👩‍💼 Professional Summary

• Work Experience:With 11 years of technical experience including 8+ years specialized in Machine Learning and Data Science, I've built a career at the intersection of research and practical implementation.
• Edicational Qualification: M.Tech, IIEST Shibpur in Computer Science.
• AI/ML Engineering: Deep hands-on experience in Machine Learning, Deep Learning, Computer Vision, NLP, and Generative AI.
• Specialized LLM Engineering: LLM Fine-tuning, RAG pipeline development, and AI Agent building with multi-modal applications across text, images, spectrum, and time-series data. Proven ability to solve ultra-small dataset challenges using Few-shot learning, Meta-learning, LLM fine-tuning (LoRA), and Domain Adaptation.
• Technical Stack: Proficient in Python, PyTorch, TensorFlow, Keras, Docker, with knowledge of AWS and Kubernetes.
• Research & Innovation: Published first-author IEEE research papers and actively contribute to solo and independent proof-of-concepts and technical blogs on GitHub & Kaggle.
• Contact:Connect with me professionally on LinkedIn.

⚡ Skills

• Python, PyTorch, TensorFlow, TorchVision, TFLite, ONNX
• CNN, RNN, Transformers, LLM, RAG, Building AI Agents
• LangChain, LangGraph, FastAPI, Docker, Kubernetes
• SQL, SQLite, Neo4j, FAISS
• Generative AI, NLP, Computer Vision, Meta-learning, Few-shot learning, Multi-modal learning, Domain-adaptation, Semi-supervised learning

📖 Publications

• First Author of "Data Drift Quantification Metrics for Month-on-Month Semiconductor Data" — IEEE WinTechCon 2024.
• First Author of "Image Retrieval using Extended Bag-of-Visual-Words" - IEEE ICACCI 2016.