WILSON B. YU
My name is Wilson. I'm a senior at Carnegie Mellon University studying Information Systems, Human-Computer Interaction, and Statistics. My personal and professional interests include programming, data science, and human behavior. Having grown up drawing way too much, I'm also an avid fan of visual art and design. You can see some of my work here.
| yu.wilson.b@gmail.com | |
| Phone | 240-543-9080 |
| Location |
Rockville, MD Pittsburgh, PA |
| Bachelor of Science | Information Systems |
| Minors |
Human-Computer Interaction Statistics |
| Expected Graduation | December 2019 |
| GPA | 3.93 |
| Distinctions |
Dean's List with High Honors (5x) Dean's List (1x) |
Over the summer, I worked on Capital One's Continuous Improvement team to build tools to streamline their workflow. As the only software engineer on a team of business coaches, I learned a lot about the business's objectives and inner workings while introducing the team to new technical possibilities.
First, I learned about what the team did, observed how they did their work, and discussed with the team to identify where I could help them. A lot of their work involved manual data retrieval, manipulation, and visualization, so I wrote scripts to automate these processes. These scripts save the teams numerous hours every month.
To allow lay users to interact with these scripts, I designed and developed a web interface so that the team could more easily use them.
I also helped the team connect to previously inaccessible data sources and wrote queries to calculate new useful metrics, enabling the team to analyze the organization's performance in a new light.
Last year, I worked on an agile development team with other interns to develop an internal full-stack web application for processing financial data.
I helped in designing and implementing tables and stored procedures in SQL and connecting the database to a Java backend. Then, I worked on implementing ETLs to clean and transform data, before creating RESTful web services to send data to the front-end. Using the React framework, I helped build the user interface for users to perform CRUD operations, and added functionalities like authentication.
During my studies at Carnegie Mellon, I've been a teaching assistant for two courses: Matrix Algebra with Applications and Methods for Statistical Data Science, helping with grading and holding office hours.
In Matrix Algebra, I taught a weekly recitation that was mostly focused on how to solve computational problems and write simple proofs. Topics included vector spaces, orthogonality, real and complex eigenvalues and eigenvectors, linear transformations, the invertible matrix theorem, and more.
In Methods for Statistical Data Science, I assisted during lab sessions, aiding students in using R to visualize and model data, and answering questions about statistical techniques such as analysis of variance and simple, multiple, and logistic regression.
Whenever I'm not at school, I'm usually working with my dad, who is a contracter. I'd been tagging along to his job sites since I was just a kid, but only recently have I developed the gains1 (and brains2) to actually help him in home renovations and repairs.
Mostly, I paint walls, assemble things that involve screws, and haul a lot of heavy stuff around. I've also been learning about carpentry, electrical wiring, plumbing, and, of course, which aisle things are located at the local Home Depot.
1 The existence of the gains are debatable, but I like to believe I have them.
2 Also debatable.
Engee is a simple machine learning sandbox web application. With an easy-to-use interface that guides the user through choosing the right machine learning model, engee was designed to enable non-programmers to get their feet wet in machine learning.
Users can upload a dataset and choose the features and techniques they would like to use, and engee will return several metrics, output the code that was used to run the machine learning, and allow users to make predictions.
Using a recommendation system, latent semantic analysis, and decision trees, Schedulize finds the right courses for each CMU student based on the students' current schedules, past academic record, and their preferences.
