Meet PolyGPT, our AI-powered Project Idea Generator
Tell PolyGPT your favorite subject and a few hobbies you're passionate about to generate personalized project ideas.
Log in to explore PolyGPTExplore project ideas with the help of PolyGPT
See your personalized project ideas come to life with PolyGPT! Log in to brainstorm ideas.
We know the jump from your interests to a research project idea can be tricky.
That's why we've built tools to help you find the perfect project idea to lay the foundation of a successful project. Simply copy your favorite idea to your clip board, and paste it in the project idea section of the application.
Browse project ideas by Polygence mentors
Introduction to computational analysis of biological images.
One of my areas of expertise is automated biological image analysis. Microscopy imaging is a common and useful tool to readout biological data. Processing and analyzing biological images are important skills for biologists to acquire if they are to become independent researchers. In this project, students will develop basic skills in quantifying biological images using introductory level Python script. Students will be presented with microscopy images and will learn to extract useful information, such as pixel colocalization. Using introductory level Python-based data visualization, students will compile the relevant information into graphs and interpret the information. The outcome of this project will be a set of Python scripts that 1) reads and quantifies biological imaging data and 2) plots the relevant data intuitively. Given enough time, students could compile these scripts into a standalone desktop application.
Nutrition
Fundamentals of stem cell biology
My primary area of expertise is stem cell and tissue regeneration. In this project, students will choose a regenerative adult tissue and write a scientific review about the resident stem cells of that tissue. The goal is for students to understand the fundamental role of stem cells during tissue regeneration and highlight the characteristic features of a specific stem cell population (eg. from muscle, liver, brain). Students will learn the answers to fundamental questions about stem cell biology, such as, “What is a stem cell? What do stem cells do prior to and after injury? How do they respond to injury? How do they form new tissues?” The outcome of this project will be a review article that can be submitted to a high school-level scientific journal.
Nutrition
From Trends to Tactics: Transforming Pop Culture Phenomena in Marketing into Strategy
What if you could take a viral trend, influencer marketing challenge, or consumer behavior shift and turn it into a marketing strategy? In this project, you will identify a compelling phenomenon—whether it’s the rise of de-influencing, the impact of AI-generated influencers, or changing attitudes toward brand authenticity—and translate it into an actionable marketing plan. You’ll start by analyzing real-world examples, conducting secondary research, and formulating research questions to better understand the drivers behind the trend. Then, you’ll develop a strategic framework to help brands or content creators leverage (or adapt to) this phenomenon effectively. The final product will be a well-structured paper outlining key insights, strategic recommendations, and potential implications for marketers. This project is perfect for students interested in digital marketing, branding, and consumer psychology—especially those who want to bridge the gap between academic research and real-world business applications.
Business, Statistics, Psychology
Exploring the Genetic Basis of Neurological Disorders
This project investigates how genetic mutations contribute to the development of neurological disorders such as Alzheimer's disease, epilepsy, or Parkinson's disease. The student will begin by reviewing key genes associated with their chosen disorder and exploring how mutations impact brain function at the molecular or cellular level. Using publicly available genetic databases (e.g., OMIM, ClinVar) and bioinformatics tools, they can analyze genetic variants, compare their prevalence across populations, and predict potential functional consequences. The final product could be a research paper, an infographic explaining gene-disease relationships, or a presentation on emerging gene-targeted therapies. This project is ideal for students interested in neuroscience, genetics, and biomedical research. It provides an opportunity to develop analytical skills while exploring the real-world implications of genetic research on brain health and disease treatment.
Healthcare, Neuroscience
AI-Powered Financial Analytics Platform for Market Forecasting - Advanced
This advanced project challenges students to develop a full-fledged financial analytics platform incorporating multiple machine learning models. Students will use ensemble techniques and time-series forecasting models to enhance prediction accuracy. They will also deploy the system with API endpoints, simulating real-world applications used by hedge funds and investment banks. Skills Covered: Time series forecasting (ARIMA, LSTM) Ensemble learning for boosting model performance API development for financial analytics services Real-world implementation of trading strategies Performance benchmarking against industry models Outcome: A production-ready financial analytics platform A research paper comparing ML-based market forecasting techniques A deployed API for real-time financial predictions
Computer Science, AI/ML
Liquidity Forecasting and Investor Behavior Classification - Intermediate
This project builds on basic ML skills by introducing students to dual-model financial predictions. Students will implement both regression models (Random Forest, Gradient Boosting) for liquidity forecasting and classification models for investor behavior prediction. Feature engineering techniques will be applied to enhance model accuracy. The final results will be presented through an interactive dashboard for financial insights. Skills Covered: Advanced feature engineering for financial datasets Implementing Random Forest and Gradient Boosting Investor behavior classification using logistic regression and decision trees Model evaluation techniques (cross-validation, AUC-ROC) Interactive financial dashboards with Plotly Outcome: A dual-model system predicting liquidity and investor behavior A research paper analyzing feature importance and financial drivers An interactive visualization comparing model performance
Computer Science, AI/ML
Mutation frequency between cancer subtypes
There are often several understudied genes in the field of cancer biology. Scientists need to have a reason to study a gene, so lets give them one! Using publicly available data we can create a data base where we look at the commonalities and differences between cancers and cancer subtypes to see if anything stands out. This project can help students learn or strengthen their data analysis skills while also learning more about the field of cancer biology.
Cancer
Genetic evolution
A project involving genetic evolution involved studying the differences between a gene of interest. Often times, these studies branch to multiple organisms and involve understanding functions of proteins. This project could result in a review paper, slide deck, or science fair entry.
Cancer
Stock Price Prediction using Regression Models - Beginner
This project introduces students to the fundamentals of financial analytics and machine learning. Students will learn how to collect stock market data from APIs like Yahoo Finance, clean and preprocess the data using Pandas, and apply basic regression techniques such as Linear Regression, Lasso, and Ridge to predict stock prices. Additionally, students will create simple visualizations using Matplotlib and Seaborn to analyze stock trends. Skills Covered: Data collection and cleaning Exploratory data analysis (EDA) Introduction to regression models Basic financial market indicators Visualization techniques for stock trends Outcome: A Python-based stock price prediction model A research report explaining the prediction process and findings A presentation with key insights on market trends
Computer Science, AI/ML
Studying mutational patterns of COVID-19
In this project I worked with a student to download genomes from widespread variants of COVID-19 and investigate genetic variance between major strains. This project was super cool and allowed for better understanding of how genetically different major strains of COVID-19 were.
Biology
