Computer Engineering student building flight software for the CUSAT-1 satellite, engineering avionics for high-altitude rockets, and developing full-stack platforms — driven by a passion for space technology and intelligent systems.
My journey in Computer Engineering began in high school with C and C++ in a Science-Mathematics Program, sparking a passion for systems-level thinking that continues to drive my work today.
I'm currently developing flight software for the CUSAT-1 satellite bound for the ISS Kibo module, designing avionics PCBs for high-altitude rockets at CUHAR, and engineering backend platforms with FastAPI and Docker at CEDT Solution Club. Space technology is at the core of what I do.
Long-term, I want to work in the aerospace industry — building the reliable, mission-critical software that keeps things running in orbit.
Technical Advisor for two student teams through the full CanSat lifecycle. Sky's Line won the Best Failure Award, and Sky's Rift 2 won the Deployment Award for their reliable parachute system. Defined the architecture across ESP32-based subsystems with LoRa telemetry.
Intelligent exercise form analysis system for Thai athletes. Integrates MediaPipe pose detection, Pathumma LLM, and VAJA Thai text-to-speech for real-time AI coaching feedback with 95% accuracy.
Production-ready Deep Q-Learning implementation built entirely from scratch with PyTorch. Features experience replay, target networks, real-time training visualization, and comprehensive testing framework achieving 85% success rate.
Developed Edge Contour Detection for plant separation addressing data imbalance and real-world noise. Received Outstanding AI Award for innovative approach to computer vision challenges.
Modern web application for comprehensive subscription payment management with real-time tracking, statistics dashboard, multi-currency support, and automated Docker deployment with CI/CD pipeline.
AI-powered Thai language learning application generating interactive exercises including vocabulary questions and sentiment analysis using state-of-the-art NLP and text-to-speech technology.
Technical Advisor for two teams. Guided both teams through the full CanSat lifecycle — design, build, test, and flight. Sky's Line achieved the Best Failure Award, and Sky's Rift 2 won the Deployment Award for their highly reliable parachute deployment system.
Project Manager & Software Engineer. Developed comprehensive Ground Station, Flight Software, and Deployment Software. Won Deployment Award as the only team in Thailand with end-to-end system design.
Software Engineer & Systems Integration. Developed advanced flight control systems and communication protocols. Advanced to national finals as one of top teams in Thailand with innovative engineering solutions.
Advanced algorithms: KNN, K-Means Clustering, DAG Scheduling. Achieved 90/300 score through intensive 2-month preparation. Awarded Silver Medal by CMKL University.
"InsureMate" - AI application for insurance literacy integrating ML and NLP/LLM features. Won 70,000 THB prize for innovative approach to insurance technology.
"ThaiSign Application" - innovative Thai sign language learning platform using MediaPipe + MobileNetV2. Designed with UX/UI accessibility focus for hearing-impaired users with comprehensive gesture recognition.
Project Manager & Full-Stack Developer. Built VR app for OCD Exposure Therapy using Unity, React Native, and Node.js. Advanced to top 20 teams.
Project Manager. Developed immersive VR insurance learning simulation for training insurance professionals. Created realistic scenarios for risk assessment and policy understanding with advanced game mechanics.
Comprehensive EDA, data cleaning, and AutoGluon model training for prompt quest challenge. Achieved top quartile performance in competitive AI field with advanced optimization techniques.
Extended workshop submission presenting practical applications and implementation details of UColor system for seasonal color analysis with perceptual awareness in computer vision tasks, achieving 13.4% accuracy improvement over baseline methods.
UColor addresses a fundamental gap in Computer Vision: current models perceive color in RGB without understanding human color perception. The project proposes a two-stage architecture using FaRL backbone with a hybrid perceptual loss (Cross-Entropy + CIEDE2000) to classify Seasonal Colors in a perceptually-aware manner, reducing cross-undertone errors by 4.2%.
Researched and developed Computer Vision and Color Analysis models. Applied Color Science principles: CIELAB color space and CIEDE2000 metric. Developed Deep Learning models for Seasonal Color classification and designed perceptual-aware loss functions.
I'm always open to aerospace collaborations, research opportunities, and conversations about space technology, satellite systems, and software engineering. Feel free to reach out.