Publications & Research¶
Thesis¶
Meta Modeling For AI Solutions Based on Existing AI Configurations M.Sc. Thesis · Yeditepe University · In Progress
Developing a system that extracts structured metadata from AI/ML research papers and recommends optimal model configurations through multi-LLM annotation, QLoRA fine-tuning, and calibrated active learning with vector search.
Papers¶
Compact Monocular Depth Estimation with Synthetic Stereo Generation¶
In Preparation
Investigates compact architectures for monocular depth estimation combined with synthetic stereo pair generation for improved stereo matching. Benchmarks multiple architectures and loss functions across datasets.
Research Interests¶
- Meta-Learning & Few-Shot Learning — Learning to learn from limited data
- Large Language Models & NLP — Fine-tuning, prompt engineering, and evaluation
- Deep Reinforcement Learning — Policy optimization and model-based methods
- High-Performance ML Systems — GPU-accelerated training and inference at scale