I build intelligent systems that bring clarity, precision, and scalability to complex engineering challenges.
From ML pipelines to full-stack systems — I engineer solutions that work in the real world.
From the first dataset to the final deployment, I build end-to-end solutions that handle real-world scale and complexity — quietly, precisely, at speed.
End-to-end ML pipelines, NLP systems, and computer vision applications built to deliver measurable business outcomes.
Database schema to production UI — Django, Laravel, every layer built with intention, performance, and scale in mind.
SCADA analysis, NLP extraction, daily production reports — turning raw operational data into actionable insights at scale.
I craft systems that work with your goals, not against them — designed for scalability, clarity, and real-world impact.
I build AI systems and full-stack applications. But, most importantly, I engineer solutions that carry the computational weight — so teams can focus on what truly matters and organizations move with confidence, not confusion.
Crafted with precision. Shipped with confidence.
Download CVProficient in Python, C, C++, and Java for core systems. Production web apps with Django and Laravel; frontend with HTML, CSS, JavaScript, and Bootstrap.
End-to-end ML pipelines with PyTorch, TensorFlow, and scikit-learn. Computer vision with OpenCV; NLP with SpaCy. Data analysis and visualization with Pandas, NumPy, and Seaborn.
Containerization with Docker, version control with Git/GitHub/GitLab. Databases: MySQL, PostgreSQL, MongoDB, SQLite, Oracle, Firebase. Linux-native workflow with VSCode and Jupyter.
AI-powered IELTS Speaking platform. Real-time speech recognition and NLP analysis for fluency, vocabulary, and grammar evaluation.
Automated scraper handling 100k+ photos via Selenium. Kivy GUI, multi-threading, and album metadata extraction.
Enterprise Laravel app supporting 1000+ users. Deployed on ONGC Mehsana servers, reducing issue resolution time by 50%.
NLP chatbot processing YouTube transcripts via Hugging Face RoBERTa and GPT-2 to answer queries with 99% precision.
Face recognition-based attendance system with real-time detection and multi-database architecture for scale.
Car price prediction achieving 100% accuracy. Full ML pipeline with preprocessing, normalization, and hyperparameter tuning.
Email spam detection using Naive Bayes. Learns from labeled data to accurately classify spam vs. legitimate mail.
SVM-based handwritten digit classifier on the MNIST dataset. Classifies digits 0–9 with high accuracy.
