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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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Blood Spatters are one of the most common forms of forensic evidence in crime scene investigation. However, analyzing and classifying blood spatters takes a lot of time and energy, slowing down the investigation process. In particular, classifying the cause of impact stains as gunshot or blunt force could be sped up through the use of Artificial Intelligence. To tackle this problem, we used a publicly available dataset of 61 impact stain images and built a Random Forest Model that classifies the data as either gunshot or blunt force induced.

computer science, machine learning, applied mathematics, data science, data analysis, modeling

Applying Random Forests to the Classification of Forensic Evidence.

This Pod will have a one week break in sessions and will not hold a session on September 20th. The program will instead conclude on September 27th.

The idea of gene editing might sound like something out of a science fiction movie… how would you even start to think about changing the DNA that gives the trillions of cells in your body instructions on how to function properly? In this pod, you’ll dive into the world of genetics and gene editing and explore the potential for gene editing use in human health and disease applications. Through this process, you’ll learn about conducting research, the cutting-edge technologies allowing for gene editing, and the ethics of manipulating the human genome.

Genetics, genome editing, molecular biology, neuroscience, bioethics, science policy, genetics in human health/medicine

Explore gene editing: Learn about genetics and its uses in healthcare

Chimeric antigen receptor (CAR) T-cell therapy is a method that extracts T cells from the patient's blood and virally introduces a genetically engineered T cell receptor targeting a specific cancer antigen and subsequently readministering these genetically engineered CAR T cells to the patient. These T cells are then better at identifying the tumors and attaching to these tumor cells resulting in a stronger cytotoxic immune response. The development of CAR T cells has been a huge success as an immunotherapy, especially for the targeting of non-solid tumors. Since their original inception in 1987, there are now six independent FDA approved CAR T cell therapies targeting a variety of blood cancers, with the first being approved in 2017. As a relatively new treatment, there is a continuous effort in improving the safety and efficacy of CAR T cell therapies. As mentioned previously, CAR T cells have undoubtedly been successful in the treatment of non-solid tumors, however their efficacy towards treatment of solid tumors has been limited. Additionally, the safety and long-term effects of CAR T cell treatments is still a concern. Combination therapy utilizing CAR-T cells and immune checkpoint inhibitors is being explored to potentially mitigate some of the limitations associated with CAR-T cells. These immune checkpoint inhibitors block the effects of the immunosuppressive microenvironment, so when combined with the CAR-T cell therapy, it would increase the success rate of the treatment. Because of this, the immune checkpoint inhibitors prevents the CAR T cells from becoming exhausted, thereby increasing the success rate of the treatment, proving the feasibility and positive impacts of a combination therapy between immune checkpoint inhibitors and CAR-T cell therapy.

Cell biology, pharmacology, cell migration, GPCR signaling and function

Combining CAR T-cell and immune checkpoint inhibitor therapy, a promising, yet unproven immuno-oncology approach

This project aims to create an online dashboard that visually presents information about a dataset containing over five thousand unique titles on Netflix. The end product will contain several graphs showcasing the correlation between specific columns of data. I plan on using Dash as the method of creating a dashboard and using the Python Language. The dataset being used was taken from the Kaggle website. The dataset contains 5850 rows and 15 columns. Each row is an entry for a title on Netflix and each column is a certain quality about it like whether it is a show or a movie, the name, the description, the year it was released, age rating(r, pg-13, tv-ma), the entire length in minutes, the genres that the movie or show satisfies, the country in which it was produced, the number of seasons there are if it is a show, several IMDB statistics and ratings, and the same for TMDB. There is also a secondary dataset that contains 54314 different people’s names each shown multiple times to amass more than 77 thousand rows and five columns. These columns include the actor’s name, the name of the character they played, and whether they were a director or actor. If they were the director, then they did not have a value in the column containing the names of the characters. I don’t plan on using this second dataset, instead focusing on the first one. I also plan to have multiple graphs with callback interactions and link different graphs together.

Any topic in data science (machine learning, applied math, statistics), web development, or chemistry.

Creating a Data Visualization Dashboard to visualize interesting trends in a dataset containing titles from the library of Netflix’s content.

