Yi Yang Wong@wong_yi_yang485
1
Events attended
1
Submissions made
Malaysia
1 year of experience
About me
Driven by self-taught curiosity and a deep focus on systems design, I am a Dean's List Electrical & Computer Systems Engineering (ECSE) student at Monash University and a Capstone Project Champion. My technical roots are in real-time systems and embedded engineering, but my current obsession is applied AI. I specialize in agentic and multimodal pipelines that combine RAG, real-time backends, and human interaction. Recently, I led a team to the Top 42 globally in the Deriv AI Hackathon, building a proactive trading platform with FastAPI and Gemini. I’m currently developing HoloPi, a multimodal holographic AI assistant that fuses speech, gesture control, and event-driven orchestration. I’m on Lablab.ai to push boundaries, combining solid engineering fundamentals with practical AI to build reliable, production-minded systems.
🤓 Latest Submissions
CircuitSense: AI-Powered EDA Debugging
CircuitSense transforms the hardware engineering workflow by replacing manual, error-prone SPICE debugging with an intelligent, physics-aware AI assistant. Traditional EDA tools often output cryptic error logs, forcing engineers to spend hours hunting down floating nodes, improper gains, or op-amp saturation issues. Existing solutions only check basic syntax, leaving a massive gap for beginners and professionals alike. Our platform provides a frictionless workspace where engineers can seamlessly import custom netlists. Powered by the Gemini API, CircuitSense goes beyond basic linting. It performs actual analog physics calculations, like applying Ohm's Law and calculating voltage gain against power rails to detect hardware collisions and topology errors before a PCB is ever printed. To ensure enterprise-grade safety, we built a non-destructive versioning system with a visual "Before & After" diff viewer, allowing engineers to review and validate AI-suggested code changes before applying them. Additionally, the platform auto-generates exportable session audit trails for documentation. Building this robust AI pipeline in a single weekend was made possible by integrating the IBM Bob IDE as our core development partner. We executed a systematic software development cycle: utilizing Bob's Plan Mode to safely architect our API backend and Streamlit UI, followed by Code Mode to execute the logic, implement regex parsing, and squash bugs. CircuitSense bridges the gap between traditional software and modern AI, proving that smarter debugging leads to faster innovation.
17 May 2026
