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Browse project ideas by Polygence mentors
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
Use machine learning techniques to classify exoplanets based on their potential habitability.
This project would use existing datasets from missions like Kepler and TESS, which contain information about known exoplanets (e.g., orbital radius, star type, size, and temperature). The student can train a machine learning model to classify exoplanets based on their habitability potential. They could use criteria such as the planet's location in the habitable zone and properties like temperature and mass to predict habitability.
Physics, Math, AI/ML
Explore the workings of basic quantum algorithms and simulate their behavior on a classical computer.
Quantum algorithms like Grover's search algorithm or the Deutsch-Josza algorithm are fundamental to understanding quantum computing’s potential. This project would involve coding and simulating these algorithms using Python libraries like Qiskit or Cirq. The student could analyze the efficiency of these algorithms by comparing their simulated performance with classical equivalents.
Physics, Math, AI/ML
Evaluating technologies for the production of potable water from atmospheric water vapor
Water scarcity is one of the biggest problems faced in underdeveloped countries and communities. A shortage in the water supply and/or a method to deliver it to homes/villages easily leads to health issues. However, there exists a solution to this issue that can be used anywhere. Solutions can include direct condensation, physical adsorption, chemical absorption etc. The goal of this project would be to evaluate existing and upcoming atmospheric water technologies and summarize in a review article.
Physics, Engineering, Chemistry
Evaluating the risk-to-reward relationship for implementation of Pb-based Perovskite Solar Cells
In recent years, there has been interest in alternative energy sources, as a result of the detrimental impacts that non-renewable energy sources, such as petroleum and coal, have on the environment (i.e. global warming). Photovoltaics has been the leading technology in the drive for sustainable energy sources. It has been predicted that by 2050, wind and solar harvesting technologies will make up close to 50% of the world energy electricity. Solar cells comprising perovskite active layers have been one of the most widely researched photovoltaic technologies in recent years, experiencing the fastest rise in power-conversion efficiency (PCE) of any emerging solar cell technology. Compared to traditional Silicon-based solar cells, perovskite-based solar cells have a smaller materials cost, are able to be processed at ambient temperatures and typically have low, direct and tunable bandgaps. Additionally, while perovskite-based cells have not been able to surpass Silicon-based ones in terms of PCE, tandem solar cells containing both Silicon and perovskite have continued to break records for PCE. The main drawback of perovskite solar cells is that the best forming perovskite chemistries are Lead (Pb)-based. While there are methods available to encapsulate solar cells, commercial implementation of this solar cell technology will come with an inherent risk due to the high toxicity of Pb0. The goal of this project is therefore to evaluate the risk-to-reward relationship for commercial implementation of Pb-based perovskite solar cells. The risk-to-reward relationship may look different for developed countries like the USA versus underdeveloped countries where cheaper solar cell technologies may be more beneficial and desirable.
Physics, Engineering, Chemistry
Evaluating technologies for remove of excess carbon dioxide from the atmosphere and/or prevent its release
In 1980 the global carbon dioxide concentration in our atmosphere was close to 340 ppm. Since then, the concentration of carbon dioxide has rise to roughly 420 ppm. The Earth receives warmth from the Sun via radiation, absorbing the EM waves to produce heat. However, the earth also releases radiation into space, a process that regulates the Earth's atmospheric temperature, however, the excess carbon dioxide in our atmosphere acts as a blanket to shield the EM waves sent towards space, deflecting them back to Earth. This process has led to a steady increase in atmospheric temperature - global warming, something we all should be familiar with. There are currently a myriad of effects aimed at reducing and reversing the effects of global warming and climate change, the goal of this project would be to evaluate all the available and upcoming technology related to carbon capture and summarize findings in a review article. This will entail searching for and reading published scientific articles, extracting relevant information while expanding your knowledge and curating an article that evaluates carbon capture technology. Being able to review and write scientific literature will be a valuable skill in college and beyond.
Physics, Engineering, Chemistry
Aerodynamics of F1 Race Car
The aerodynamics of F1 cars project immerses students in the exciting world of automotive engineering and aerodynamics. By building an RC car from scratch and 3D printing the body, students will gain valuable skills in mechanical design, additive manufacturing, and hands-on assembly. They will have the opportunity to test various aerodynamic features in a homemade wind tunnel, allowing for practical experimentation and data collection. Additionally, using simulation software to validate and compare results will enhance their understanding of fluid dynamics and computational modeling. This project not only cultivates critical thinking and problem-solving skills but also encourages collaboration and innovation, providing a solid foundation for future pursuits in engineering and technology.
Engineering
Remote Controlled Robotic Arm
The 6-axis robotic arm project provides students with an engaging opportunity to explore robotics and programming. By building and programming the arm using Arduino, students will learn essential skills in electronics, coding, mechanical design, and 3D printing. They will also gain hands-on experience with mobile app development, as the robotic arm will be controlled via a user-friendly phone interface, allowing for real-time input and manipulation. This project fosters problem-solving abilities and creativity while introducing students to concepts such as servo motor control, sensor integration, and the fundamentals of automation.
Engineering