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Browse project ideas by Polygence mentors

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Can We Make Brain Scans from Different Hospitals Look More Similar?

When scientists use brain scans (like MRIs) from different hospitals, the images can look a little different because they were taken with different machines. This can confuse computer programs that are trying to learn patterns, like figuring out who might have a disease based on their brain scan. In this project, you'll explore how we can make these scans look more similar—this process is called harmonization. You’ll learn how to use AI tools like convolutional neural networks (CNNs), which are great at looking at images, and generative AI methods like GANs (generative adversarial networks), which can help transform one type of image to look like another. You’ll also explore domain adaptation methods—these help AI models adjust when the data comes from different places. The goal is to teach the computer to ignore the differences between scanners and focus on what’s really important: the patterns in the brain that relate to health. This is a great way to dive into machine learning, computer vision, and real-world healthcare problems using brain imaging data.

Advancements at the Intersection of AI and Aerospace Science

This research project aims to explore the transformative role of artificial intelligence (AI) in aerodynamics and highlight its profound impact on the field. It examines how AI algorithms are revolutionizing traditional methods of aerodynamic analysis and design, allowing for more efficient and optimized aircraft configurations. The project delves into specific applications such as airfoil design, where AI decreases the time to results with the design of the experiment. It also explores the challenges that come along with linking AI with aerospace whether that be the guidance, navigation, and control issues or the long-term sustainability and efficiency of current commercial systems.

Engineering, Computer Science, AI/ML, Business

Shervin
Shervin

Field Survey Proposal for: Building an Eco-Friendly Multipurpose Stadium/

The project’s primary aim is to coduct a study on multipurpose dome for football, among other uses, while adhering to sustainable practices. We aimed to align this project with Saudi Arabia’s national goals of reducing carbon emissions and promoting renewable energy. By using eco-friendly materials and energy-efficient design, the dome will not only minimize environmental impact but also serve as a model for sustainable development in the region. The outcome is presented in the local highschool journal as a scientific research paper.

Engineering, Computer Science, AI/ML, Business

Shervin
Shervin

The significance of native biomolecules in the tumor microenvironment

This interesting project will investigate and seek to find the chemicals found in tumors, why they are there and how they affect the tumor cell population. This project will provide a sound understanding of the nature of oncology.

Cancer

Reuben
Reuben

The role of Macrophages and Class Switching in the Tumor Microenvironment

This project would go into cellular detail of the role macrophages, an immune cell plays in the initiations, development and metastasis of cancers. This project will also explore how immunomodulators can effect a chance on the role immune cells play in the tumor microenvironment in resistance, fibrosis, evasion and cytotoxicity. This project will provide state-of-art insights into immunotherapies and immune cell genetics

Cancer

Reuben
Reuben

The role of emerging biomarkers for targeted therapeutic and diagnostics in cancer treatment.

This project would go in depth into emerging protein biomarkers, their role and potential to be exploited for the targeted delivery of cytotoxic payload as cancer treatments. This project will provide the student with detailed information on genetic drivers of oncology and the science and utility of computer aided drug design, chemical synthesis, biological evaluation and development of targeted -radiotherapy, -chemo, -immunotherapy and other forms of cancer specific therapies

Cancer

Reuben
Reuben

U.S. Monetary and Fiscal Policy Responses during Recessions and Depressions

This project will explore macroeconomic business cycles (booms and busts) and fiscal and monetary policy responses in the United States since the creation of the Federal Reserve System in 1913. Topics of focus can include the Great Depression and the New Deal; the post-World War II period; the Great Moderation; Great Recession; and the Covid-19 Recession. Student will explore and analyze U.S. macroeconomic data (employment, gross domestic product, etc), Federal Reserve Federal Open Market Committee statements, and fiscal policies to understand the challenges in conducting monetary and fiscal policies to respond to business cycle dynamics. Potential student outcomes can include a research paper, case study, or poster presentation.

Statistics, Economics

Elena
Elena

Analyze Environmental Data

Identify publicly available data related to student's question, re-analyze downloaded data, and write a scientific research paper. Skills gained: data analysis, biostatistics, data visualization, scientific writing.

Biology, Environmental Science

Emma
Emma

Diabetic Retinopathy Detection

Project Description: Use deep learning to analyze retinal images and identify early signs of diabetic retinopathy, a leading cause of vision loss. Skills Learned: Computer vision (CNNs), medical imaging interpretation, data preprocessing, ethical AI. Information Gathering: Students will use public datasets such as the Kaggle EyePACS dataset and review medical literature to understand grading of retinopathy severity. Outcome: Trained CNN model + presentation on diagnostic accuracy and real-world impact.

AI/ML

Issam
Issam

AI Stethoscope Analyzer

Project Description: Train an AI model to detect abnormal heart or lung sounds (such as murmurs or crackles) using open-source stethoscope audio recordings. Skills Learned: Audio signal processing, classification models, medical acoustics, dataset labeling. Information Gathering: Students will explore open datasets like the PhysioNet/CinC Challenge databases and learn how to process and label audio recordings of bodily sounds. Outcome: Working audio classifier + research paper on its clinical applications.

AI/ML

Issam
Issam

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