Research & academic work

Research

My interests sit at the intersection of applied machine learning, data science and reliable AI systems. I want to understand how models behave beyond a single evaluation score.

Accepted · publication pending

Two-layered Artificial Intelligence System to Assess and Forecast the Safety Level of Drinking Water Resources

International Journal of Engineering Approaches (IJEA)

O. Ergüden, B. Ceylani, A. Şengül, S. Yılmaz, E. Yılmaz, M. Y. Kalkan, D. E. Fawzy

A two-layer approach to current contamination detection and future water-safety trends.

Read the research project

Independent study · not submitted for peer review

Clustering and forecasting public transport ridership in İzmir

Three-person CE 477 course project

25,775 daily İzmirim Kart ridership rows by operator and fare type, January 2021 – April 2025.

DBSCAN clustering, seasonal features and demand forecasting with XGBoost and Random Forest.

See it in the archiveSource on GitHub

Questions I’m exploring

  1. How should retrieval systems behave when the available evidence cannot support an answer?
  2. How well do predictive models generalize across time and changing data sources?
  3. How can evaluation separate model quality from data leakage and dataset-specific shortcuts?

Academic foundation

Degree
BSc Software Engineeringİzmir University of Economics · June 2026 · GPA 3.30 / 4.00
Academy
Google AI & Technology AcademyDeep Learning · 2026
Publication
IJEAAccepted · publication pending

Academic interests: AI, machine learning, data science and software architecture.