YUHAN WANG
Building Java/Spring Boot systems, REST APIs, and data-driven applications.
Currently building a lightweight RPC framework from scratch in Java.
About
Before moving into software engineering, I worked in urban planning, where I used GIS data and supported projects from field surveys through final submissions. Over time, I became more interested in the systems behind the tools I was using.
I am now completing an MSc in Computer Science at University College Dublin. I primarily build with Java and Spring Boot, focusing on backend systems while also contributing across the full stack.
I care about readable code and understanding the design decisions behind the systems I build.
Skills
Technologies and tools I work with
Java
Python 3
JavaScript
Spring Boot 3
Flask
Spring MVCSpring Data JPA
Hibernate
Maven
Docker
Jenkins
GitHub Actions
AWS (EC2/S3/RDS)
Hetzner
Nginx
Linux/Unix
Bash Shell
JUnit5
Git
HTML/CSS
React.jsProjects
Selected work and side projects
Multi-tenant food ordering platform for campus canteens. Dual-token JWT auth, Stripe payments with webhook-driven order state machine, role-based access with ownership-level authorization. Deployed via Jenkins CI/CD + Traefik on Hetzner Cloud.
Real-time bike availability predictor for Dublin's bike-share network. Flask/React, containerized and self-hosted on Hetzner behind Traefik, self-hosted MySQL, ~93% test coverage. Built with a 3-person team (COMP30830); I owned the database schema, data pipeline, backend integration, deployment architecture, and test suite.
Custom RPC framework built from scratch in Java. Handles dynamic proxy generation, custom serialization, and service invocation over a pluggable transport layer.
Ride-sharing app that matches riders heading the same direction in Manhattan to split taxi/rideshare costs. Predicts real-time demand and fares using NYC TLC trip data, with an AI chat assistant for ride and destination recommendations. Built with a 6-person team (COMP47360); I owned the ML layer — training and serving the demand forecasting and fare prediction models — contributed to the FastAPI backend, and shipped the AI chat assistant using the native OpenAI API.
Activity
Contact
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