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
Antibiotic Resistance Patterns - Mining Global Surveillance Data
This research project uses publicly available databases from the WHO Global Antimicrobial Resistance Surveillance System (GLASS) and CDC's antibiotic resistance data to analyze patterns of bacterial resistance across different regions and time periods. Students would examine datasets showing resistance rates for common pathogens like E. coli and Staphylococcus aureus, creating graphs and maps to visualize how resistance patterns change geographically and over time. They would research the connection between antibiotic usage policies and resistance rates, comparing countries with different regulatory approaches. This project teaches data analysis skills, epidemiological thinking, and connects to current global health challenges. Students learn to work with real scientific datasets while exploring how human behavior and policy decisions impact microbial evolution, making complex concepts accessible through concrete data analysis. Image from the BBC.
Biology, Languages
Idiopathic Pulmonary Fibrosis - Analyzing Treatment Evolution and Patient Outcomes
This project involves analyzing the current state of Idiopathic Pulmonary Fibrosis (IPF) research by examining publicly available clinical trial data and published studies to understand how treatments have evolved over the past decade. Students would use databases like PubMed and ClinicalTrials.gov to research FDA-approved treatments like nintedanib and pirfenidone, comparing their mechanisms of action, clinical trial results, and patient outcomes data. They would create timelines showing treatment development, analyze survival rate improvements, and investigate emerging therapies in current clinical trials. The project teaches students how to read scientific literature, interpret clinical data, and understand drug development processes while exploring a real medical challenge affecting thousands of patients. Students can create presentations comparing different treatment approaches or analyze geographic differences in treatment access, making this both scientifically rigorous and socially relevant.
Biology, Languages
Beginner Research Review
My expertise is in neuroscience and gene regulation, with a focus on how the nervous system responds to injury and potential strategies for repair. A student interested in this project will explore the broad landscape of approaches being developed to treat spinal cord injury, including biological, technological, and pharmaceutical strategies. Through this project, the student will build research and critical thinking skills by learning how to gather information from scientific articles, company websites, clinical trial databases, and news sources. They will practice summarizing complex scientific information in their own words and organizing it into clear categories. The final review article will include: • An overview of the major therapeutic approaches (e.g., stem cells, gene therapy, biomaterials, rehabilitation devices) • A list of companies and organizations developing therapies for spinal cord injury • Categorization of each company’s therapy into the appropriate approach type • A description of the stage of development for each therapy (preclinical, clinical trial phases, or approved use) The outcome of this project will be a written review paper that organizes and explains the different categories of spinal cord injury therapies, highlights key companies, and discusses the current state of progress in this field. This final product will not only improve the student’s research and writing abilities but also provide a comprehensive snapshot of how science and industry are working together to tackle a challenging medical problem.
Biotech, Neuroscience
Modeling and Observing Crystal Structures
Students could explore how atoms arrange themselves in different crystal structures and how this affects material properties. They might build 3D models of simple structures like cubic, hexagonal, or tetrahedral lattices using balls and sticks, marshmallows, or LEGO bricks. They could also investigate how packing efficiency relates to density or how defects in the structure might influence strength. For a hands-on twist, students could compare crystals formed from salt, sugar, or other household substances under different conditions, observing shapes, sizes, and growth patterns. This project introduces fundamental concepts in materials science while combining modeling, observation, and experimentation.
Engineering
Fracture Mechanics of Food Items
In this project, students could explore how different foods break, crack, or deform under stress. For example, they might measure the force needed to snap a cookie, crush a carrot, or bend a chocolate bar, and analyze how texture, moisture content, or shape affects the results. Students could design experiments using simple tools like weights, clamps, or household presses, and record observations to connect material properties to fracture behavior. This project introduces concepts from materials science—like stress, strain, and toughness—in a fun and accessible way, while encouraging hands-on experimentation and data analysis.
Engineering
Protein Modeling Using AI
AI has revolutionized the protein structure game! This project leverages AlphaFold, an advanced deep-learning tool for protein structure prediction, to investigate the 3D conformations of target proteins of interest. By inputting amino acid sequences of a protein of interest to you, AlphaFold generates accurate models of protein folding, which we will analyze to identify key features. The results will support hypotheses about protein function and guide follow-up experiments such as mutagenesis. Ultimately, this project aims to connect sequence information to biological mechanism by integrating computational predictions with experimental validation.
