Machine Learning Engineer & NLP Researcher passionate about LLMs, recommender systems, and production-scale AI.
- 🎓 MSc in Computer Engineering @ Kadir Has University (GPA: 3.94/4.0) — Thesis on ML-based Recommender Systems
- 🔬 Research Assistant — Fine-tuning transformer architectures, publishing at IEEE conferences & Q2 journals
- 🚀 Experienced in deploying LLMs in production, building end-to-end ML pipelines & containerizing models with Docker
- 📝 4 publications in NLP, anomaly detection, and neural recommendation systems (2 under review at Q2 journals)
- 🧘 Fun fact: I love horror movies, yoga, and running — a chaotic but balanced trio.
- 📫 Reach me at: s.kilinc.ce@gmail.com
🧠 NLP & Large Language Models (LLM Fine-tuning, LoRA/QLoRA)
📦 Recommender Systems (Collaborative Filtering, Neural Architectures)
🔍 Anomaly Detection (LSTM, Knowledge Distillation, Quantile Regression)
🖼️ Computer Vision & Multimodal Sentiment Analysis
⚙️ MLOps (Docker, MLflow, Flask, Grafana, InfluxDB)
- 📘 Inherent Explainability in Neural Recommendation Architectures — Under Review, UMUAI (Q2)
- 📘 Multimodal Sentiment Analysis — Under Review, IJ-AI (Q2)
- 📗 Advancing Anomaly Detection: A Knowledge Distillation Approach with LSTM — IEEE ASYU 2023
- 📗 Network Traffic Anomaly Detection: Quantile Regression with Tolerance — IEEE BlackSeaCom 2023