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en970/README.md

Enes Öz

Applied ML research and AI apps in production

Fourth-year Mathematics and Computer Science student. I work on machine learning for scientific discovery: LLMs, VLMs, and ML applied to astronomy and space data. Alongside research, I build and ship AI-powered apps.

Research

space-ml-lab — discovery-oriented ML on open space data:

  • CNN detector for solar radio bursts on e-CALLISTO spectrograms (validation AUC ~0.83)
  • Star-cluster recovery in Gaia DR3 with HDBSCAN
  • Autoencoder-based spectral anomaly detection on SDSS

Reproducible pipelines with a written technical report.

Building

Shipped AI and mobile apps:

  • MacroLens — AI nutrition tracker, meal photo to macros. Flutter, Firebase, GPT-4o. App Store · Google Play
  • AI CV Analyzer — resume scoring and ATS-oriented rewriting. Flutter, FastAPI, Gemini. App Store · Google Play
  • SwipeCure — screen-time coach with weekly AI reflections. Swift, Gemini. App Store
  • Plectro — guitar practice tracker with real-time pitch and chord detection. Swift. App Store
  • Niva — offline habit and mood tracker with home-screen widgets. SwiftUI. App Store

Education

  • BSc Mathematics and Computer Science — in progress
  • Associate degree in Computer Programming — Anadolu University (Open Education)

Links

LinkedIn

Typing SVG

Pinned Loading

  1. gravitational_lensing_simulation gravitational_lensing_simulation Public

    I made a simulation that uses real equations to show how gravitational lensing works.

    Python

  2. odysseus odysseus Public

    Forked from pewdiepie-archdaemon/odysseus

    Self-hosted AI workspace.

    Python

  3. space-ml-lab space-ml-lab Public

    Discovery-oriented machine learning on open space data: solar radio bursts (e-CALLISTO), star clusters in Gaia DR3, and spectral anomaly detection. Reproducible pipelines with formal reports.

    Python