B Engineering (Hons) — Electrical & Computer Engineering
AI & Hardware — from embedded silicon to production model
Final-year Electrical & Computer Engineering student at UQ specialising in embedded hardware and applied AI. I've programmed Siemens S7 PLCs on live industrial sites, designed multi-layer PCBs for ARM embedded targets, and built ML pipelines processing real sensor data — including a flood-risk model that outperformed Google's public baseline by 75%. I work across the full stack: silicon to software.
Developed an award-winning geospatial flood-risk model at a UQ × KMITL × Thai National Innovation Agency hackathon in Bangkok. Processed 15 years of Thai government hydrological data — outperforming Google’s forecast baseline by 75%. Thai government expressed interest in continued development.
Prototyped an IoT smart valve system integrating flow sensors, embedded firmware, and ML-based anomaly detection for real-time water network monitoring.
Engineered a hard real-time sensor pipeline with deterministic interrupt handling and a fixed-point FFT for reliable in-flight data acquisition under strict timing constraints.
Engineered a handheld gaming device on an STM32L4 microcontroller featuring DMA-driven I2S audio playback from SD card, a custom DAC amplifier circuit, OLED display, LED matrix, and arcade-style input.
Placed 2nd competing solo in a team event. Built a maze-solving robot with 3 IR sensors, an MPU6500 IMU, DC motor drive, and implemented a DFS traversal algorithm for autonomous navigation.
Led technical architecture of a React Native prototype during a UQ-funded international exchange at Dalian Neusoft University. Platform recommends projects to users via heuristic AI matching based on engagement patterns.