Final Year B.E. Computer Engineering, Pune Institute of Computer Technology (PICT)
I build backend systems, AI/ML applications, data pipelines, cloud-native services, and robotics software. My work spans Generative AI & LLMs, RAG, distributed systems, computer vision, data engineering, autonomous UAVs, and full-stack development.
I enjoy taking problems from an initial idea to a working system — designing the architecture, writing the code, testing it, debugging failures, and integrating different components into a reliable solution.
- 🔭 Currently working on secure LLM/RAG pipelines, AI systems, and backend engineering
- 🌱 Deepening my knowledge of distributed systems, cloud-native architecture, MLOps, and AI agents
- 🤖 Building systems around robotics, UAVs, computer vision, and autonomous navigation
- 🧠 Exploring LLMs, RAG, LoRA/PEFT, adversarial ML, and AI infrastructure
- 🌍 Interested in open source, software engineering, AI/ML, and scalable systems
- 💬 Ask me about Python, backend engineering, AI/ML, computer vision, robotics, or system design
I actively explore and contribute to open-source projects by working with existing codebases, understanding issues, implementing fixes, writing tests, and following collaborative Git/GitHub workflows.
- gVisor — Worked with the gVisor codebase and contributed fixes through issue-based development, debugging, and validation.
- eksctl — Contributed to the official CLI for Amazon EKS by working on reported issues, implementing fixes, and adding/validating tests.
- py-gpt — Worked on security and stability improvements, including issue investigation and code-level fixes.
- SoL-Pi — Worked on the project and contributed to its development and implementation.
- More open-source work — Exploring and contributing to additional repositories across AI, backend engineering, developer tooling, and systems.
My open-source workflow focuses on understanding the existing architecture first, reproducing issues, implementing targeted changes, testing the solution, and keeping changes maintainable.
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Microservices · Distributed Systems · System Design · CI/CD |
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LLMs · RAG · LoRA/PEFT · Adversarial ML · TreeSHAP |
ETL Pipelines · Data Processing · Feature Engineering · Data Validation |
AWS S3 · EC2 · DynamoDB · CI/CD · Containerization |
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UAVs · FreeRTOS · Computer Vision · MAVSDK |
DBMS · Querying · Data Modeling · Database Fundamentals |
Data Structures & Algorithms Object-Oriented Programming Operating Systems DBMS Computer Networks System Design Testing & Debugging |
| Area | Work |
|---|---|
| 🧠 AI / ML | Computer vision, classification, fraud detection, adversarial ML and ML pipelines |
| ✨ GenAI | LLM applications, RAG, LoRA/PEFT and secure enterprise AI |
| ⚙️ Backend | REST APIs, FastAPI, Flask, WebSockets, microservices and distributed components |
| 📊 Data Engineering | ETL pipelines, large-scale data processing, feature engineering and validation |
| ☁️ Cloud | AWS, Docker, CI/CD and cloud-native application development |
| 🔐 AI Security | Adversarial ML, Red-Team/Blue-Team systems, PII protection and data governance |
| 🌱 AI Infrastructure | Carbon-aware inference routing and efficient AI systems |
| 🤖 Robotics & UAVs | Autonomous navigation, LiDAR mapping, landing-zone detection, telemetry and mission control |
- 🥇 AIR 1 — ISRO IRoC-U Robotics Challenge 2025
- 🏅 AIR 9 — DD Robocon India 2026
- 📝 Best Technical Report Award — DD Robocon India 2026
- 🛰️ Top 28 / 8,744 Teams — ISRO Bharatiya Antariksh AI/ML Hackathon 2025
- 🧠 82% accuracy — EEG/BCI ML classification system