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Ozel Yilmazel

Computer Science Graduate Student & Researcher
University of Massachusetts Amherst | College of Information and Computer Sciences
Pronouns: he/him/his

Contact

• Email: ozel at yilmazel dot com
• LinkedIn: linkedin.com/in/ozelyilmazel
• GitHub: github.com/oz03-hub

Education

Master of Science in Computer Science

University of Massachusetts Amherst
Expected Graduation: May 2026 | GPA: 4.0

Bachelor of Science in Computer Science

University of Massachusetts Amherst
Graduated: May 2025 | GPA: 4.0

Coursework: Advanced Algorithms, Applied Information Retrieval, Search Engines, Machine Learning, Applications of NLP, Artificial Intelligence, Information Systems, Web Applications

Awards & Honors: Bay-State Fellowship, Phi Kappa Phi Honors, Summa Cum Laude

Work Experience

Student Researcher

Center for Intelligent Information Retrieval – UMass Amherst
April 2025 – Present | Amherst, MA

• Conducting research on personalization for cold-start settings in retrieval-augmented generation (RAG) systems, leveraging Stack Exchange data to model user behavior and develop cross-domain profiling techniques
• Performed comprehensive experimental analysis to evaluate personalization models, deriving new research questions and insights
• Presented findings at the CIIR Poster Series

Student Researcher

Initiative for Digital Public Infrastructure – UMass Amherst
February 2025 – September 2025 | Amherst, MA

• Investigated topic distributions on YouTube by applying clustering algorithms to large-scale video embedding datasets (~16,000 samples)
• Analyzed how embedding representations influence topic granularity and revealed structural patterns within the platform’s content ecosystem
• Developed a multilingual recommendation analysis pipeline using the YouTube Innertube API, generating recommendation trees to study cross-language exposure paths and user discovery patterns across linguistic boundaries

Researcher

Center for Data Science and Artificial Intelligence – UMass Amherst
May 2024 – May 2025 | Amherst, MA

• Built a machine learning pipeline for song recommendation using learning-to-rank models (XGBoost, scikit-learn) for the music therapy app SingFit, contributing to an academic publication
• Designed and implemented a versatile text classification suite for large language models using LangChain, enabling rapid experimentation across multiple NLP tasks
• Developed and deployed full-stack web annotation platforms for the NSF Buzzards Bay water preservation project and iNaturalist, leveraging React, PostgreSQL, and Azure cloud services
• Fine-tuned geo-predictive models with PyTorch, utilizing user-generated labels from iNaturalist, improving species location inference accuracy

Course Teaching Assistant

College of Information and Computer Sciences – UMass Amherst
September 2022 – Present | Amherst, MA

• CS446: Search Engines – Introduced and taught a new module on Retrieval-Augmented Generation, designed and implemented programming assignments, developed automated grading tools
• CS121, CS230, CS326 – Provided academic support to hundreds of students through office hours, project guidance, and grading assistance
• Received the Outstanding UCA Award for excellence in teaching, communication, and collaboration across multiple semesters

Projects

Natural Language Playlist Querying

Fall 2025

• Designed and implemented a natural language playlist retrieval system, developing custom song embeddings and a dual-encoder retriever
• Processed 100,000 playlists from Spotify, leveraging PyTorch and HuggingFace Transformers to train retrieval models
• GitHub

OverMath – A Math Cooking Game

Fall 2024

• Co-developed a Unity-based educational game; implemented Adversary AI, player controls, and projectile physics
• Contributed core gameplay mechanics as part of a 5-person team

Publications

• Yilmazel, O., Zhu, A., Navarrete, P., Pogorelov, S., & Partridge, V. (2024). iNatator: Obtaining Expert Feedback on Species Ranges. New England Computer Vision Workshop (NECV); November 2024; Yale University, New Haven.

• Yilmazel, O., McGrady, R., Partridge, V., & Zuckerman, E. (2025). YouTube Topic Modeling. Computational Social Science Poster Session 2025; May 2025; UMass Amherst. Winner of the People’s Choice Award.

• Myers, J. R., et al. (2025). Developing an equitable machine learning-based music intervention for older adults at-risk for Alzheimer’s: Pilot findings for algorithm development and validation. JMIR Aging; October 2025 (submitted). Contributor.

Skills

Programming Languages: Python, JavaScript, Java, SQL, HTML/CSS, C#, C

Tools & Frameworks: PyTorch, pandas, NumPy, SciPy, matplotlib, scikit-learn, NLTK, XGBoost, HuggingFace, LangChain, MongoDB, Unity, Azure, PostgreSQL, SLURM, Git, Docker