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Browse project ideas by Polygence mentors
The Role of Technology in Enhancing Student Engagement
This project invites students to explore how technology tools can boost student engagement and improve learning outcomes in the classroom. Students will research current educational technologies and gather feedback from educators through surveys or interviews to evaluate their effectiveness. The outcome may be a detailed report assessing specific tools or the creation of a workshop module aimed at training teachers on integrating technology to enhance classroom engagement.
Linguistics, Finance
Exploring Bilingualism and Cognitive Development
Students will investigate the cognitive benefits of bilingualism, examining how learning multiple languages influences cognitive development and problem-solving abilities. Through literature reviews and interviews with bilingual individuals, students will gather insights and data on the relationship between bilingualism and cognitive skills. The project will culminate in a research paper or presentation outlining the findings and implications of bilingualism on cognitive development.
Linguistics, Finance
Analyzing the Impact of Financial Decision-Making in Banking
This project invites students to investigate the financial decision-making processes within the banking sector, using my extensive experience as a financial analyst at Standard Chartered Bank as a foundation. Students will explore how various factors—such as market conditions, regulatory changes, and economic indicators—affect the financial strategies of banks. Through literature reviews and case studies based on historical decisions made by banks, students will analyze the outcomes and implications of these decisions. The final outcome may be a comprehensive research paper or a presentation that highlights key findings, successful strategies, and critical lessons for aspiring financial analysts.
Linguistics, Finance
Identifying reproducible biomarkers for early stage lung cancer using microRNAs
Overview: MicroRNAs are popular candidate for biomarkers for cancer, because they can be easily measured in blood. However, there is a reproducibility problem in the field and some promising microRNA biomarkers found in a single dataset do not replicate when applied to other populations. Can we identify our own biomarker candidates with machine learning and then assess how well they reproduce in external datasets? If they don't replicate, what factors are associated with the lack of replication? Knowledge/Skills: - RNA-seq analysis - Feature selection methods - Machine learning classification - Cross-validation techniques - Statistical association testing Skills needed: - Basic coding skills in Python or similar programming language - Basic statistics knowledge - Introductory genetics knowledge - Experience with data visualization Expected Outcomes: - Panel of 5-10 blood-based RNA biomarkers - Classification model with performance metrics - Replication statistics - Academic paper - Github repository Possible extensions: - Developing deep learning or transfer learning models - Generalizing to other datasets - Incorporating genetic risk scores to models - Incorporating population genetics theory to models
AI/ML
Finding novel disease-related variants in founder populations
Overview: Founder populations are populations who experienced a historical bottleneck, which results in less genetic diversity in modern day individuals. This can mean genetic variants that cause disease are at higher frequencies than what might be expected from evolutionary theory. In this project, we can identify a public dataset that might contain founder populations. Then, we can use population genetics algorithms to model the population history and search for potentially pathogenic variants. Knowledge/Skills to be learned: - population genetics algorithms, like identity-by-descent analysis - classifying genetic variants based on pathogenicity - statistical association testing Skills needed: - Intermediate to advanced coding skills in Python or similar programming language - Basic statistics knowledge - Introductory genetics knowledge - experience with the command line a plus Expected Outcomes: - Map of disease-associated genetic segments - Potential novel variant discoveries - Documentation of population-specific risks - Academic paper - Github repository Possible extensions: -Create visualization tools or web interfaces - Optimize computational efficiency of existing tools - Compare with ancient DNA - Analyze natural selection effects
AI/ML
Cybersecurity Awareness and Digital Safety Practices: Protecting Teens from Online Financial Risks
This project focuses on educating teenagers about the importance of cybersecurity in managing their online presence and financial activities. Students will design an interactive educational campaign that includes real-world scenarios, quizzes, and case studies. The project involves researching common online financial threats, surveying students' awareness levels, and developing a toolkit or curriculum to promote digital safety. The final deliverable can be a digital or physical product aimed at high school audiences.
Finance
AI-Powered Tools for Financial Literacy: Enhancing Decision-Making for Students and Young Professionals
This project investigates how AI-powered financial tools, such as budgeting apps and debt management platforms, can improve financial literacy among students and young professionals. Students will evaluate existing tools, identify gaps in usability or accessibility, and design a framework for an AI-driven solution to bridge these gaps. This project emphasizes the practical application of machine learning concepts and involves a combination of qualitative and quantitative analysis to assess user needs and tool effectiveness.
Finance
J.S. Bach's 30 Inventions
Johann Sebastian Bach, a composer from the Baroque era, famously wrote 15 Inventions to be used as a piano exercise tool for young students to increase finger mobility and strength. The 15 inventions are written in eight major and seven minor keys. In classic music theory, it is known that there are 30 keys in total (15 major and 15 minor). In this project, the student will be working on extending J.S. Bach's 15 Inventions to have an Invention for each of the 30 keys using data science and machine learning. The students will be in charge of carrying out a literature review for current algorithms for data-driven musical compositions, collecting + cleaning the data, writing an algorithm to create the neural network, and writing a final report that discusses their findings of the project. I will assist the student on the technical aspects of the project while also guiding them through the research workflow as a mentor. There will be hand-holding through the advanced portions of coding using my previous research experience in machine learning to build wind simulation results. The students will learn how to code in Python, some music theory, basic machine learning techniques, and also the workflow of starting and completing the research project.
Physics, Engineering, Math
Blockchain for Sustainable Supply Chains: Tracking and Transparency
This project explores how blockchain technology can enhance transparency and efficiency in global supply chains, with a specific focus on sustainability. Students will research how blockchain can provide real-time tracking of materials, verify the ethical sourcing of goods, and reduce waste in logistics by improving data transparency and trust across different stakeholders (e.g., suppliers, manufacturers, and consumers).
Business
Build and train a neural network model to identify gravitational wave signals in noisy data from sources like LIGO.
Gravitational waves are often hidden within large amounts of noise in observational data. The student could use publicly available gravitational wave datasets and apply deep learning techniques, such as convolutional neural networks, to detect the presence of these waves. This project could include data preprocessing, feature extraction, and model training and evaluation.
Physics, Math, AI/ML
