AI Engineer | Systems Engineer
I am a Computer Engineering student at Gazi University (ranked 1st in my department out of 120 students) and currently work as a Systems & Reliability Engineering Trainee at Turkish Aerospace (TAI - TUSAŞ). I specialize in building highly optimized deep learning architectures, developing lightweight MLOps tools, and solving complex, system-wide architectural bottlenecks.
- Languages & Architecture: Python, C#, SQL, System Architecture, Docker
- AI & Machine Learning: PyTorch, TensorFlow, CNNs, Vision Transformers (ViT), Federated Learning
- NLP & Backend: GPT APIs, LLM Fine-Tuning, Hugging Face Transformers, FastAPI, Flask
- DriftSense: A lightweight, Docker-first MLOps CLI tool for tabular pipelines that detects data and concept drift using statistical tests (KS, PSI, ADWIN) with built-in Slack/SMTP alerting.
- High-Dexterity Prosthetic Hand (sEMG Deep Learning): A custom Domain-Adversarial Neural Network (DANN) for sEMG gesture classification. Achieved 87.7% validation accuracy via per-subject fine-tuning and slashed training time by 80% using XLA JIT compilation.
- MeldFlow: A multi-modal ML toolkit (vision, tabular, text) built with PyTorch and Hugging Face, enabling rapid training and deployment via a FastAPI inference server.
- FedChain: A privacy-preserving federated learning system secured on an Ethereum blockchain, utilizing smart contracts for immutable auditability of model weight updates.
- Email: nizamfurkanegecan@gmail.com
- LinkedIn: linkedin.com/in/furkan-egecan-nizam

