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Browse project ideas by Polygence mentors
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
Neuromorphic Computing
This project will introduce you to the field of neuromorphic computing, an area of research that designs computer systems inspired by how the brain processes information. You will explore how neurons and synapses can be modeled in hardware and software, and how these approaches are applied to problems such as sensory processing, robotics, and brain-computer interfaces. The project will involve reading and synthesizing recent scientific papers, with a focus on identifying the strengths, challenges, and future directions of neuromorphic systems. By the end, you will produce a short review article that summarizes your findings for a broad scientific audience. A more ambitious project could include neuron modeling, or applications of spiking neural networks.
AI/ML, Biotech, Neuroscience, Computer Science
Neuroengineering: Neural Interfaces, Neuroprostheses, and Brain-Computer Interfaces
This project will explore the field of sensorimotor brain-computer interfaces (BCIs), which are systems that allow the brain to directly control devices and receive feedback from them. You will study how BCIs can restore movement for people with paralysis or provide naturalistic sensation through neuroprosthetic limbs. The project will focus on reviewing recent scientific papers, comparing different approaches to recording brain activity and delivering feedback to the nervous system. By the end, you will write a short review article that highlights the current state of the field and discusses exciting future directions for sensorimotor BCIs. A more ambitious project could include modeling of neural interfaces, or analyzing neural data.
AI/ML, Biotech, Neuroscience, Computer Science
Experiment in Virtual Worlds
We can design a mini virtual reality experience that lets users explore a concept, environment, or phenomenon in an interactive way. For example, we might create a VR ecosystem where users can interact with animals and plants, a space station simulation to explore zero gravity, or even a tiny virtual city to test design ideas.
Animation, Game Design
