UBC researcher and co-founder building at the intersection of machine learning, computational biology, and open-source infrastructure. Originally from Indonesia; currently making LLMs less painful to run locally and teaching machines to read RNA.
I grew up in Indonesia competing in national science olympiads — the kind of thing that teaches you to be comfortable with hard problems and uncomfortable with easy answers. That instinct helped me earn a place in the inaugural cohort of Beasiswa Indonesia Maju (now Beasiswa Garuda), a full government scholarship by Indonesia's Ministry of Education for outstanding students to study abroad. That brought me to Vancouver, where I enrolled at UBC and immediately started looking for problems worth solving at the intersection of data, biology, and systems.
My first published work applied deep learning and Gaussian blur preprocessing to circular RNA classification, achieving 75% accuracy with 0.14ms inference — fast enough to be clinically useful. The paper is published in URNCST Journal. Around the same time I won Best Research Project at UBC Vantage College's Capstone Conference for work on P-53 tumor suppressor gene mutation analysis using genetic algorithms. Two papers, two directions: one molecular, one computational.
“I chase problems where data hides something meaningful.”
On the infrastructure side, I co-founded Kolosal AI — an open-source platform for running large language models locally, privately, and fast. The desktop app and CLI together have earned over 900 GitHub stars. Before that, I co-founded Genta Technology — the experience that first planted the idea of making AI infrastructure genuinely accessible. After the olympiad years, I also took on an AWS / Cloud Computing trainer role, delivering courses to 1,000+ students across Indonesia.
My research portfolio has since expanded into ML clustering (SOM-TSK, GRASP), gene regulatory network inference, and most recently computational economics — building agent-based Keynesian models in Rust to study Minsky dynamics, zero lower bound persistence, and coordination failure. When I'm not debugging loss curves, I'm reading about macroeconomics or hiking the trails around Vancouver.
Building open-source infrastructure to make running LLMs locally simple, private, and fast. The Kolosal desktop app and CLI have together earned 900+ GitHub stars. Products span a C++ inference server, AutoML platform with Optuna + MLflow, a model memory calculator, and a Retrieval Management System.
First-author research in computational biology (circular RNA, GRN inference), ML systems (SOM-TSK, GRASP), and computational economics (Keynesian ABM). Published in URNCST Journal; Best Research Project at UBC Vantage College Capstone Conference 2023.
The early seed of what would become Kolosal AI. Built the Genta Academic Assistant — an AI-powered paper search tool using Streamlit, Weaviate, and the OpenAI API — which first crystallised the idea of making AI infrastructure accessible and locally deployable. Also served as AWS / Cloud Computing trainer, delivering courses to 1,000+ students across Indonesia.
Enrolled via UBC Vantage College. Active undergraduate researcher in deep learning and genomics. First-author URNCST publication (2024). Best Research Project, Capstone Conference 2023.
National Science Olympiad (OSN/KSN) finalist in Informatics. Also competed in the national debate circuit — LDBI (Lomba Debat Bahasa Indonesia) and NDDC (National Schools Debating Championship). Conducted independent research projects in high school alongside these competitions.
Full government scholarship awarded by Indonesia's Ministry of Education, Culture, Research & Technology to outstanding students for undergraduate study at international universities. Among the inaugural cohort of recipients.