DOMichelis
Web app for visualizing HTML DOM Tree traversal using BFS and DFS. It supports URL/manual HTML input, CSS selector search, traversal logs, search statistics, DOM visualization, and LCA features.

An Informatics student exploring the intersection of AI, data, and software.

Currently studying Informatics Engineering at Bandung Institute of Technology (ITB), Indonesia, as part of the 2024 cohort. I have a strong interest in AI/ML, software engineering, and data-driven problem solving, especially in how technology can turn ideas into practical systems that solve real-world problems. I value collaboration, communication, and continuous learning as essential parts of every project I work on. Alongside my academic journey, I am also interested in social and environmental projects, campus organizations, and football analysis, where I can combine curiosity, teamwork, and impact-driven thinking.
Let’s talkMy top 5 VIA Character Strengths that shape how I collaborate, communicate, and grow
2026
Jan 2026 – Apr 2026
Backend Developer
2025
Dec 2025 – Present
Staff of Electrical
Nov 2025 – Mar 2026
Staff of Hackvidia
Sep 2025 – Mar 2026
Intern of Intracampus Division
Jun 2025 – Sep 2025
Mentor
Mar 2025 – Jul 2025
Staff of Main Event
Mar 2025 – Dec 2025
Staff of Project Division
Jan 2025 – Present
Awardee
2024
Nov 2024 – Jul 2025
Staff of Internal Relation
Web app for visualizing HTML DOM Tree traversal using BFS and DFS. It supports URL/manual HTML input, CSS selector search, traversal logs, search statistics, DOM visualization, and LCA features.

Book search and recommendation web app using linear algebra techniques, including image similarity, TF-IDF text search, SVD topic analysis, and personalized recommendations. Built with React, Go, and Docker.

Monopoly-inspired board game built in C++ with SFML, featuring property trading, auctions, taxes, special cards, save/load systems, and an interactive GUI for 2–4 players.

Estimates football goal probability from a single shot image using affine basis transformation, wedge product, and logistic regression — no tracking cameras needed. Built with Python, OpenCV, and NumPy.

Digital pet adoption & health tracking platform. Covers ER modeling, relational schema, data seeding, and integrity constraints (triggers, views, CHECK, referential actions).

