Pragathi Kanala

Hello, I am

Pragathi Kanala


With a passion for building impactful, secure, and user centric solutions, seamlessly blending technical innovation with industry compliance to drive meaningful digital experiences.

About Me

I am a Computer Science graduate from Florida Institute of Technology with 2 years of experience in software development, specializing in Java, MySQL, Actimize and web technologies like HTML, CSS, JavaScript, and React. I am passionate about building secure, high-performance applications and have worked on dynamic projects focused on scalability and security. Currently, I am expanding my skills in AWS, Privileged Access Management (PAM), and Identity Access Management (IAM) to stay at the forefront of modern technology solutions.

Skills

C

C++

Python

Java

Restful API

Git

DevOps

AWS

HTML

CSS

JavaScript

jQuery

MySQL

PAM

IAM

Work Experience


Mphasis Limited – Software Engineer (September 2021 – July 2023)


Tools & Technologies: Java, Spring Boot, HTML, CSS, JavaScript,, MySQL, Actimize AML-SAM, AIS, RCM


Key Activities:

Projects

Recipe Finder – Full-Stack Web Application

Developed a full-stack MERN application that allows users to manage a recipe database with features to initialize the database, search for recipes by name, ingredients, or description, and display results in a responsive card layout. Designed the backend using Node.js and Express for data retrieval and manipulation with MongoDB, while the frontend utilized React for a dynamic interface, including controlled form components, recipe cards, and detailed recipe views. Implemented an add-recipe feature with an ingredient auto-suggestion and dynamically updating ingredient lists. Added a favorites system to manage and view favorite recipes, with functionality to remove items from a dropdown list. The application was deployed on AWS EC2 for live access.

Handwritten Digit Recognition using Convolutional Neural Networks

Developed a CNN model to identify the digit '9' from the MNIST dataset using Python, TensorFlow, and Keras. Designed and implemented the CNN architecture, performed image preprocessing with OpenCV, and trained the model to extract key features for accurate predictions. Built a real-time prediction interface using Tkinter, enabling interactive digit recognition. Integrated error detection for multiple digits, ensuring precise single-digit classification. Demonstrated skills in deep learning, image processing, and model deployment using NumPy, OpenCV, and Jupyter Notebook.

Development of a Flutter-Based Agriculture Management Application

Developed DigiFarmer, a cross-platform mobile application using Flutter, Dart, TensorFlow Lite, and LGBM Classifier to provide farmers with AI-driven insights. The app offered features like market price tracking, inventory management, crop monitoring, and real-time weather updates, along with real-time disease diagnosis and crop quality monitoring, even in low-connectivity areas. Ensured secure user authentication, cross-platform compatibility, and GDPR/CCPA-compliant data encryption, aiming to help farmers optimize operations, manage risks, and boost productivity and profitability.

Let's Connect

An open door to connect, share ideas, and discover exciting career opportunities. Explore my portfolio and let's build something impactful together!