Duje Vukovac

CS student at VU Amsterdam.
Interested in AI-assisted tooling and what good software looks like.
Currently shipping side projects and documenting the learning process.

Seal logo

About Me

I'm a VU Computer Science student who's into AI-powered software. Currently learning core SWE skills while also building self-study tools (like this StudyBot I wrote about) and exploring ML/HCI/AI tooling on the side. Outside of code, you'll find me with my Canon camera in one of the big Amsterdam parks. (in good weather, of course).

Skills & Tech Stack

Python C C++ JavaScript HTML & CSS Flask Node.js Express SQLite Git Assembly (x86, IJVM) MATLAB AI-Assisted Development

Experience & Projects

2021 — 2023

Hearts of Iron IV Community

Head of Mod Development

Built, maintained and optimized a multisystem mod using Paradox's scripting framework, reaching hundreds of downloads. Achieved ~30% improvement in in-game performance through mod optimization.

Community Manager (concurrent)

Grew community from 30 to 500+ members, leading a team of 8 moderators. Organized 50+ events with 80%+ capacity fill rate. Built advertising bots and tracked member analytics (performance stats, win/loss ratios) via spreadsheets. Brokered partnerships yielding shared sessions and 2 competitive tournaments. Handled moderation and conflict resolution across the community.

Volunteering

Aug 2026 — Present

Safe AI Netherlands (SAIN) · Amsterdam, NL

Discussion Co-lead

Run the weekly discussion sessions end to end: scheduling them, selecting the paper topic each week, and preparing the material the group works through. On the day I guide the discussion itself, keeping it on track and drawing out contributions from everyone in the room.

Apr 2026 — Present

AI Spring Amsterdam · Amsterdam, NL

Co-Organizer

Co-organize the weekly AI paper reading events at VU Amsterdam, covering logistics, topic suggestion, and hosting. Co-organized the July 2026 end-of-year AI papers showcase together with Safe AI Netherlands (SAIN) and AISO, where I presented an overview of Chain-of-Thought improvements toward more efficient LLM reasoning.