explore a third area of security which could include things such as how browser's protect the users or how some of the new VPN protocols, like WireGuard, work.

Computer Science, Software engineering, Software design

Being Secure and Safe in Today's Internet

This is a review article detailing how stem cell transplants are used after intense chemotherapy and radiotherapy treatments.

Biology, Physiology, Biochemistry, Chemistry, Disease Modeling with Patient Derived Stem Cells

The Role of Stem Cell Transplants in Cancer Treatments -- a review

Around 9% of the US population (30 million people) will experience an eating disorder at some point in their lives. Moreover, eating disorders are among the deadliest mental illnesses, second to opioid overdose. In fact, eating disorders affect the brain in ways that are mechanistically similar to addiction disorders. Due to lack of information and awareness, many people with eating disorders don’t recognize that their struggle is a treatable mental illness. This podcast will illuminate the biological and environmental causal factors of the different types of eating disorders and reveal the ways in which brain circuits go awry to propagate the illness. Revealing the science behind eating disorders could open doors to new treatment targets and provide evidence to destigmatize the disease.

Neural systems and circuits; Neurotransmitters (dopamine, serotonin); Circuits underlying neuropharmacology and neuropsychiatric disease; Neuroscience of behavior and perception; Drug discovery; Intersection between art and science; Photography

Eating Disorders: A comprehensive review of the psychology, neurobiology and etiology behind the stigmatized mental illness

With the growing need to address global threats such as global warming and climate change, the demand for green chemistry has never been greater before. As a result of detrimental human activities including fossil fuel combustion and deforestation, climate change has irreversibly caused an anomalous rise in the average global temperature, extreme weather, and other climate phenomena. In fact, according to the IPCC Fifth Assessment Report, “It is extremely likely (95% confidence) that human influence on climate caused more than half of the observed increase in global average surface temperature from 1951 to 2010”. Additionally, the third chapter of IPCC’s Special Report of the Intergovernmental Panel on Climate Change has also confirmed that other obvious signs of climate change have wrought havoc across the continent as ocean acidification, melting glaciers, and ice sheets continue to emerge while extreme weather phenomenons such as tropical storms, floods, heavy precipitation, heat waves, droughts, cold waves, and snowstorms increase tenfold. To combat this issue, scientists throughout history have developed chemical products and synthesis pathways that aim to minimise the harmful impacts of hazardous substances in industry and healthcare. Specifically, inorganic-organic hybrid nanomaterials with their highly desirable features, such as high activity and selectivity, excellent stability, efficient recovery and recyclability, enable benign catalytic processes and are environmentally friendly. In this paper, a historical perception of the evolution of inorganic-organic hybrid nanomaterials will be discussed as well as the different effective synthesis pathways scientists with diverse expertise have come to discover, focusing on their catalytic applications on a global scale. For instance, using the sol-gel method or hydrothermal synthesis to form silica nanoparticles which can act as catalysts in reactions such as oxidation, reduction, and decomposition.

Chemical Engineering, Physics, Chemistry, Perovskite, Batteries

A review of the development of synthesis and catalytic applications of inorganic-organic hybrid nanomaterials: silica and graphene oxide

Migration, be it forced or chosen, is and will be a structural phenomenon which needs to be addressed by policy makers and institutions in a long term and structural matter. Countries who fail to do so pay a high prize in terms of school dropout, unemployment and raise people without perspectives -costs that are far higher than the necessary investments in education. One area of increased attention in world politics is the refugee crisis. This paper handles this issue in the specific case of Turkey. Although Turkey has implemented several policies for Syrian refugee pupils’ integration, how effective they are functioning in practice is questionable. Segregation is of great importance with dire consequences for the refugee children. The issue of the refugee crisis is engaged in terms of the integration of Syrian refugees to the society, and the problems that the children refugees face regarding their education. Emigrating to another country generally means that there may be language barriers and the refugees may need to suspend their education and/or work. In this paper, to gain a better perspective of the Syrian refugees and especially of children, Syrian refugee crisis is approached from many different aspects such as educational, psychological, and sociological. As a suggestion, a brief period in immersion classes for each refugee children should to be combined with an extended support for them in regular classes, since it is obvious that the war in Syria has not been over and many of the Syrian refugees will stay in Turkey more for an undefined period.

History, Geography, Arabic, Islamic Studies, Middle Eastern Studies, Religious Studies

Syrian Refugee Crisis: Psycho-Social Impacts in Turkey

In recent years, the widespread use of generative language models has brought opportunities as well as some philosophical and technical questions. GPT2, a language model with 1.5B parameters, is an open-source language model provided by OpenAI. Our aim in this paper is to utilize the classification capabilities of GPT2 to create a new perspective on the question of whether language models show some kind of consciousness/self-awareness, in addition to technical questions such as how to detect the misuse of the outputs of language models.

To investigate this phenomenon, GPT-2ForSequenceClassification model was fine-tuned on TuringBench datasets and its performance was examined. In addition, the accuracy achieved by model as a result of training with training sets of different sizes, as well as its performance in human-machine discrimination, were evaluated.

The model exhibits consistent and above-average performance in identifying GPT-2-generated content compared to its classification accuracy in distinguishing other machine-generated text from human writing. This performance of the model in understanding self-generated texts is very similar to people's ability to recognize their own writing, and these results offer an interesting perspective on the self-awareness of artificial intelligence. Additionally, the model showed high accuracy in distinguishing machine generated output from human output, even when trained with very few examples.

