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Browse project ideas by Polygence mentors
Snooze Time, For What? How Sleeping Less Than Eight Hours Affects the Adolescent Brain and Body
Areas of guidance for this project include neuroscience, sleep, adolescent brain development, learning and memory, and mental and physical health. Adolescents aged 13 to 18 are recommended to sleep 8 to 10 hours a night, yet many regularly sleep less than 8 hours on school nights. In this project, the student reviews the research on what happens when adolescents fall below that minimum, and asks which effects are most consistently supported, which are still debated, and why getting enough sleep can be especially difficult during the teenage years, when the body clock naturally shifts later but school often starts early. The student will learn how sleep supports memory consolidation, attention, and emotional regulation, and how to read and compare scientific studies critically. They will build skills in searching research databases, defining clear criteria for which studies to include, organizing findings from many sources, and distinguishing strong, repeated evidence from a single interesting result. Information gathering will be a structured review of published research and trusted health sources. The student will search for studies on adolescent sleep duration and outcomes, screen them against criteria they set in advance, and sort the findings into areas such as learning and school performance, mood and stress, physical health and metabolism, and safety, including sports injuries and drowsy driving. They will also note differences in study design, sample size, and how sleep was measured, since self reported sleep and device measured sleep do not always agree. The student will finish with a scientific review paper or poster that synthesizes the evidence on sleeping less than 8 hours, a summary table comparing the main effects and the strength of evidence for each, and an infographic for fellow students that explains, in plain language, why sleep matters for the teenage brain and what the research actually shows.
Neuroscience
Friend, Foe, or Both? The Two Faces of Zinc in the Nervous System
Areas of guidance for this project include neuroscience, neurochemistry, and brain health, particularly how the brain tightly regulates essential trace elements and what happens when that balance is lost. Zinc is necessary for normal brain function, yet its effects depend strongly on amount, location, and timing. In this project, the student investigates zinc as a double edged sword in the brain. Too much zinc released during intense neuronal activity can contribute to excitotoxic injury, while too little zinc can interfere with processes linked to neurogenesis, DNA repair, and cellular defense. The student asks how the same element can be both protective and damaging, and what determines which outcome occurs. The student will learn how neurons communicate, how the brain maintains chemical balance, and how scientists weigh evidence when studies appear to point in opposite directions. They will build skills in reading primary research, comparing experimental models, organizing findings by zinc level, brain context, and outcome, and explaining a complex idea accurately to a non specialist audience. Information gathering will center on a structured review of published studies in cells, animals, and humans. The student will record the source of zinc, the amount or condition studied, the brain region or process affected, and whether the reported effect was beneficial, harmful, or dependent on context. The student will finish with a scientific review paper or poster and an original evidence map or visual model showing where zinc supports brain health, where it becomes harmful, and what questions remain unresolved.
Neuroscience
Can we love AI?
This project would focus on the ethics of relationships and artificial intelligence. We will read and discuss the work of philosophers who work on personal identity, relationship ethics, neuroscience, and AI. We will discuss what it would mean to love an AI agent, and whether an AI agent could love a human being. We will evaluate some of the ethical consequences of these issues. Students will have the option to evaluate these ideas with respect to familial relationships (can we replace parents or children with AI?), friendships, or romantic relationships. Alternatively, we could evaluate whether certain social/work relationships like teachers, mentors, therapists, or pets etc. could effectively replace human relationships of the same kind, and what the ethical outcomes of those might be. This project type would not involve any coding, nor a strong background in computer science or artificial intelligence. These ideas will be evaluated through a philosophical lens. The outcome of this project will be a research paper aimed at a high school academic journal.
Philosophy
Modern Technology's Impacts on the Environment and the Effectiveness of Renewable Energy Systems
In this project, I mentored a student in exploring how different methods of electricity production affect the environment and how we can reduce carbon dioxide (CO₂) emissions. We investigated renewable energy technologies, carbon capture methods, and emerging solutions for reducing greenhouse gases. A key part of the project was comparing the environmental benefits, costs, and energy requirements of different approaches to understand which solutions are the most practical and sustainable. This project is a great opportunity for students interested in climate change, renewable energy, and engineering to explore real-world environmental challenges, analyze scientific research, and identify promising technologies that could help build a cleaner future.
AI/ML, Engineering, Computer Science, Business
Developing a Novel Robot Localization Algorithm Using Low-Cost Sensors
In this project, I mentored a student who found a simpler way for robots to track their location using everyday low-cost sensors. Traditional methods often need careful measurements of wheel positions and still struggle with sideways drift. My student showed that for certain wheel setups those measurements aren’t necessary, then built a clean arc-based algorithm that reconstructs the robot’s path while naturally correcting for drift. The results were strong enough that we turned the work into a research article, which has been submitted to a journal for publication.
