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 intelligent systems.
Azumie is taking shape through real client work, not a hypothetical dashboard.
My current work with Senza Fine grounds Azumie in the daily realities of a small business: turning fragmented operational information into systems people can actually use and trust.
That work feeds applied machine-learning questions around forecasting and decision support. I document the technical findings through Towards Data Science and the wider building journey on Medium.
Selected systems, arranged as evidence of how my work moved from sensing the physical world to making machine reasoning visible.
An early-stage product direction for turning fragmented company data into clear, evidence-backed recommendations that people can inspect before acting.
A visual reasoning laboratory where weighted concepts become a graph people can inspect, perturb, and run instead of accepting an opaque answer.
SIHMT is a price intelligence and tender analytics system designed during my Cost Engineering internship at Pertamina Maintenance & Construction.
12 to 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.
I began with circuits, robotics, and flood detection: systems whose behavior could be measured directly. SIHMT and TTPL taught me to design around imperfect data and real people.
MindAssembly marks the next orbit: systems that expose how conclusions form. UC Berkeley in Spring 2027 and AZUMIE sit further along that same path.
I first contributed to Towards Data Science in 2021 and returned as a contributor in 2026. My archive spans more than thirty pieces across data science, engineering, and learning in public.
Read the transmission archive