- 🔭 Actively building end-to-end systems: RAG pipelines, document intelligence, scalable data workflows, and model deployment.
- 🌱 Interested in bridging research-grade models with real production constraints: retrieval, evaluation, MLOps, and AWS-native GenAI stacks.
- ⚡ Outside tech, I’m a self-taught artist exploring realism and abstract acrylic work.
Highlights
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Detecting-Depression-with-a-Flask-Application
Detecting-Depression-with-a-Flask-Application PublicFlask based application using to detect depression for transcripts of interviews from patients
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arviz
arviz PublicForked from arviz-devs/arviz
Exploratory analysis of Bayesian models with Python
Python
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Multimodal_LLM_Document_Bot
Multimodal_LLM_Document_Bot PublicAdvanced multimodel multilingual LLM chatbot that used Langchain, LLama Parse, OCR and RAG . Mistral AI and LLama2 7b used
Python
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Agentic-Multi-Modal-Interview-Readiness-Coach-IRC-
Agentic-Multi-Modal-Interview-Readiness-Coach-IRC- PublicIntelligent interview prep system: analyzes resume/JD, identifies skill gaps, generates adaptive study plans, provides AI-evaluated practice, tracks mastery. LangChain + FastAPI + React.
Python
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Ask-the-Web-Agent
Ask-the-Web-Agent PublicAsk the Web Agent is a lightweight full-stack AI app that searches the web in real time and summarizes answers using a local LLM via Ollama. It combines FastAPI, DuckDuckGo search, and a React UI t…
Python
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