Hi, I'm Hy Nguyen.
Software engineer and computer science student focused on high-performance systems, optimization, and ML-powered products.
Currently studying at Adelaide University.
About
My work spans research and industry, from robotics and computer vision to combinatorial optimization, low-latency systems, and LLM-integrated full-stack products.
I enjoy problems that reward strong fundamentals and careful engineering, whether that means pushing latency down in a GPU-heavy pipeline, benchmarking search heuristics under strict budgets, or turning messy data workflows into usable products.
Technical Experience
- •Selected for a competitive program focused on low-latency systems, networking, and exchange-level trading infrastructure.
- •Built a simulated exchange from scratch using gRPC and Protobuf, implementing order matching, low-latency communication, and real-time position and risk management.
- •Benchmarked LNS, VNS, and LKH-3 across TSPTW instances scaling from 20 to 200 nodes under strict computational budgets to establish fair sequential baselines.
- •Developed a warm-start transfer strategy that reuses solution states between tasks, achieving statistically significant efficiency gains over isolated execution.
- •Overhauled the synthetic data generation pipeline in NVIDIA Isaac Sim, enabling scalable fine-tuning of vision-language foundation models on domain-specific tasks.
- •Debugged trajectory planning algorithms to eliminate path instability, generating 500+ high-fidelity video sequences used as ground-truth training data.
- •Built an LLM-powered analytics platform with React, Python, and PostgreSQL for NRC Health, enabling natural-language queries over structured data with sub-3s response times.
- •Developed data-to-text generation pipelines using structured prompt chains, automating weekly reporting for 30+ stakeholders.
Education
The University of Adelaide
Bachelor of Computer Science (Advanced)
GPA: 6.28/7.0 | Major GPA: 6.43/7.0
Feb 2024 – Expected Nov 2026
Projects
- •Built a full-stack spaced repetition platform with a modified FSRS algorithm and confidence-based grading to dynamically optimize review intervals.
- •Designed the review workflow around 200+ coding problems, balancing retrieval practice, retention targets, and usability for consistent long-term study.
- •Architected a production-ready web application, implementing a modular MVC architecture to decouple business logic, API routes, and data access layers.
- •Designed a scalable relational database schema (MySQL) and a custom Repository Pattern abstraction layer, optimizing complex join queries for real-time aggregation.
Awards
- •Secured 1st place out of 15 teams by engineering a market-making strategy around statistical arbitrage signals and real-time order book imbalances.
- •Optimized for risk-adjusted PnL, balancing aggressiveness, inventory risk, and execution quality in a competitive simulated market.
Technical Skills
Languages: Python, C/C++, TypeScript, JavaScript, SQL, Java
Frameworks: Next.js, React, Node.js, Vue.js, Express.js
Tools: CUDA, Docker, PostgreSQL, MySQL, Git, Linux, CMake