Suicide is one of the leading causes of death in America. Every day, about 125 Americans take their own lives. These deaths can be executed through both violent (e.g. firearms, hangings) and non-violent methods (e.g., overdosing). Prior work has found that the use of firearms contributed to around 60% of all completed suicides. Nearly 50% of suicidal attempts are done impulsively, with little planning. Access to firearms can often be dangerous in these situations, given that individuals in close proximity to a firearm are able to act on these impulses. Suicide by a firearm can be deadly, as 90% of firearm suicide attempts lead to death. This being said, individuals often turn to firearms when considering different methods of suicide. Owning a gun inside a home, increases the risk of suicide. The risk of suicide in homes with firearms increases for not only the gun owner, but also anyone living within the home. The present paper discusses access to firearms and the risks of suicide across all ages and genders.

projects that examine emotion regulation from a mental health perspective

What are the risks of owning firearms on suicide?

In the medical world, a multitude of revolutionary technologies have been developed to improve the process of diagnosing and treating a patient. In the modern era, one of the most innovative developments is the use of CRISPR-Cas9, an enzyme that uses palindromic sequences of nucleotides to bind to and delete or edit DNA. Although heavily studied as a genetic engineering tool, this fascinating protein can also identify genetic targets to improve cancer therapy through CRISPR screening. CRISPR screening is an experimental approach that can identify genes that are responsible for a specific phenotype. This paper

Cancer Biology, Immunology, Biochemistry, Molecular Biology

Genetic Vulnerability: PIK3CA Gene Dependency in HER2-Positive Breast Ductal Carcinoma

The global outbreak of COVID-19 has significantly affected various aspects of healthcare, including the management of children with Autism Spectrum Disorder. For example, the disruptions in healthcare services, including reduced access to in-person interventions, have resulted in changes in diagnosis and treatment. Telehealth and remote interventions have emerged as viable alternatives, enabling the continuation of therapy while ensuring the safety of the patients involved. AI-based technologies have shown promising potential in assisting with this transition to virtual care for individuals with ASD, and have improved the early detection, diagnosis, and treatment of autism. This review highlights some of the key findings related to the application of AI in autism management and its potential for enhancing the delivery of care during the COVID-19 pandemic.

psychiatry, psychology, neuroscience, public health, projects that involve neurocognitive testing, neuroimaging, and social determinants of health.

How has AI improved the COVID-19-facilitated transition to virtual healthcare in the context of diagnosing and treating patients with ASD?

The changing regulatory environment for crypto, countries adopting cryptos to use as their national currency, war donations being made with crypto, and the wholesale ban of crypto transactions and wallets in other countries has raised questions regarding what crypto’s place will be in an evolving regulatory world. My research will center around examining the evolution of the development, regulation, shaping of cryptocurrencies by geopolitical events, and subsequent social and economic reactions to cryptocurrencies. This paper will 1) define why cryptocurrencies by nature are different than any other form of exchanging value, 2) explore the plethora of uses for crypto that have emerged over the past several years, 3) outline how regulations have enhanced and limited crypto’s use-cases, 4) explain how governments will be unable to replicate cryptocurrencies through centralized means, 5) discuss the Pros/Cons of using crypto in regulated environments, 6) discuss the Pros/Cons of using crypto in unregulated environments, and 7) ultimately suggest that cryptocurrencies are here to stay and be used in global and country specific economies.

The tentative main points of the paper are:

Explaining what cryptocurrencies are and how they are different from any other form of exchanging value. 

Explore the uses for crypto technology, coins, and NFTs. 

How different countries have used them, regulated them, and fallout from those actions.

Government created cryptocurrencies are centralized in nature and thus are unable to replace cryptocurrencies’ use cases.

Pro/Con analysis of crypto in regulated settings.

Pro/Con analysis of crypto in unregulated settings.

Conclusion: Crypto is a technology that is here to stay to be used in global and country specific economies.

Law, International Law, Finance, Business, Economics

In the wake of current geopolitical events, what is crypto’s place in a post regulatory world?

