Researcher in Machine Learning | Ph.D. Candidate in Quantitative Methods, Istanbul University

Projects • Publications • Teaching Activities • Contact
I am a researcher working on Recommender Systems, Large Language Models, and Explainable AI.
Currently pursuing my PhD in Quantitative Methods at Istanbul University and conducting research at the University of Passau.
Computer Science, 10(1), 53-91 (2025)
→ This paper discusses the growing importance of recommender systems in enhancing user experience and information access in digital environments.
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2022 International Congress on Human-Computer Interaction, Optimization and Robotic Applications (HORA), IEEE
→ Compared ML models on CDC BRFSS 2020 data; achieved 0.89 accuracy with XGBoost after SMOTE-Tomek balancing.
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Hacettepe Journal of Health Administration, 25(1), 17-28 (2022)
→ Analyzed political, economic, and demographic drivers of vaccine access across 88 countries using R and SPSS.
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Izmir Journal of Economics, 37(3), 760–777 (2022)
→ Explored how economic freedom influences the link between perceived corruption and national happiness in 150 countries.
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4th International Conference on Data Science and Applications, 142–145 (2021)
→ Tested recursive feature elimination on 9 ML algorithms across 5 datasets. Improved accuracy and reduced fit time.
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Y-BIS 2019 Conference, ISBIS Young Statisticians Workshop
→ Compared 9 classification algorithms on UCI cardiotocography data. Best model: Random Forest (0.88 accuracy).
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A content-based recommendation system that uses cosine similarity on standardized audio features to suggest similar songs.
Tools: Python, Spotify API, Cosine Similarity
📂 Tags: Recommender, Content-Based, Audio Analysis
Collaborative filtering recommendation system using transaction data and language models.
Tools: Python, NLP, Transaction Logs
📂 Tags: Fashion, Collaborative Filtering, Language Models
NLP-based sentiment analysis on Edgar Allan Poe’s short stories using VADER and visualized emotion trends.
Tools: Python, VADER, Word Clouds
📂 Tags: NLP, Sentiment, Visualization
Comparative study on 9 ML models for early heart disease prediction using SMOTE-Tomek and CDC BRFSS dataset.
Tools: Python, XGBoost, Sklearn
📂 Tags: Health, Classification, SMOTE
Fundamentals of algebra, functions, and calculus applied to economics and business problems.
Practical implementation of hypothesis testing, confidence intervals, and regression analysis.
Application of linear programming and optimization techniques in decision-making scenarios.
Basic descriptive statistics and probability theory for beginners.
Quantitative methods used in finance and business management, including interest calculations.
Hands-on use of the R programming language for data analysis and statistical modeling.
Introduction to data preprocessing, clustering, classification, and association rule learning.
📄 You can download my latest resume here.
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