Machine Learning • Full-Stack
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🧠 AI Engineer with a focus on building interpretable, production-grade ML systems
⚙️ Leveraging Vision Transformers, Wavelet Analysis, XAI, and LangChain to solve real-world problems
🔬 Architecting pipelines that combine deep learning, structured logic, and scalable infrastructure
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Brain Tumor Classification
96.4% accuracy on enhanced MRI data using ResNet + Vision Transformers.
Integrated SHAP + ScoreCAM for pixel-level tumor explainability. -
Welding Parameter Prediction
Multi-output regression pipeline using deep autoencoders + SHAP
Achieved R² = 0.93 | 5-Fold CV | Ensemble stacked model -
1v1 DSA Duel Platform (Current)
Real-time competitive coding arena using Django Channels, WebSockets, and live judge sync. -
SmartFormFiller (Open Source)
Chrome extension to parse resumes, extract metadata, and auto-fill Google Forms.
PDF parsing + DOM mutation + Chrome Storage APIs. -
Neural Network in C++ (from scratch)
Custom backprop, weight updates, and training loop in raw C++ OOP — no libraries used. -
OsttraGPT (Internship)
Enterprise-grade GenAI assistant using LangChain, Tesseract OCR, and FastAPI.
Reduced QA overhead by 10+ hours/week via automation of metadata extraction.
Languages: Python, C++, JavaScript
Frameworks: PyTorch, FastAPI, Django, React
ML/AI: Vision Transformers, SHAP, LangChain, OCR, Generative AI
DevOps: Docker, Git, SQLite, Chrome Extensions, WebSockets
- Solved 400+ DSA problems across LeetCode
- Delivered real-world ML pipelines used in industry & open source
- Obsessed with performance, explainability, and clean system architecture