The first part is acquiring and parsing through data. Then you have to evaluate the data and see if it is possible for the machine to adapt to scenarios dependent on luck. The data we will get will be from Pokémon as it is a game that you can learn and grow as a player through playing the game, but has luck based components that can lead  to lots of different outcomes, which separates ML playing Pokémon from ML playing most board games, as most board games have zero luck dependency. Pokémon has a pretty simple set of moves with at most 9 options per turn for 2 players. The main focus will to be to analyze what options are chosen in specific scenarios and to see if said options leads to wins or losses, and to analyze the effectiveness of said options using a calculator. Data for Pokémon can be extracted from Pokémon showdown, and the GitHub, and via match transcripts from match replays that will be the main data source. The random components will change the scenario from predicting to adapting to see the capabilities of ML to react rather than predict, as in certain cases predicting all the options can require a lot of computing power, which might not be available. Also we will be able to see how the ML actually chooses to gamble on luck rolls and see if that correlates to a 50/50 or if the ML either chooses more consistent rolls, or gamble more often on lower probability rolls.

Chemical engineering & data science applied to biology

How can you use data science to analyze the outcomes in a turn based scenario with random components?

From Sarayu: I am planning on writing a research paper on wireless communication and its implementation in satellite communication. To start of the paper I want to give an introduction to what wireless communication is and the different steps included in the process such as transmission and modulation. Then I want to go into how wireless communication actually works and how signals and systems make it possible, I could talk about different types of signals and how continuous time signals act differently from discrete time signals? After this I want to talk about how wireless communication can be applied to satellite technology and explain what satellite communication is and how it is implemented often in much technology today.


Deep learning, machine learning, Python, Arduinos, electrical engineering, biomedical engineering, computational imaging, optics, computational electromagnetics, signal processing, computational craft, computational art, algorithmic art

How Wireless Communications is Implemented on Satellite Technology  

Epilepsy is a neurological disorder which affects approximately 1% of the population, including more than one million women of childbearing age. Women with epilepsy have higher rates of pregnancy complications which affect both them and their children: they have a higher risk of preeclampsia, gestational hypertension, bleeding in pregnancy, and excessive bleeding postpartum, and higher rates of congenital abnormalities and stunted cognitive development in children. Studies have shown that antiepileptic drugs (AEDs), particularly valproate, may trigger malformations and birth defects. Moreover, changes in AED prescription patterns, including a decrease in the use of valproic acid and carbamazepine, an increase in the use of lamotrigine and levetiracetam, and a decrease in polytherapy exposure, have been linked to a decrease in the prevalence of major congenital malformations. This study utilized an open source dataset (Lussier et al., 2017) including 318 women from the Taiwanese Registry of Epilepsy and Pregnancy (TREP), a voluntary prospective registry which collects questionnaire responses from pregnant women with epilepsy and AED prescriptions throughout pregnancy, delivery, and early childhood development. The dataset contains information about AED prescription, including number of medications taken, type of AED, and exposure to first generation AEDs (developed prior to 1993), and pregnancy outcome. We analyzed the data to find additional relationships between AED use and premature birth, need for a cesarean section, and other malformations, and built predictive machine learning models to aid in the prediction of the need for medical intervention in pregnancies involving epileptic women. We expect to find that polytherapy, exposure to first generation AEDs, and use of valproate serve as markers of premature birth or other obstetric complications. Results and discussion to be added later.

Neuroscience, Artificial and Biological Vision, Machine Learning, Computational Neuroscience, Psychology/Behavior, Biostatistics

How can the use of AEDs in epileptic women predict poorer perinatal outcomes?

Medical applications of AI/Machine learning, AI/ML in the field of radiology, cognitive neuroscience topics (especially memory), stroke pathology/imaging/interventions/epidemiology, diagnostic or interventional radiology

In this project, I have built machine learning models that can predict epilepsy diagnosis and epilepsy subtype (chronic vs. controlled) in children based on their eye movement data. I have also written an experimental research paper that covers the motivations for new ways of detecting epilepsy, my methods for determining the optimal models, and the clinical implications of the results. This project demonstrates the predictive value of certain saccadic eye movement parameters for detecting epilepsy. My models have achieved significantly above-chance performance and can be used to aid in low-cost, non-invasive epilepsy diagnosis for children.

