Shannon AureliaEngineer · TDS Contributor · Jakarta
I'm Shannon Aurelia Widjaja, an electrical engineering student building Azumie, researching applied machine learning, and turning real operational problems into useful systems.
Azumie is where I am learning to turn operational data into decisions people can understand and trust.
My current client work with Senza Fine keeps the product grounded in real small-business needs, while my earlier PertaMC work shaped how I think about messy data, review, and decision support.
Alongside building, I am developing machine-learning research around forecasting and operational decisions, then documenting what survives contact with practice through Towards Data Science and Medium.
Projects chosen for the problem, decisions, and outcomes they reveal, not just the tools used to build them.
SIHMT is a price intelligence and tender analytics system designed during my Cost Engineering internship at Pertamina Maintenance & Construction.
12 → 400+participant growthAs Project Officer, I led a 40+ person committee across eight divisions and helped grow Techtonic from roughly 12 participants to more than 400.
A digital laboratory platform and operating system for circuits, instrumentation, high voltage, practicum resources, and student workflows.
A line of embedded projects connecting my I2-Tech winning flood sensor with a later water-level monitor and servo-driven rescue boat prototype.
I began with circuits, robotics, and flood detection. Then I started building the software, data systems, teams, and ventures around technical ideas.
Now I'm moving deeper into machine learning, algorithms, and NLP while preparing for UC Berkeley and developing AZUMIE as the long-term home for that ambition.
I first contributed to Towards Data Science in 2021 and was accepted to continue writing in 2026. My archive now spans more than thirty articles and essays across data science, engineering, and the process of learning in public.
Explore my writing ↗