I'm Tan Jin Chun (Nigel), a Physical Design Engineer and Agora Ambassador
My work brings together semiconductor engineering, software automation, and applied machine learning. I enjoy building tools that make engineering workflows easier to manage and turn data into useful decisions.
- Semiconductor physical design and power integrity — working on chip implementation and analysis, alongside Python and Tcl tools for engineering workflows.
- Uncertainty-aware monitoring — researching how forecasting and conformal prediction can improve the reliability of smart-building alerts, with attention to fault detection, alert workload, and detection delay.
- Engineering dashboards — developing tools to organise APR and static timing analysis metrics into consistent reports and dashboards.
- Embedded prototyping — developing Quipus, a Fovea-branded hardware prototype exploring recording, local storage, and Wi-Fi connectivity.
My master's research codebase for uncertainty-aware smart-building monitoring and alerting. It connects time-series forecasting, conformal prediction, and alert generation, then evaluates detection performance, alert burden, robustness, and recalibration under a common experimental protocol.
An ongoing hardware prototype project connecting embedded development with a compact recording device.
- Programming and automation: Python, Tcl, C
- Semiconductor engineering: physical design, power integrity, static timing analysis, Cadence Innovus and Voltus
- Applied machine learning: time-series forecasting, XGBoost, LSTM models, conformal prediction, and reproducible evaluation
- Embedded systems: ESP32 prototyping and IoT
My technical background includes Electrical and Computer Systems Engineering at Monash University Malaysia and coding projects at 42KL.
- Industry Advisory Panel member for Semiconductor Systems Engineering at Monash University Malaysia.
- Agora Ambassador and Aspire Institute volunteer, supporting learning and community initiatives.
- PMI IGNITE 2026 Young Project Manager Award finalist for the Hybrid Solar Lighting System project.
I'm interested in collaborating on engineering automation, reliable IoT systems, and practical machine-learning applications.