Gayathri Kandukuri

Dynamic Associate Software Engineer at Tech Mahindra with expertise in ABAP programming and SAP application support. Proven track record in debugging complex issues and managing change requests, enhancing operational efficiency. Strong collaboration skills with functional teams, driving timely resolutions and successful project outcomes. Proficient in full stack Java and machine learning applications.

AI - ML intern|company - Codegnan

Developed and implemented machine learning models for various real-world applications, worked on projects like house price prediction, spam email classification, sentiment analysis, and handwritten digit recognition, focusing on data preprocessing, feature engineering, model training, and evaluation, gained proficiency in Python, Pandas, NumPy, Scikit-learn, TensorFlow, and data visualization techniques Strengthened problem-solving skills and understanding of supervised and unsupervised learning algorithms.

Customer invoice monitoring and notification system

• Developed a custom SAP ABAP Module Pool application to display pending and cleared customer invoices in a structured tabular (ALV) format.
• Implemented dialog programming (PBO/PAI) with interactive screens for users to review invoice details.
• Enabled approval functionality, where approved invoices trigger outbound file generation for customer notification
• Retrieved and processed invoice data from SAP FI tables, ensuring accuracy and performance optimization
• Incorporated validations, error handling, and user-friendly navigation to enhance usability

CrowdSense Pro: Advanced people counting and social distancing monitoring using Python and machine learning

• Used computer vision and deep learning for public safety applications
• Technologies: YOLOv4, OpenCV, MobileNet-SSD

Learning Tracker

• The Learning Tracker is a simple, yet effective, web-based application designed to help users monitor and manage their personal or academic learning progress. Users can add, update, and mark learning topics as completed The application provides a structured interface to track learning goals, topics covered, and progress over time, ensuring consistent growth and motivation.
• It is especially useful for students, self-learners, or professionals who want to maintain a log of topics
• learned across different technologies or subjects.
• Technologies used: PYTHON, HTML.

Classification of Lung Tumor using Machine Learning

• This project aims to advance lung tumor identification using machine learning techniques in the context of cancer diagnosis and treatment, ultimately improving patient outcomes and survival rates. The primary challenge involves developing a highly accurate and efficient machine learning model capable of early detection and precise identification of lung tumors in medical imaging data, such as CT scans and X-rays

• SAP ABAP - Udemy
• Java Full Stack - Wipro
• Introduction to Machine Learning - NPTEL
• SQL - UDEMY
• Agile Experience program - Cognizant
• Frontend Development - Tap Academy

• Bronze Medalist in Academics - college level
• Bronze Medalist in chess - school level