- 🎓 Senior Undergraduate at VIT-AP University
- 🔭 Currently working on LLM Fine-Tuning, RAG, and AI Safety
- 🌱 Learning advanced MLOps workflows & scalable AI deployment
- 👨💻 All my projects are available on GitHub
- 💬 Ask me about LLMs, RAG, Explainable AI, MLOps
- 📫 Reach me at korivichetan5@gmail.com
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MedIntel – Biomedical QA System
Fine-tuned SciBERT on PubMedQA and built a RAG pipeline with FAISS + Sentence Transformers.
🐳 Deployed with Docker + Streamlit for explainable biomedical Q&A. -
CodeMentor-AI – Coding Interview Assistant
Fine-tuned Flan-T5 on 20k+ QA pairs to provide coding interview prep assistance. -
WatchTowerAI – Log Analysis & Incident Response
LLM-powered log classifier with Slack automation and AWS S3 integration. -
LLMGuard – Prompt Injection & Moderation Toolkit
AI Safety project with real-time unsafe prompt detection and Streamlit dashboard. -
StackGenie – Cloud Release Notes Dashboard
Streamlit + BigQuery-based release notes analyzer with live dashboards and secure auth. -
PriceSense – Laptop Price Prediction
Regression model with R² > 0.73, explainability using SHAP, and drift monitoring.
- BirdZ – Indian Bird Species Detection
Dataset of 6,900+ images across 14 species; trained YOLOv12 achieving mAP@50 = 81%.
Drafting research paper for academic submission.
- Languages: Python, SQL, Bash, JavaScript
- ML/AI: PyTorch, TensorFlow, Hugging Face, scikit-learn, SHAP, FAISS, RAG, XAI
- MLOps/Infra: Docker, Kubernetes, CI/CD, Render, AWS, Hugging Face Spaces, Git
- Data/Cloud: BigQuery, PostgreSQL, pandas, numpy, AWS S3
- Other: Prompt Engineering, AI Safety, LaTeX, Model Monitoring
