Shinya K
- Research Program Mentor
MS at University of Pennsylvania
Expertise
Applied Physics, Applied Math, Mechanical Engineering, Data Science, and Machine Learning
Bio
Hi! My name is Shinya, and I'm currently a Wind Engineer in the Civil/Design Engineering Space. My passion in research is understanding patterns in the real world and applying them to real-life application. During my graduate studies, I carried out research to identify patterns in small-scale fluid structures to more accurately + efficiently simulate wind flows around building structures. My background is in Mechanical Engineering and Applied Mathematics, and I like to use both Data and Governing Equations from Physics to understand the world around us and to shape a more sustainable world. Outside of work/research, I enjoy exploring the art scene in NYC, reading, and also crafting. I have recently been using my 3D printer to build a scaled model of NYC and have been learning a lot of interesting facts about the unique buildings in the city.Project ideas
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.