Machine Learning, Artificial Intelligence, Computer Vision, Natural Language Processing, Data Science

Examining the Human-Like Proficiency of GPT-2 in Recognizing Self-Generated Texts

I will combine scRNA-seq data from multiple liver datasets, extract the genes of interest from those, and combine that in a new umap graph. I will then further analyze this data in order to find a new subset of a cell in the liver.

Cancer/Immunolgy

Using scRNA-seq data to find new liver cell subset

Kaitlyn is interested in researching the common causes or issues that are affecting the mental health of teenagers, as seen through their social media posts. The way that she will do this is by looking at the keywords users are using in their posts on Reddit when they are describing their mental health issues. Outside of count-based processes to determine common keywords, Kaitlyn will explore some machine learning techniques to determine the role that the concepts described by these keywords play in modern mental health. One avenue of exploration will be in looking at the context of the sentence to see if the word is being used positively or negatively. Another will be to see if certain keywords pop up together more frequently when certain events occur in the world.

natural language processing, machine learning, broadly engineering, audio processing, computational linguistics

Analyzing Mental Health Keyword Trends in Reddit Posts over Time

Despite its constitutional and historical purpose of being an institution that operates free of outside political influence, the Supreme Court of the United States has become an increasingly available means of executing partisan conflict over public policy in recent years. This is no better evidenced than by a developmental analysis of its rulings in regard to abortion legislation since the landmark case of *Roe v. Wade*. Upon inspection, a pattern of back-and-forth conflict over abortion policy that serves partisan interests above those of the American public becomes evident. This dynamic of retaliation and internal animosity threatens the constitutional integrity of the judiciary, putting the democratic rights of Americans in serious jeopardy. Major policy change to the way the Court functions, therefore, is required to maintain the ethicality of the Supreme Court in the future.

Creative Writing, Law, English, Philosophy

Hyper-partisanship in the Federal Judiciary

For the human brain to analyze and understand music, there is a brilliant and meticulous symphony that orchestrates our ability to perceive a compilation of sounds as music. Starting as variations in air pressure received by the pinna at the outer ear, musical sounds are transmitted via the ossicles in the middle ear to the cochlea of the inner ear that habor our sensory hair cells, which due to their mechanotransductive capabilities, transform the mechanical forces into electrical signaling that is then picked by the spiral ganglions transmitting the auditory message to various areas and pathways in the brain. While this cascade of events hold for every sound that enters our ears, why and how does music affect us? Why do specific songs trigger happiness while others unleash sad memories, and yet other songs bring relaxation or send shivers down our spines? In this work, we review the involvement of two major brain nuclei, the amygdala and the hippocampus, in the emotional processing of music. Among their many roles in the brain, these two nuclei had been shown to be heavily involved in enhancing emotional music memories and the euphoric response to music, interacting with one another to form long-lasting memories. This review gives an elaborate overview of the intricate interplay between the amygdala and the hippocampal neurons in the generation of the neural encoding of musical memories and their associated emotions.

Neuroscience, Neurodegeneration, Mathematics, Computer Programming, Dynamical Systems Analysis, Ordinary and Partial Differential Equations, Computational Neuroscience, Computational Physiology, Python, Matlab, Java

How are the amygdala and the hippocampus involved in the emotional processing of music and memories?

The Hippocampus Pituitary Adrenal Gland (HPA) axis is one of the major hormonal pathways in the human body which secretes some of the most important hormones needed for survival such as corticotropin (CRH), adrenal corticotropin hormone (ACTH), Androgens (AND), Aldosterone (ALDO), and Cortisol (CORT). The HPA axis consists of the Hypothalamus, the pituitary, and the adrenal glands. The Hypothalamus and pituitary reside in the brain, and the adrenal glands reside on top of the kidneys. Just like everything in the human body, the levels of corticotropin and other hormones synthesized by the HPA axis fluctuate based on the time of day, internal and external stimuli, and the circadian rhythm of a person. 7 neutral inputs either directly or indirectly affect this axis. The Indirect inputs would be the medial prefrontal cortex, hippocampus (HC), Amygdala (Amyg), Septum Pellucidum and the direct inputs would be bed nucleus of the stria terminalis (BNST), dorsomedial hypothalamus (DMH), ventromedial hypothalamus (VMH), Nucleus Tractus Solitarius (NTS), and Ventrolateral Medulla (VLM). Even though there are tangible aspects which can affect the HPA axis, there are other major regulators which are more abstract and are not tangible things. In particular, one of the greatest effectors of the HPA axis would be any type of stress exerted for an extended period of time. The HPA axis is one of the major hormonal pathways in the human body which secretes some of the most important hormones and here we will review the major regulators which affect the HPA axis and to what extent they alter HPA secretion, as well as examining how to counteract these effects.

Neurosurgery, Neuro-Oncology, Neurology, Medical Imaging

What are the major regulators of the HPA axis and at what level do they alter HPA secretion?

In this research paper, we explore the causes, current and proposed solutions to mitigate homelessness in San Francisco. First, we take a look at who makes up the homeless population by exploring data on their age, gender, mental health, and other conditions, as well as employment and family backgrounds. This section provides a crucial foundation for the rest of the paper to build on. Then, we consider current causes of homelessness in the city of San Francisco such as high costs of living, drug use, employment, and health. After this, we analyze current policies that aim to address these causes such as drug, theft, and prison reformation policy (Prop 47) and healthcare policies focused on the homeless. In this section, we take a deep look at what forms these policies and address points of failures or shortcomings in them. Finally, by forming new policies around credible data, we suggest tangible propositions that work to mitigate homelessness in this city without placing large burdens on surrounding communities.

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