I am a final-year student at Shri Vishnu Engineering College for Women, pursuing a Bachelor of Technology in Artificial Intelligence and Data Science. With a strong academic record (CGPA 9.31/10), I have built expertise in programming, web technologies, and data-driven problem solving. Over the years, I have worked on impactful projects, including a Product Review Analysis Dashboard for sentiment insights, a Smart Notepad with security and accessibility features, and a News Report platform with personalized content delivery. My learning journey has also been shaped by hands-on experiences as a finalist in the Adobe India Hackathon 2025 and AeroHack 2025, where I designed innovative AI and algorithmic solutions. Beyond academics, I actively contribute to collaborative initiatives such as the Wikimedia Technology Summit and interdisciplinary IoT projects at IDEA Lab. I am passionate about Artificial Intelligence, Data Science, and Software Development, and I am seeking opportunities to apply my skills in solving real-world challenges while continuously growing as a technologist.
My favorite languages for systems programming, software engineering, and data analysis.
My preferred technologies for front-end web development and component design.
My preferred technologies for back-end web programming and database architecture.
My favorite tools for version control, code editing, and container orchestration.
Created a system to scrape and preprocess product reviews, analyze sentiment, and generate concise summaries. Designed an interactive dashboard using Streamlit to present insights clearly, enabling quick understanding of customer opinions.
Check it out!Developed a secure, voice-enabled notepad with password-protected access and accessibility features. Integrated text-to-speech and encryption-based storage to ensure privacy and efficient note management.
Check it out!Built a web-based news platform with dynamic category-based content filtering, enabling personalized news delivery. Enhanced user engagement by tailoring content to individual preferences.
Check it out!Designed and implemented a machine learning model to predict calories burned based on physical activity parameters. Achieved 85% prediction accuracy, making it a reliable tool for personalized health tracking.
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