Here's a collection of projects I've worked on, from systems and web development to deep learning and compilers.
AWS DevOps CI/CD Security GitHub Actions Jekyll August 2025 - September 2025
In this project, I deployed melvyn-tan.com as a secure static website hosted on AWS. The site uses a private S3 bucket with CloudFront as the CDN, Route 53 for DNS, and ACM certificates for HTTPS. I set up logging, CloudTrail, and budgets for monitoring, and automated deployments first with AWS CodePipeline/CodeBuild before migrating to GitHub Actions with OIDC for long-term use.
Web Development React TypeScript Leadership Educational Technology April 2025 - Current
OCCTIVE is an NSF-funded initiative aimed at helping non-CS faculty introduce foundational computing concepts—such as variables and control structures—to students in non-computing courses. Many of these faculty are experts in their research fields but have no formal training in computer science and limited familiarity with the pedagogical challenges faced by introductory students. OCCTIVE addresses this gap by creating a curated video library that instructors can easily integrate into their teaching.
AWS Lambda Amazon ECR Docker Serverless July 2025 - August 2025
I worked on a containerized application to get familiar with running containers in AWS Lambda. The project involved building a Docker image, pushing it to Amazon ECR, and deploying it as a Lambda function using Lambda’s container image support.
AWS Cloud Computing Data Engineering Serverless Python June 2025 - August 2025
I built a clickstream ingestion pipeline on AWS to familiarize myself with real-time data processing and analytics. The project connected API Gateway, Kinesis Data Firehose, Lambda, S3, Athena, and QuickSight into a working architecture for transforming, storing, and visualizing clickstream data.
AWS Cloud Computing Event-Driven Architecture Serverless Python June 2025 - August 2025
I built an event-driven architecture on AWS to familiarize myself with core services and how they integrate to form scalable, serverless applications. The system simulated an order processing pipeline with notifications.
AWS Kubernetes Amazon EKS Docker DevOps July 2025 - August 2025
I worked on a containerized directory application to get familiar with Amazon EKS and Kubernetes on AWS. The project involved building Docker images, pushing them to Amazon ECR, configuring IAM policies, and applying Kubernetes manifests to deploy backend and frontend services on EKS.
Parallel Computing Automatic Differentiation OpenMP MPI Compiler Design March 2025 - June 2025
I extended a research compiler framework for automatic differentiation (AD) to support distributed execution across multiple cores using OpenMP and MPI. The goal was to allow users to define any numerical function, regardless of input dimensionality, and automatically generate C code that computes derivatives in parallel.
AWS Distributed Systems etcd Consensus DevOps June 2025 - July 2025
I set up a three-node etcd cluster on AWS EC2 to gain first-hand experience with distributed consensus, leader election, and fault tolerance. The project involved launching virtual machines, configuring firewall rules, installing etcd, and experimenting with cluster behavior under simulated failure conditions.
Deep Learning Music Generation Music Transformer Sequence Modeling PyTorch March 2025 - June 2025
I trained a Music Transformer from scratch to generate symbolic music using the POP909 dataset. The goal was to build a model capable of composing music by predicting the next token in a sequence of encoded musical events.
GPU Programming Triton Matrix Multiplication Deep Learning Optimization CUDA February 2025 - March 2025
In this project, I wrote a custom matrix multiplication kernel using Triton that fuses three operations—A @ B + C, followed by a ReLU activation—into a single GPU kernel. The goal was to outperform PyTorch’s high-performance cuBLAS backend by taking advantage of kernel fusion and manual tiling. My Triton implementation achieved a 1.4× speedup over the equivalent PyTorch function on fp16 tensors.
Distributed Systems Consistent Hashing gRPC Go SQLite Video Streaming April 2025 - June 2025
Distributed content delivery is critical to scalable systems like YouTube, especially when reliability and fault tolerance are required. TritonTube simulates this at a systems level, allowing videos to be uploaded, segmented using MPEG-DASH, and distributed across a network of storage nodes using consistent hashing. As part of a networking course, I built this application from the ground up in Go and achieving full functionality.
Transformers Deep Learning Automatic Differentiation Machine Learning Python January 2025 - March 2025
In this project, I built a Transformer model entirely from scratch, including both the architecture and the underlying automatic differentiation engine. I implemented everything using only Python and NumPy—without relying on PyTorch, TensorFlow, or any external ML libraries.
Ruby on Rails CSS Web Development Frontend Development November 2024 - February 2025
I contributed to an ongoing Ruby on Rails project for Stratax - Tax Strategist of America, where my primary task was to reskin the application to align with newly provided UI/UX designs. Since this was my first time working with Ruby on Rails, I started by learning the fundamentals of the framework, setting up the development environment, and resolving dependency issues to ensure the application ran smoothly on my local machine.
Wireless Networks Internet of Things LoRa Energy Modeling Systems Design Cost Analysis January 2025 - March 2025
As part of my Wireless Network Systems class, I designed a smart farming solution for a 40-acre plot of land in Malaysia. The goal was to modernize traditional farming methods using wireless sensors to monitor soil moisture and nutrient levels (nitrogen, phosphorus, potassium). Each sensor transmits 11 bytes of data twice a day—at 6am and 6pm—and undergoes firmware updates three times a year.
Recommender Systems Collaborative Filtering Matrix Factorization Factorization Machines Data Processing October 2024 - January 2025
Recommender systems are essential for platforms like Yelp, where users rely on personalized suggestions. In this project, I built a system to predict how a user would rate a business they haven’t visited, using real-world Yelp data.
