About Me
Hi! I'm Ananya Reetha Noble — a Computer Science graduate from Mar Athanasius College of Engineering (APJ Abdul Kalam Technological University), where I completed my B.Tech in Computer Science and Engineering in 2024 with a CGPA of 9.25. I'm currently pursuing my M.Tech in Computer Science and Engineering (Artificial Intelligence) at the Defence Institute of Advanced Technology (DIAT), Pune, with a current CGPA of 9.05.
My research focuses on large language models, parameter-efficient fine-tuning, and retrieval-augmented generation — with applied work spanning computer vision and deep learning. I'm interested in building efficient, deployable AI systems that bridge foundational research and real-world impact.
I co-authored and published a research paper titled "Exploring LoRA for Parameter-Efficient Fine-Tuning of LLMs in Enhanced Algorithm-to-Python-Source-Code Translation Task", presented at ITECHCET 2024 and published in AIP Conference Proceedings (DOI: 10.1063/5.0247544). As part of this work, I fine-tuned Mistral 7B using LoRA on a custom dataset of 18,000 algorithm-code pairs — achieving 93.5% accuracy and a perplexity of 2.03 — and publicly released the dataset on Hugging Face to support reproducibility and community research.
I also have a manuscript in preparation on deep learning for marine biofouling detection and classification, where a proposed EfficientNetV2-S model with CBAM attention and BYOL self-supervised pretraining achieved a validation mAP@50 of 0.9624 — suitable for deployment on autonomous underwater vehicles.
🎓 Education
- M.Tech in Computer Science and Engineering (Artificial Intelligence)
Defence Institute of Advanced Technology (DIAT), Pune
Expected Graduation: May 2027 | Current CGPA: 9.05 - B.Tech in Computer Science and Engineering
Mar Athanasius College of Engineering (KTU)
Graduated: 2024 | CGPA: 9.25 - AISSCE (Class XII)
Hill Blooms School, Mananthavady, Wayanad
Percentage: 95.4% | Year: 2020 - AISSE (Class X)
Hill Blooms School, Mananthavady, Wayanad
Percentage: 93.4% | Year: 2018
🛠️ Skills
- Languages: Python, C, Java, SQL
- ML/AI Frameworks: PyTorch, Hugging Face Transformers, LoRA, PEFT, Scikit-learn, Pandas, LangChain, ChromaDB, Sentence Transformers, YOLOv8, BYOL
- Tools & Platforms: Git, Docker, FastAPI, Google Colab, Unix/Linux, VSCode
- Techniques: LLMs, Parameter-Efficient Fine-Tuning, Retrieval-Augmented Generation (RAG), Transfer Learning, Computer Vision, Self-Supervised Learning
💡 Interests
- Large Language Models & Parameter-Efficient Fine-Tuning
- Retrieval-Augmented Generation
- Computer Vision & Deep Learning
- Open-source software (FOSS) & Linux
- Technical writing & knowledge sharing