Formulated and documented Product 360 overview and optimized pipeline for client, achieving a 12% increase in efficiency.
Developed, and integrated websites, external data sources, and AI-driven chatbots, enhancing customer service response time
by 30%.
Collaborated on a team of 10 to migrate CRMnext to a microservices architecture, enhancing scalability by 13%.
Created a real-time analytics dashboard using React and D3.js, improving data visualization for 1,000+ users.
Crafted RESTful APIs, conducted rigorous testing using Postman and Soap UI, and enhanced CRMnext mobile responsiveness with
Bootstrap for 5,000+ mobile users.
Led the management of the MySQL database and optimization of procedures.
Engineered a cost-effective home assistant model leveraging Raspberry Pi, Arduino, and Home Assistant, achieving a 47%
reduction in implementation costs compared to traditional solutions
Produced a user-friendly dashboard using Flutter, enhancing accessibility and control, leading to a 51% surge in user satisfaction
Created a user-friendly National Police Incident Database (NPID) full stack application using semantic web engineering.
Deployed on Amazon EC2 with a 99.9% uptime, ensuring continuous accessibility. Integrated Flask API for seamless data flow,
expanding application capabilities.
Preprocessed data with pandas, analyzing a 1900+ police incidents dataset, generating 42,000+ triples. Built an ontology-based
system for optimized data organization and query efficiency.
Synthesized gaming experience with immersive audio and visual elements, and smooth camera transitions, resulting in a
significant 25% increase in user satisfaction and a 15% boost in player engagement.
Pioneered responsive player controls and refined enemy AI, contributing to a 35% improvement in overall user experience.
Overcame intricate technical challenges through methodical debugging, accomplishing a 40% decrease in critical bugs.
Face Recognition and detection system
Built an advanced face detection and recognition system using OpenCV library and SVM (Support Vector Machine) algorithm.
Utilized advanced feature extraction algorithms to identify crucial facial components (eyes, ears, nose, and mouth).
Attained 91% precision by training an SVM classifier on extracted features for precise face recognition
Directed creation of an innovative and cost-effective IoT(Internet of Things) solution, resulting in a 30% increase in user-machine
interaction for individuals with limited mobility
Engineered a Morse Code Technology-based communication controller, attaining a 40% improvement in user independence
Spearheaded design and development of a user-friendly mobile application, enhancing users overall experience by 25%
Designed and implemented a software system using various design patterns which served as an
auction house for
farmer's market.
Developed numerous software test cases to test the system against potential edge cases to check
the efficiency of the
system.
Publications
Certifications
Get In Touch
If you'd like to talk about a project you want help with or need an advice about sofware
development,
just drop me a message at nagraw18@asu.edu ! I'm currently Open to Work.