About
I'm a data and AI practitioner with a strong foundation in engineering and research. With over a decade of hands-on experience and a PhD in Electrical Engineering, I bring deep technical expertise across the full data and AI lifecycle — from modern data platforms to production-grade machine learning and generative AI systems.
Current
I specialize in architecting end-to-end data and AI solutions that transform raw data into actionable insights and business value. My current focus is on Generative AI — particularly Retrieval-Augmented Generation (RAG) systems and enterprise AI solution architecture. I work across Azure, AWS, GCP, Databricks, and Snowflake, combining modern data engineering with MLOps and full-stack development practices to deliver robust, real-world AI capabilities.
Previous Life
Before transitioning into the data and AI industry, I worked as a postdoctoral researcher at the School of Engineering & IT, UNSW Canberra, where my research focused on adaptive optics for astronomy — developing real-time wavefront sensing techniques using holographic and Shack-Hartmann sensors implemented on FPGA-based systems. This experience honed my skills in algorithm design, embedded systems, and high-performance computation, which continue to shape my approach to building efficient and scalable data-driven systems today.
Hobby
Beyond data and AI, I've always been curious about technology and productivity tools — from FPGAs and robotics to Emacs, Vim, and automation frameworks — continually exploring new ways to work smarter and build better systems.