A Predictive Model of Pediatric Epilepsy from Visually-Guided Saccades

Epigenetics is the study of how external factors from the environment change the way genes are expressed. Similar to how a change in DNA sequence may cause certain disorders, epigenetic modifications alter the biochemical and physical properties of DNA that affect gene activation to influence disease development. Epigenetic markers, which are found on the complex of DNA and protein known as chromatin, have been recognized as a potential gateway to achieving improved disease diagnostics. Thus far, we have obtained a foundational understanding of how epigenetic modifications affect chromatin in a laboratory setting. Adaptations of sequencing technology to assay epigenetic features of chromatin have enabled the identification of numerous biomarkers of disease. Here, we review the most widely studied epigenetic biomarker, DNA methylation, in cancer progression. However, a more mechanistic understanding of how epigenetic modifications impact chromatin structure to regulate gene transcription would advance the field even further. Many of these mechanisms involve changes in how the chromatin polymer compacts in nuclei and folds in three dimensions. In this paper, we not only discuss the current applications of multiple sequencing assays to study higher-order chromatin structure, but also propose microscopy-based techniques as the next frontier in translating epigenetic-based diagnostics to a clinical setting.  

Biological Engineering, Developmental Biology, Molecular Biology

Towards an Advanced Understanding of Epigenetic Disease: From Sequencing to Microscopy

Stuttering is a speech disorder in which the flow of speech is disrupted by involuntary repetitions and prolongations of sounds, syllables, words, or phrases. It is also characterized by involuntary silent pauses or blocks in which the person who stutters is unable to produce sounds, and it prevails in every region of the world.  The etiology of stuttering is yet unknown, but previous studies have found different genes arrangement and brain dysfunction between people who stutter (PWS) and people who don’t stutter (PWNS), which pave the way for future research. Bilingualism is the use of more than one natural language, within the category of multilingualism, whose speakers outnumber monolingual speakers in the world population.

Multilingual speakers have been documented with higher levels of typical dis-fluency in their speech than their monolingual peers, which put multilingual speakers at greater risk of misdiagnosis as individuals who stutter. However, disparages are investigated between monolingual people who stutter (MWS) and bilingual people who stutter (BWS). Researchers have been examined MWS and BWS separately, yet limited research have been done to compare different performances between them. In this work, the overview of MWS and BWS are introduced: different types and traits of stutter between MWS and BWS are compared and the difference between brain structure, executive force, motor control, and cognitive reserve are investigated and synthesized based on previous studies. MWS appear to show deficits in executive control, while BWS seem to be classified as having greater potential in language, thus transferring to general executive control.


Research methods; General psychology; Social cognition; Developmental psychology; Theatre; Music composition; Film; Graphic design

The Difference of Performances And Brain Structures Between Monolingual Stutterers And Bilingual Stutterers

The project is focused on trying to create a game in Unity. Our goal during the mentorship is to figure out mechanics, aesthetics, and story to set them up to create a full game in his spare time afterwards.

Game Design/Development, learning the process of creating a game from start to finish, analyzing and creating games that have a transformational impact on the player

Game Pre-Production

This article presents a review of drama therapy’s effect in children’s psychological development and its possible therapeutic applications. Drama therapy is conceptualized as the use of theatrical techniques to allow the release of emotion to address unresolved trauma (Jennings et al., 1994). As people grow up, there is a decline in creativity that leads to a reduction in human ingenuity later on in life, thus decreasing society’s potential (Bronson & Merryman, 2010). Traumatic experiences, such as losing a loved one, is one of the main sources of psychological distress in children, and traditional therapy methods show only moderate success in these age groups (Edgar-Bailey & Kress, 2010). Confronting trauma and the ontogenetic decline in creativity will be explored through analyzing the effects that drama therapy has on improving children’s emotional wellbeing and promoting self-expression. This is crucial in exploring the future success in utilizing drama therapy as a more common form of therapy and as a platform for promoting creativity across the lifetime.

developmental psychology, early cognitive development, early language acquisition, gesture and communication, theater and performance studies

Developmental Approaches in Drama Therapy: Addressing Trauma and the Decline in Creativity

This article discusses the technical derivation and components of the ER=EPR conjecture by Susskind and Maldacena, starting with the mathematical derivation of Einstein-Rosen wormhole solution in general relativity, building on the Schwarzchild metric to arrive at the Eddington-Finklestein and Kruskal-Szekeres coordinates.  Lastly, it will construct a Penrose diagram to the four-part model of spacetime. It then introduces elementary ideas from quantum entanglement (EPR) and connects it to the wormholes solution in AdS/CFT holography. If time permits, we explore the interesting implications ER=EPR has on Hawking Radiation, firewalls, and black hole information theory.

