Machine Learning Engineer | PhD in Mathematical and Computational Modeling | Post Graduation-Level Lecturer
I build production-grade AI solutions with a focus on code quality, scalability, and interpretability. I also teach graduate-level courses in ML, Deep Learning, and Generative AI.
ML/DL (PyTorch, Scikit-learn) · Generative Models (VAEs, Transformers) · NLP & LLMs (RAG, LangChain, LangGraph) · Time Series & Anomaly Detection · MLOps (FastAPI, Docker, ONNX)
- Outlier Detection with LSTM Autoencoders — Financial time series with a full PyTorch training/validation pipeline
- Advanced PyTorch Examples — AMP, quantization, torch.compile, ONNX export, efficient GPU usage
- Generative AI & RAG Applications — Agents, semantic retrieval, and API integration with LangChain/LangGraph
- Graduate-Level Teaching Materials — Code and examples for ML, Deep Learning, and Generative AI courses
(See pinned repositories for direct access.)