A dynamic and results-driven student and developer, recognized for successfully executing high-impact projects within tight deadlines while maintaining excellence and innovation.CARRER GOAL
To pursue a career in software development in an organization where I can use my talents and skills to grow and expand an organization as well as myself. Also, skills in testing and coding will be useful while delivering a service to a customer.
View Resume Download ResumeContributed to PRISM, Intel’s internal analytics platform, by adding CSV export for Material-UI tables to improve reporting efficiency and reduce manual data handling. Built ReactJS logic integrated with MUI components to enable downloadable, filterable, and paginated data tables across 3+ enterprise dashboards.
At CISCO, I worked as a Software Engineer Intern, where I built an AI automation system using LangChain and LLMs to streamline software patch deployment, testing, report generation, and dashboards on router hardware systems. I also developed a Webex chatbot with four intelligent agents for patch loading, Jenkins execution, and log analysis, accelerating regression testing and reducing debugging time by 38%. The solution improved timely test result visibility for stakeholders and cut manual effort across workflows.
I worked on the NCCS project, developing its homepage using ReactJs, Spring Boot, MySQL, and Thymeleaf to create a seamless and responsive user experience. I integrated APIs and optimized data flow between the frontend and backend, ensuring efficient communication. Additionally, I enhanced the UI/UX, improving navigation, accessibility, and overall design. On the backend, I contributed to secure data management and database operations, ensuring reliability.
In the POTP project at C-DOT, I worked on hardware and software integration for ROADM5 systems, ensuring seamless communication across 8T, 12T, and 4.8T networks. I contributed to testing and debugging hardware configurations, including processors like 82xx, 85xx, and T1022. Additionally, I provided software and database support, implementing NTP software for embedded systems and troubleshooting non-functional cards.
At Infosys, I worked as a Digital Specialist Engineer, where I helped build a scalable MERN stack web application for a major client. My role involved working on both frontend and backend, improving UI/UX with React.js and managing data flow using Node.js and MongoDB. I collaborated with my team to optimize performance, responsiveness, and user experience, ensuring a smooth and efficient application.
Pursuing M.Tech in Computer Science & Engineering at NIT Warangal, specializing in Machine Learning, Deep Learning, Data Mining, and System Design. Excited to explore new technologies and build innovative solutions!
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Completed B.Tech in Computer Science & Engineering from Maharaja Agrasen Institute of Technology (IP University, Delhi). Built a strong foundation in Full-Stack Development, Data Structures & Algorithms, and System Design. Excited for the journey ahead!
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Completed 12th (CBSE) from Abhinav Public School, Delhi, securing 91.4%. Grateful for the experiences, friendships, and lessons that shaped my academic journey!
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Completed 10th (CBSE) from Gateway International School, Baghpat, securing a perfect CGPA of 10.0. Cherishing the memories and lessons that sparked my curiosity and shaped who I am today.
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Worked as a College Fest Organizer in our college fest named Techsurge and Mridang and organized a Kho-Kho tournament in which more that 50 students participated.
VisitVolunteered for more than 1 year for our college society Leaders for Tomorrow and collaborated in a team of 10 fellow volunteers to help children with food and books in New Delhi.
VisitA full-stack campground review platform with CRUD operations and search functionality. Built with Node.js, Express, MongoDB, and React. Features user authentication, campground management, and review system.
View ProjectML-powered disease prevalence estimation using CatBoost and XGBoost algorithms. Features data analysis and predictive modeling for early detection, demonstrating advanced machine learning implementation in healthcare diagnostics.
View ProjectTrustX-Defect is an explainable AI pipeline that predicts software defects from tabular datasets and pairs strong model performance with transparent SHAP-based insights. It automates preprocessing, cross-validated training, and reliability analysis so teams can trust and interpret their defect forecasts.
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