Hello, I'm
Yinfeng Lu.
former math grad
current CS student
future software engineer
about
Before I started coding, my journey began with a professional grounding in mathematics, specializing in a field known as algebraic topology. Yet, as I delved deeper into my studies, I couldn't shake the nagging feeling that the theoretical knowledge I was acquiring might never find practical application.
Eager to make a tangible impact, I started to teach myself computer science, all while diligently pursuing my mathematics degree. Fortunately, I discovered a wide range of transferrable skills, coupled with an aptitude for fast learning. Putting my knowledge to test, I achieved an A+ in a graduate-level medical image analysis course — an early milestone in my coding odyssey. Further enriching my skill set and gaining real-world experience, I also joined a bioinformatics research lab.
I am currently studying computer science at the University of Chicago. I will graduate in December, 2024.
In my spare time, I enjoy reading novels, travelling, and learning foreign languages!
experience
2023.09 ‐ present
University of Chicago
M.S. Computer Science
2021.08 ‐ 2023.05
University of Pennsylvania
M.A. Mathematics
2022.01 ‐ 2023.05
Thesis Research
2022.08 ‐ 2023.05
Shen Lab – Perelman School of Medicine
Research Assistant
2018.01 ‐ 2021.05
University of California, Berkeley
B.A. Mathematics
B.A. Physics
2019.01 ‐ 2019.07
Experimental CMB Cosmology Group – Departments of Physics & Astronomy
Research Assistant
skills
languages
- C/C++
- Python
- Java
- JavaScript
- HTML
- CSS
- SQL
frameworks
- Flask
- React
- Qt ‐ C++
- PyTorch
- Boto3
development tools
- Git
- Linux
- Makefile
- JUnit
- Redis
- MongoDB
- Amazon Web Services
relevant courses
- Algorithms & Data Structures
- Databases
- Artificial Intelligence
- Medical Image Analysis
- Computer Architecture
- Cloud Computing
- Software Engineering
- Networks
- Web Development
- OO Architecture Patterns
projects
Featured Projects
Genomics Annotation Service
Genomics Annotation Service (GAS) is a distributed SaaS application deployed on Amazon Web Services (AWS), featuring a frontend server, a backend server, and a utility server. It facilitates file submission, file annotation, job tracking, and result file retrieval. GAS offers tiered user access (free & premium), with corresponding service distinctions. Free users have the option to upgrade to premium (via the Stripe test API). Inter-server communication adheres to the observer design pattern.
Cytometry Autogating Pipeline
While working at Shen Lab (Perelman School of Medicine, UPenn), I contributed to the development of a Cytometry Autogating Pipeline — an automated mass-cytometry data preprocessing solution. Utilizing a U-net-based neural network, we trained the system to filter out erroneous data stemming from defective equipment during data collection. This fully automated pipeline significantly reduces processing time compared to manual plotting and gating method. Users simply input the raw CSV file, and the pipeline generates a gated CSV file along with a comprehensive plot report.
My Responsive Personal Website
After learning HTML, CSS, and JavaScript, I independently constructed my responsive personal website. Each component and effect was carefully worked out using pure CSS and JavaScript, without the assistance of any libraries or frameworks. This project served as a cornerstone for my skills in frontend web development.
More Projects
LAN Connect
A local area network (LAN) communication application facilitating private messaging and file exchange over a TCP connection. It also incorporates modern features like typing status and availability indicators.
Sticky Notes
A simple desktop application that mimics the functionalities of the sticky notes application on Windows 11. I wrote it for my low-spec Linux laptop. It features a minimalist and modern UI.
Berkeley Map
I implemented the backend for a map application centered around the Berkeley (CA) area. It supports raster maps rendering, navigation calculating, and location searching.
contact
Let's get in touch!
Please feel free to send me an email using the form. Alternatively, you can send me a message on LinkedIn. I will get back to you as soon as possible!