A b o u t M e
Currently pursuing a Master of Computer Applications (MCA) degree with a focus on Artificial Intelligence at KL University (2023-2025), I am developing a strong foundation in machine learning, software development, and AI principles. My coursework emphasizes practical application and includes focused study in data analysis and data preprocessing. I am particularly interested in leveraging AI to create impactful solutions in areas like data management and system optimization. I am eager to apply my growing skillset in a professional setting and contribute to innovative projects.
Interests and Hobbies
- Avid Reader: I am passionate about exploring diverse genres of books, from fiction to self-development, constantly seeking new knowledge and perspectives.
- Film and Television: I appreciate the immersive experience of cinematic storytelling and character-driven narratives.
- Creative Writing: I enjoy crafting stories that resonate with emotions and imagination.
- Music Appreciation: I find listening to various genres of music to be a source of relaxation and inspiration.
Skills
- Programming Languages: Python, C, PHP
- Machine Learning: Machine Learning Algorithms (including Supervised Learning, Regression, Multinomial Naive Bayes), Data Preprocessing, Data Analysis
- Web Development: HTML, CSS, Flask
- Data Management: SQL, CSV Data Handling, Data Integration
- Other: Excel, Tkinter, Socket Programming, Documentation, Error Handling
Languages
- Telugu (Native)
- Hindi (Proficient)
- English (Fluent)
- Tamil (Basic)
Recognitions and Achievements
- Monologue Performance: 3rd Prize for performance as Puck in William Shakespeare's *A Midsummer Night's Dream* (Undergraduate).
- Short Story Writing: 1st Prize for "Insomnia" in a short story writing competition (Undergraduate).
- Poetry Writing: 3rd Prize in a poetry writing competition (Women's Day celebration, Undergraduate).
E d u c a t i o n
2023-2025
Master of Computer Applications
KL University
Focus on Artificial Intelligence.
CGPA: 8.6
2019-2022
Bachelor of Science in Computer Science
Annai Violet Arts and Science College
CGPA: 7.1
2016-2018
Intermediate (MPC)
KBN JR College
CGPA: 81%
2015-2016
SSC
MSREMH SCHOOL
CGPA: 7.8
Projects
Disease Prediction
Developed an innovative application leveraging advanced algorithms trained on extensive medical datasets, achieving 91% accuracy in providing preliminary diagnostic suggestions. Enhanced healthcare accessibility by delivering actionable insights for early disease detection and promoting prompt medical consultations. Additionally, created comprehensive technical and functional documentation to ensure the application's scalability and ease of use.
Bi-Directional CSV-SQL Converter
Developed a robust application for bi-directional conversion between CSV files and SQL tables, enabling seamless data transfer and integration. Optimized the system to handle large datasets, including processing CSV files up to 2GB, ensuring scalability and efficiency. Automated data validation and error handling to maintain data integrity during conversions, streamlining workflows for diverse data management needs.
File Sharing
Developed a secure file-sharing platform using Tkinter and Socket programming, allowing users to upload, store, and share files efficiently. The platform features file organization into folders, customizable sharing permissions, and the generation of secure links for accessing files. It supports file versioning, large file uploads, and previews for common file types, enhancing the overall user experience. Additionally, real-time notifications and usage analytics were integrated to foster improved collaboration and usability. I focused on ensuring robust data security and optimized performance, making the system capable of handling diverse user needs effectively.
E x p e r i e n c e
MAY 2024- JULY 2024
Intern Data Science, Machine Learning, and Artificial Intelligence
Brain O Vision
As an intern, I worked on developing a disease prediction system using the Multinomial Naive Bayes algorithm to analyze user-reported symptoms and predict potential health conditions. I processed and cleaned large datasets to improve model accuracy, trained and fine-tuned the algorithm, and integrated the system with Flask for seamless deployment. Additionally, I documented the technical aspects of the project to ensure clear knowledge transfer for future development.