Quantum Computing, Quantum Gravity, Black Holes

Exploring the links between Quantum Entanglement and Curved Space-Time

In this pod you will explore the theories, research, and practical applications that inform the fields of community psychology and social justice. We'll focuses on understanding and addressing the social, cultural, and systemic factors that influence well-being and social inequities. Through this process, you'll learn about conducting research and develop a skill set you can use to work to make changes you'd like to see in your community.

gender-based violence prevention and intervention; global health; public health; racial disparities in programs and health outcomes; program evaluation, culturally-responsive approaches to teaching, policy advocacy,  community-based research methods

Publish an article: Dive into community psychology and social justice

Alzheimer's Disease (AD) is a type of progressive dementia that causes loss of memory and function. It affects over 5.8 million people sixty years of age and older in the United States alone. When an individual has AD, neurodegeneration ultimately leads to severe impairment and eventually death. Throughout the stages of the disease, symptoms can range from mild forgetfulness to loss of motor control and bodily functions. Unfortunately, the disease may go unnoticed during initial stages if not tested for and detected early. Signs of Alzheimer's may accidentally be overlooked by physicians, especially if they are subtle. Artificial intelligence (AI) and machine learning models (ML) can be used to improve the identification process of early signs of AD. Some neuropsychological impairments AD patients suffer from include memory loss, difficulty recalling words or phrases, changes in personality and behavior, and decline in bodily functions that affect day to day life. AI may be able to pick up certain details and data that human perception cannot. If trained with a proper data set, ML models would be helpful to physicians in this area of healthcare. In this systematic review, the different neuropsychological impairments visible in the early stages of AD will be discussed as they relate to ML, deep learning, and AI applications intended to aid the diagnosis of AD.

Artificial Intelligence Applications For Improving Alzheimer's Disease Diagnosis Using Neuropsychological Assessments

A short film following a college student post pandemic as they navigate their day while dealing with anxiety while in New York City. The film depicts a rising NYU junior's struggle to combat day to day life while dealing with a common mental disorder. Specifically, the film gives an insight into the anxiety experienced by a college student that has been exasperated by the pandemic. As the city opens up, anxiety begins to embed itself in ways that are both unique but also predictable. The viewer can learn and perhaps empathize with the student in terms of anxiety as well as the pandemic and the infestation of more anxiety.

Clinical psychology, Sexuality, Racial and Gender Discrimination, Mental Health, Social Justice Issues, Maternal Psychology,

Anxiety: Day in the Life of a College Student

From its discovery in the immune systems of prokaryotes, the clustered regularly interspaced short palindromic repeats/CRISPR-associated (CRISPR/Cas9) system has revolutionized gene editing. With these advances in gene editing, there come many potential medical applications of the CRISPR/Cas9 technology to treat genetic diseases. This paper describes methods of using CRISPR/Cas9 to treat the genetic disorder Cystic Fibrosis (CF). CF is caused by a mutated cystic fibrosis transmembrane conductance regulator (*CFTR)* gene, affecting many of the body’s cells. People carrying this mutation have thick and sticky mucus which can build up in the digestive tract and lungs, leading to severe blockages and damage. These blockages can lead to trouble breathing and a higher possibility of infection. This paper will examine the current cystic fibrosis treatment, including the available drugs and their limitations. CRISPR/Cas9 has the potential to completely cure the disease in one treatment through the modification of the *CFTR* gene in the patients’ cells. This paper describes delivery mechanisms and mechanistic details of the gene editing process and how it can be applied to cystic fibrosis patients.

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