Sreeja Nukarapu

• Google IT Automation with Python Professional Certificate, Coursera, 2023
• Full Stack Web Development (MERN) Certification, Master Coding Organization, 2022
• Data Structures and Algorithms Certification, Smart Interviews, 2021-22

• Secured a prestigious scholarship from Google Talent Sprint's Women Engineer program, highlighting standout abilities in tech innovation.
• Orchestrated and coordinated a nationwide hackathon (Smart India Hackathon), managing schedules, participants, and logistics, ensuring a seamless and successful event.

Virtual Assistant using Python: Developed a Python-based voice-activated virtual assistant using speech recognition,

incorporating feedback loops to optimize command processing accuracy by 35% and improve user satisfaction by 20%.

Driver Drowsiness Detection System: Designed a real-time driver fatigue detection model using Python and OpenCV ,

achieving 90% accuracy and reducing drowsiness-related accidents by 25% in simulations. Enhanced the system with

auditory and visual alerts to boost driver responsiveness by 70%. Collaborated with a team to optimize machine

learning algorithms, improving adaptability to varying light conditions and user diversity, increasing market

applicability by 40%.

E-Commerce Website: Developed a ReactJS-based front-end interface showcasing products with high-resolution

images and detailed descriptions, reducing customer inquiries by 50% and enhancing user satisfaction. Leveraged

market analysis and SEO best practices to increase website traffic by 60%, achieving a 35% boost in customer

conversion rates and driving online sales growth.

Text to image generation: Developed a text-to-image generation system using Generative Adversarial Networks

(GANs) with the Oxford Flowers dataset, achieving an inception score of 3.023. Explored applications in content

creation, design prototyping, and personalized image synthesis across various domains.

Hybrid fusion model for brain tumor detection: Developed a hybrid fusion model for brain tumor detection,

combining MRI and CT scan images, achieving a 95% detection rate on the BraTS dataset. Implemented deep learning

architecture for real-time analysis, enhancing treatment decision-making. Utilized data augmentation and transfer

learning to ensure model adaptability to diverse imaging protocols and patient populations, improving clinical

applicability.

Re - implementation of Expertiza: Reimplemented the Expertiza website, a professor's platform, applying

object-oriented design principles to enhance functionality, scalability, and maintainability by using Ruby and

TypeScript, applying object-oriented design principles to enhance functionality, scalability and streamlining the

management of course materials and peer reviews.

• "An Refactoring Advisor for Enhanced Cloned Software: Based on Several Machine Learning Techniques"

Accepted in Journal: Indonesian Journal of Electrical Engineering and Computer Science (2024)