"Engineering the space of Backend and Artificial Intelligence, and turning abstract systems into realities."
- 🌌 Exploring Agentic AI Systems & RAG Architectures
- ⚡ Designing scalable backends with Flask, FastAPI & serverless Azure Functions
- 🛰️ Automating Geospatial AI with Google Earth Engine & LLMs
- 🧪 Experimenting with model validation, fine-tuning, and vector databases
| Domain | Tools & Frameworks |
|---|---|
| AI/ML | PyTorch · HuggingFace · LangChain · LangGraph · Transformers · Wav2Vec2 · LLMs (Llama3, Qwen) |
| Backend | Flask · FastAPI · REST APIs · PostgreSQL · MySQL · Pydantic |
| Cloud/DevOps | Azure AI (Search, Storage, Function Apps) · Docker · Git · Postman |
| Geospatial | Google Earth Engine · PostGIS |
| Languages | Python · C++ · C |
🔵 AI Intern @ Siemens DISW (2025 – Present)
Building scalable agentic pipelines on Azure AI, integrating RAG + serverless backends.
🛰️ Project Intern @ ISRO (2024–25)
Developed REST APIs combining LLMs + Earth Observation Data for geospatial automation.
AI-powered productivity agents orchestrating Notion & email workflows.
🔗 View Project
Speech-to-text pipeline fine-tuned on Wav2Vec2-BERT, deployed to Hugging Face Hub.
🤗 View Model
- 🥇 ISRO Bhartiya Antariksh Hackathon – Winner
- 🥈 Citi Campus Innovation Challenge 5.0 – Top 5 Finalist (out of 1743 teams)
- 🏅 Multiple Hackathon Wins in AI/ML & Generative AI
- 📄 Research Publications in Springer & Scopus (Flood Prediction, Healthcare AI)
flowchart TD
A((Backend Systems)) --> B[APIs]
A --> C[Databases]
A --> D[Scalability]
E((AI/ML)) --> F[Agentic Systems]
E --> G[RAG Pipelines]
E --> H[ASR Models]
I((Cloud)) --> J[Azure AI]
I --> K[Serverless]
I --> L[Docker]
