About Me
I’m an undergraduate pursuing a degree in Computer Science – AI, complemented by specialized coursework in Data Science and Artificial Intelligence. My academic journey gives me a theoretical grounding in cloud computing, machine learning, and software development, while my hands-on projects have challenged me to apply that knowledge in real-world scenarios.
Here you can explore my world, from an none fancy IT Developer to a person that have great passion in seeking knowledge by exploring new technologies and world insight about AI and related domain when applying up-to-date technologies into it.
Fields of Interest
Artificial Intelligence & Applied ML
Developing practical, optimized machine learning solutions. My focus is on turning raw data into actionable insights, utilizing everything from spatial clustering to deploying quantized ONNX models for real-time edge inference.
Cloud Computing & Serverless Architectures
Designing highly scalable, event-driven systems on AWS. As an AWS Certified AI & Cloud Practitioner, I prioritize zero-idle-compute architectures that maximize performance while rigorously optimizing operational costs.
Generative AI & LLM Orchestration
Building intelligent, context-aware tools powered by Large Language Models. I specialize in designing full-stack Retrieval-Augmented Generation (RAG) pipelines, leveraging vector databases and sophisticated prompt engineering via AWS Bedrock.
MLOps & Production Engineering
Bridging the gap between the Jupyter notebook and the real world. I engineer end-to-end serverless MLOps pipelines—handling everything from automated data telemetry processing to containerized production deployments.
Full-Stack AI Product Development
Merging robust AI backends with seamless user experiences. I build accessible, interactive web products using modern frameworks like Nuxt, Vue, and React, backed by FastAPI and PostgreSQL.
AI in Cybersecurity
Exploring the intersection of machine learning and system security. I have experience engineering hybrid, ensemble-based ML engines designed for automated vulnerability detection and static code analysis.