Data & AI Enthusiast | Citizen Scientist | Privacy Advocate | Lifelong Learner

I come from a background in AI data services, customer success, and technical support with hands-on experience in PII annotation, data quality auditing, and GDPR compliance. I'm now channelling that into learning programming and exploring where data meets science.

I don't have a computer science degree. I learn by doing, asking questions, and not pretending I know things I don't.

I'm an active contributor to research platforms where anyone can help advance real science:

• EyeWire — Mapping neurons in the retinal connectome for neuroscience research at Princeton
• Folding@home — Donating computing power for protein dynamics simulations in disease research (300,000+ points contributed)
• Stall Catchers — Analysing brain blood flow data for Alzheimer's disease research

These projects are what first drew me toward computational biology and neuroscience, and they're shaping where I want to take my career.

Languages & Scripting

• 🐍 Python — Working through the back-end developer path; primary language for data science and bioinformatics
• 📊 MATLAB — Learning for computational neuroscience, neuroimaging, and scientific data analysis
• 📈 R — Learning for bioinformatics and statistical analysis of biological data (widely used in genomics, RNA-seq, and health research through tools like Bioconductor)

Systems & Tools

• 🐧 Linux — Daily driver (Ubuntu). Comfortable with systemd services, networking, firewall configuration, and troubleshooting
• 🐙 Git & GitHub — Building the version control habit
• 🐳 Docker — Running containerised applications, managing images, and working with tools like Ollama and custom Dockerfiles for isolated environments

Privacy & Networking

• 🧅 Tor / .onion — The onion routing network that anonymises internet traffic by encrypting it and bouncing it through multiple volunteer-run relays worldwide. Used via Tor Browser for accessing .onion hidden services
• 🟣 I2P (Invisible Internet Project) — A separate anonymity network from Tor, designed for internal services ("eepsites") rather than accessing the clearnet. I run i2pd (the C++ implementation) and browse .i2p sites through Mullvad Browser configured with I2P's local HTTP proxy
• 🔒 Mullvad DNS — Using encrypted DNS-over-TLS for query privacy, and Mullvad Browser (a hardened Firefox fork by the Tor Project & Mullvad) as my privacy-focused browser
• 💰 Monero (XMR) — Privacy-focused cryptocurrency; using the Feather wallet connected through I2P's SOCKS5 proxy for anonymous transactions

I'm not a developer yet. I'm learning in public. What you'll find here are practice repos, guided projects, and experiments as I build up my skills.

• 🇬🇷 Based in Greece, native Greek speaker, C2 English (Cambridge & Michigan certified)
• 🗣️ Currently learning Lebanese Arabic, Mandarin Chinese, and Spanish
• 🎨 Gouache painter, Studio Ghibli enthusiast
• 🎹 Trained in classical piano, accordion, and vocal performance (Music School of Pallini)
• 💼 Former Data Annotation Auditor (iMerit) · Customer Success (Plum) · Tech Support (Microsoft/Movate)

I'm drawn to the intersection of data, biology, and open science. I'm currently studying computational neuroscience and bioinformatics through Coursera, learning how to apply Python, R, and MATLAB to problems in brain research, genomics, and health informatics.

Long-term, I want to contribute to tools and systems that help us understand the brain, decode genetic data, or improve healthcare outcomes. I'm especially interested in connectomics (mapping neural circuits, which is what drew me to EyeWire), neuroimaging data analysis, and machine learning applications in medicine.

For now, I'm building a solid foundation one commit at a time and staying close to the citizen science communities that keep me motivated.