I specialize in building intelligent, data-driven systems that turn complex data into scalable AI solutions. My work focuses on machine learning, deep learning, and production-ready models using Python, TensorFlow, and Scikit-Learn.
I am an AI Engineer focused on designing, building, and deploying intelligent systems that solve real-world problems. My expertise spans machine learning, deep learning, and pretrained models, with hands-on experience in Python, TensorFlow, NLP, and data analytics. I enjoy transforming raw data into scalable AI solutions that improve automation, decision-making, and product intelligence.
Designing & deploying production-ready AI models
Deep learning, NLP & generative AI systems
Data analytics, visualization & insight-driven solutions
2.5+
Years Experience
20+
Projects Completed
06/2022-12/2022
A comprehensive toolkit spanning AI model development, data analytics, cloud platforms, and modern web technologies—focused on building scalable, production-ready intelligent systems.
2019-2023
GPA - 3.58/4.0 | CGPA - 8.94/10.0
2018-2019
Percentage - 61.60%.
2016-2017
Generative AI / NLPBuilt a Retrieval-Augmented Generation (RAG) based first-aid chatbot capable of delivering contextual, accurate responses using external knowledge sources. Integrated vector search with transformer-based models to enable dynamic retrieval and response generation. Deployed as a full-stack solution with an intuitive UI and backend server.
Generative AI / NLPBuilt a Retrieval-Augmented Generation (RAG) based document reader capable of extracting key information from documents in real time. Combined vector search with transformer language models to enable precise retrieval and context-aware response generation. Developed a clean user interface and scalable backend API for fast document ingestion and query resolution.
NLP / Machine LearningDeveloped an advanced NLP-based system to identify semantically similar and duplicate questions, achieving an accuracy of 83.25%. Implemented robust text preprocessing, feature engineering, and deep learning techniques, and designed a scalable data processing pipeline capable of handling large datasets for real-world deployment.
Computer VisionDesigned and implemented a real-time automated attendance system using facial recognition. Achieved accuracy rates of 96.82% with CNN and 96.97% using ResNet50 through extensive model training and optimization. Automated attendance record generation into structured CSV files for efficient data management.
Data AnalyticsPerformed in-depth analysis of e-commerce purchase data to identify growth trends, top markets, best-selling categories, and payment preferences. Built interactive dashboards with detailed charts, enabling stakeholders to make data-driven business decisions and optimize strategy.
Computer Vision / Deep LearningDeveloped a deep learning-based system for detecting pests and diseases in rice plants with an accuracy of 96%. Deployed the model using Flask for real-time detection, built a responsive web interface, and engineered an Android application to enable on-the-go agricultural disease monitoring.