Biology
A Mobile Application that can Help Reduce Patient Risk of Negative Outcomes
There are multiple scoring tools that clinicians utilize to access the risk of patients in certain disease condition. What if we create an app that has some of these tools that are patient-friendly? This way patients can navigate these tools and get an understanding of what their risk are for certain conditions and that they may need to eat more healthy, be sure to be adherant to their medications, or seek medical attention.
Cancer, Medicine, Healthcare
Addressing Common Barriers to Patient Access to Medications
There are plenty of scenarios where patients are not able to access ideal therapies for their survival from insurance issues to product backorder. Explore some of these barriers and provide a guide on how healthcare professionals can navigate around these issues.
Cancer, Medicine, Healthcare
Promising role of Antibody-Drug Conjugates (ADCs) in Cancer Treatment over Traditional Chemotherapies
Research the mechanisms and the promising patient trial data of how and why ADCs provide a promising therapeutic approach compared to the non-specific cytotoxic chemotherapeutics. The final product should be a review research paper that can be published.
Cancer, Medicine, Healthcare
Building an AI-Powered Personal Investment Research Assistant: Multi-Agent System for Teen Financial Literacy
In this project, students will develop a sophisticated AI-powered investment research assistant designed specifically for young investors and financial literacy education. This hands-on project combines cutting-edge artificial intelligence with practical financial knowledge, creating a system that can help teenagers make informed decisions about their first investments while learning fundamental market concepts. What Students Will Build Students will create a multi-agent AI system using modern frameworks like OpenAI's Agent SDK or CrewAI that includes: Research Agent: Automatically gathers and analyzes company financial data, news sentiment, and market trends Risk Assessment Agent: Evaluates investment risk levels appropriate for young investors with limited capital Educational Agent: Explains complex financial concepts in teenager-friendly language Portfolio Tracker: Monitors simulated investments and provides performance insights Learning Objectives By the end of this project, students will: Understand how modern AI agents work and collaborate Learn fundamental investment principles and financial literacy concepts Gain hands-on experience with Python programming and API integration Develop skills in data analysis and visualization Create a practical tool they can actually use for their own financial learning Technical Skills Developed AI/ML Frameworks: OpenAI API, multi-agent orchestration, natural language processing Programming: Python, async programming, API integration Data Analysis: Financial data processing, sentiment analysis, trend identification Web Development: Building user interfaces with Gradio or similar frameworks Cloud Deployment: Deploying applications to platforms like HuggingFace Spaces Project Scope & Timeline This 8-12 week project is designed to be challenging yet achievable for motivated high school students: Weeks 1-3: Foundation building - Learn AI agent concepts, set up development environment, understand financial markets basics Weeks 4-6: Core development - Build individual agents for research, analysis, and risk assessment Weeks 7-9: Integration & testing - Connect agents into a collaborative system, implement safety guardrails Weeks 10-12: Enhancement & deployment - Add user interface, deploy to cloud platform, create project documentation Real-World Impact This project addresses the critical need for financial literacy among teenagers. According to recent studies, only 21 states require high school students to take personal finance courses. The AI assistant students build will: Help peers make informed decisions about their first investments Serve as an educational tool for learning market concepts Demonstrate how AI can be used responsibly in financial decision-making Provide a foundation for understanding algorithmic trading and fintech Sample Research Questions Students will explore questions such as: How can AI agents be designed to promote responsible investing among young people? What safeguards should be built into AI financial tools to prevent risky behavior? How effective are AI-generated explanations compared to traditional financial education? What types of investments are most suitable for teenagers just starting their financial journey? Deliverables Fully functional multi-agent AI investment research system Research paper documenting methodology, findings, and lessons learned Public deployment of the application for peer testing and feedback Presentation suitable for science fairs or academic conferences Prerequisites Basic programming experience (Python preferred but not required) Strong interest in both technology and finance Willingness to learn complex technical concepts Access to a computer capable of running Python development tools This project uniquely combines the excitement of cutting-edge AI technology with practical financial skills that students will use throughout their lives. It's designed to be both educational and personally valuable, giving students a head start in both technological literacy and financial responsibility.
AI/ML, Computer Science