AI/ML, Engineering, Computer Science, Business
The Psychology of Everyday Decisions: Understanding Human Behavior Through Research
Why do people follow social norms even when they disagree with them? How does social media influence self-perception? Why do people procrastinate, make impulsive decisions, or struggle to prioritize their own well-being? Everyday human behavior is full of interesting psychological questions, and this project gives you the opportunity to investigate one of them. You'll explore established theories in cognitive psychology, social psychology, and behavioral science to understand how people make decisions, form attitudes, respond to social pressure, and interact with others. Potential topics include conformity, persuasion, social identity, cognitive biases, motivation, moral judgments, self-control, and the psychology of health and well-being. Depending on your research question, you may conduct a literature-based investigation, analyze existing datasets, or develop a survey or experimental study to explore a psychological phenomenon. I'll help you formulate testable hypotheses, develop an appropriate research design, analyze findings, and communicate your results through an academic research paper. This project is ideal for students interested in psychology, neuroscience, sociology, behavioral science, and understanding why people think and behave the way they do.
Statistics, Psychology, Business
Modeling a Flexible Surgical Needle That Bends Toward Its Target
Many surgeries and biopsies take place deep inside the body, where a straight, rigid needle simply cannot reach without damaging healthy tissue along the way. This project explores how steerable needles and catheters solve that problem: by taking advantage of an asymmetric bevel tip and carefully timed rotation, a flexible instrument naturally curves as it advances, allowing it to arc around obstacles toward a target. Working in surgical robotics and medical device mechanics, the student will investigate how factors such as bevel angle, insertion speed, rotation pattern, and tissue stiffness influence the curvature of the needle's path and the accuracy with which it reaches its target. The student will learn Python programming, the basics of mechanics and geometric modeling, and how to run controlled simulation experiments, varying one parameter at a time and recording how the trajectory responds. The process begins with a survey of image-guided surgery and needle-steering research, moves through building and validating a simulation model against published experimental data, and finishes with an analysis of which design and control choices most improve targeting accuracy. The final outcomes are a working trajectory simulation, a quantitative study of the parameters that govern steering, and a scientific research paper presenting the findings.
AI/ML, Computer Science
Computer Vision for Autonomous Obstacle Avoidance
A drone flying on its own has no pilot's eyes, so it must build its understanding of the world from cameras and learn to react in fractions of a second. This project explores how computer vision allows a drone to perceive its surroundings and navigate safely without human control. Working in aerial robotics and machine perception, the student will study how a drone can detect and track obstacles, estimate its own motion from video, and make simple decisions such as stopping, detouring, or following a target. The student will learn Python programming, the fundamentals of image processing and object detection, and how to train and evaluate a small computer-vision model on aerial imagery, then test it inside a drone simulator where crashes are free. The process begins with a survey of how autonomous drones sense and plan, continues with building and benchmarking a detection model, and culminates in integrating that model into a simulated flight in which the drone must navigate a course while avoiding obstacles. The final outcomes are a working simulated autonomous flight demo, quantitative results on detection accuracy and navigation success, and a scientific research paper presenting the full study.
AI/ML, Computer Science
Designing a Tendon-Driven Prosthetic Hand: How Cable Routing Shapes Grip Strength and Motion
Modern prosthetic hands must solve a difficult trade-off: they need to be strong enough to hold everyday objects, gentle enough not to crush them, light enough to wear all day, and simple enough to be affordable. This project explores how tendon-driven mechanisms, in which cables pulled by a small motor flex the fingers much like the tendons in your own hand, can meet those demands. Working in prosthetics and biomechatronics, the student will investigate how design choices such as tendon routing, pulley placement, and joint stiffness affect a prosthetic finger's range of motion, fingertip force, and ability to conform to objects of different shapes. The student will learn foundational mechanics and kinematics, Python programming, and how to build and run physics simulations of a tendon-driven finger, systematically varying one design parameter at a time and measuring the results. The process begins with a survey of how natural and prosthetic hands achieve grip, moves into modeling and simulation experiments, and, if time and resources allow, can extend to a simple 3D-printed prototype finger tested against the simulation's predictions. The final outcomes are a quantitative comparison of competing designs, a working simulation (and possibly a physical prototype), and a scientific research paper presenting the design study.
AI/ML, Computer Science
Teaching a Simulated Robot Arm to Learn from Demonstration
Robots are remarkably good at repeating exact motions and remarkably bad at handling the messy variability of the real world, and this project explores how learning from human examples can close that gap. Working in robot learning and imitation learning, the student will use Python and the MuJoCo physics simulator to study how a robot arm can acquire a manipulation skill, such as picking up and placing objects, from recorded demonstrations rather than from hand-written rules. Along the way, the student will learn to program a simulated robot, design a simple teleoperation interface, collect and clean demonstration data, train a small neural network policy, and evaluate it rigorously by measuring success rates and cataloguing how and why it fails. The student will begin by surveying recent research on imitation learning, then move through data collection, model training, and iterative testing, keeping a research log throughout. The final outcomes are a working simulation demo in which the robot performs the learned skill, a set of quantitative results comparing performance across conditions, and a scientific research paper presenting the full study.
AI/ML, Computer Science