GPT-2 NLP Summarization Token Optimization Prompt Engineering Deep Learning October 2024 - January 2025
Large language models like GPT-2 are powerful for summarization but can be expensive to use, especially when deployed via APIs where cost is based on token count. This project focused on reducing input token usage while maintaining—or even improving—summarization quality.
Parallel Computing Matrix Multiplication MPI Ghost Cells Domain Decomposition Strong Scaling Weak Scaling November 2024 - December 2024
Parallelizing numerical simulations requires efficient data exchange between processes, particularly for stencil-based computations like 2D wave propagation. In this project, I implemented ghost cell communication using MPI, allowing each process to exchange boundary data with its neighbors while minimizing synchronization overhead.
Parallel Computing Matrix Multiplication CUDA GPU Computing Shared Memory Tiling Warp Utilization October 2024 - November 2024
Matrix multiplication is a fundamental operation in high-performance computing, and optimizing it for GPUs requires an in-depth understanding of memory hierarchy, parallel execution, and warp scheduling. In this project, I implemented a highly optimized CUDA-based matrix multiplication kernel, leveraging 2D tiling, shared memory, and interleaved computation to maximize efficiency.
GPT NLP Transformers Attention Mechanism Language Modeling Deep Learning November 2024 - January 2025
Transformers are the foundation of modern NLP models, and for this project, I developed a GPT-style model from the ground up. My implementation included a Transformer Encoder for classifying political speeches and a Transformer Decoder for generating text in an autoregressive manner, following the same structure used in GPT models.
Parallel Computing Matrix Multiplication ARM SVE SIMD Tiling Cache Optimization Loop Unrolling September 2024 - October 2024
Matrix multiplication is a critical operation in high-performance computing, and optimizing it requires an in-depth understanding of memory hierarchy, vectorization, and instruction-level parallelism. In this project, I implemented an optimized DGEMM (Double-precision General Matrix Multiplication) routine that achieved significant performance improvements using ARM Scalable Vector Extension (SVE) intrinsics, hierarchical blocking, and memory packing.
Software Engineering UI/UX Design Documentation React TypeScript Database Mapping May 2024 - July 2024
Seamgen is a digital transformation company located in San Diego that specializes in full-stack custom application development services for web and mobile across all cloud platforms. During the first phase of my internship as a Software Developer, I was tasked with submitting a deliverable for the state of Florida’s Statewide Vulnerability Assessment (SVA). My primary responsibility was to create comprehensive documentation for a React-based web application used in the assessment.
SEO Web Performance Optimization Google PageSpeed Insights HubSpot Ahrefs Agile Jira Web Development July 2024 - February 2025
After completing the first phase of my internship, I transitioned into the second phase, where I joined Seamgen’s marketing team to focus on search engine optimization (SEO). This phase was dedicated to improving the performance and visibility of Seamgen’s website to attract more leads and potential clients. My work involved a combination of technical SEO optimizations, content improvements, and collaboration with other team members to enhance the overall user experience of the website.
Deep Learning Machine Learning PyTorch Research Image Processing March 2024 - September 2024
As a research assistant in the Machine Learning, Perception, and Cognition Lab at UCSD, I work under the supervision of PhD student Zeyuan Chen and Professor Zhouwen Tu. My research focuses on deep learning techniques for image processing, where I have reproduced results from state-of-the-art papers like Re-Confusion, PixelSplat, and NeRF. These projects have provided me with practical experience in implementing novel techniques and debugging complex models.
Machine Learning Unsupervised Machine Learning Python Scikit-Learn March 2024 - June 2024
In this project, I classified songs into distinct genres using the Spotify 1.2M+ Songs dataset. The goal was to group songs based on shared musical features such as danceability, tempo, acousticness, and valence. I hypothesized that songs within the same genre would exhibit similar patterns in these variables.
Backend Development MongoDB Mongoose RESTful APIs Express.js Authentication Web Development Jira May 2023 - July 2023
I worked on RoomEase, a platform that simplifies room rentals, where I focused on backend development. I designed and implemented data schemas using Mongoose and managed the database with MongoDB to store and retrieve user and room information. I also built RESTful APIs with Express.js to allow for efficient interaction between the frontend and backend.
Natural Language Processing (NLP) OpenAI API Flask Summarization Quiz Generation Web Development Prompt Engineering Python Figma September 2023 - December 2023
In this group project for my NLP class, I developed and programmed a summarizer and quiz generator using the OpenAI API. The summarizer extracted relevant and key information from the course textbook and displayed it on a website. I collaborated with the team to design the interface using Figma and set up the backend using Flask to handle API calls. The summaries were then presented in a static format on the web.
Web Development TypeScript Angular Figma Agile June 2021 - September 2021
As a Software Engineering Intern at IT Paradise, I worked alongside a team of senior developers on the URMU Museum website, a web application for a museum in Malaysia. This internship marked my first experience in a professional software development environment. I focused on front-end development using TypeScript and Angular where I translated designs from Figma into a functional website.
Web Development React TypeScript Accessibility WCAG SEO GitHub Node.js Yarn Netlify Agile April 2022 - Current
As a web developer for the ComputingPaths project, I worked to enhance both the functionality and accessibility of a React-based web application. This platform is designed to inform prospective UCSD students about the various engineering majors offered at the university. My role involved collaborating with other developers, improving the user experience, and creating new content.
