CHINMAYI SREE CHITRA CHANNAPRAGADA

Result-oriented Computer Science graduate student with a strong background in Python development and testing, coupled with a comprehensive understanding of object-oriented programming. Dedicated to delivering high-quality solutions, adept at problem-solving, and experienced in working under the Agile methodology. Proficient in Python, MySQL, and Selenium, seeking hands-on technical internships to apply and further develop software development skills in a software developer role.

IEEE (2022 4th International Conference on Artificial Intelligence and Speech Technology (AIST)):

• Developed an image restoration technique using deep learning, based on the IN-PAINT_TELEA method, for repairing and restoring images.
• Utilized a Convolutional Neural Network (CNN) to compare the restored images with their original counterparts, analyzing landscapes and human subjects to diversify the data, and evaluated model performance through metrics such as before and after image comparison, overall accuracy, confusion matrix, and precision score.

International Research Journal of Engineering and Technology (IRJET):

• "Automatic Detection of Suspected Vehicles" introduces an automatic license plate recognition system and text extraction using Optical Character Recognition for vehicle license plates.
• The system is designed to operate effectively under various conditions and accommodate a large number of number plates.

Co-Authored & Published an article “Design Intelligent Machine Learning Classifiers in Healthcare Sectors for Diagnosis Accuracy” in International Journal of Cardiovascular Disease Research, Vol.12, Issue 05, 2021

Co-Authored & Published an article “ A Survey on Machine LearningAlgorithms in Credit Card Fraud Detection” in International Journal of Techno-Engineering,Vol.3, 2021

Co-Authored & Published an article “Automatic Detection of Suspected Vehicles” in International Research Journal of Engineering and Technology, Volume 7, Issue 5, May 2020

Certified in Agile Scrum Master from Simplilearn

Image Repair and Restoration Using Deep Learning, CSUF

• Proposed an image restoration technique using deep learning, based on the IN-PAINT_TELEA method, followed by a CNN for comparative analysis of restored and original images. Analysis included diverse landscape and human subject images.
• Developed a CNN model that accepts damaged images, identifies missing information, and aims to repair and restore the images. Model performance was validated through before and after image comparison, overall accuracy, confusion matrix, and precision score metrics.

Big Data for Tourism, CSUF

• Developed a location-based itinerary generation system using Python, integrating the Yelp API for querying and sorting tourist attractions based on user-specified locations. Implemented dynamic adjustment of rating thresholds and randomization of attractions for diverse and personalized itineraries.
• Implemented Kafka message publishing and consumption to exchange attraction data, along with functionality for saving itineraries to both text and CSV files. Additionally, demonstrated proficiency in HDFS data management, including storing, checking file presence, and converting files between formats for efficient data processing.