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bhargavakrishna14/README.md

Hey 👋, I'm Bhargava Krishna Ikkurthi !

  • I'm working on full-stack application development with Spring and React.

  • I’m currently learning React


linkedin

Glad to see you here!


🎓 Education:

Master of Technology (M.Tech) in Computer Networking

🏛️ Maulana Azad National Institute of Technology, Bhopal, Madhya Pradesh

📚 CGPA: 7.32 📅 Sep 2021 – Jul 2024

Bachelor of Technology (B.Tech) in Computer Science and Engineering

🏛️ Gayatri Vidya Parishad College of Engineering(A), Visakhapatnam, Andhra Pradesh

📚 CGPA: 7.25 📅 Aug 2016 – Oct 2020


💼 Experience:

👨‍💻 Student Intern 🏢 Siemens Digital Industries Software India Pvt Ltd, Pune, Maharashtra 📆 Jul 2022 – May 2023

  • Integrated PII encryption measures into services and developed a Java Swing utility for secure data decryption.

  • Resolved Compile Time and Runtime errors during the migration of services from Java 8 to Java 11.

  • Undertook the PoC to automate the task of fixing security vulnerabilities using Gradle Version Catalog.

  • Increased SonarQube Code Coverage and Reduced Code Smells


🚀 Projects:

E-COMMERCE MICROSERVICES BACKEND (April 2025 – May 2025)

Developed RESTful microservices using Spring Boot and Spring Cloud (Eureka, Gateway, Config).
Used Kafka for async communication, PostgreSQL/MongoDB for storage, and Docker Compose for deployment.
Integrated Zipkin for distributed tracing and MailDev fortesting email notifications.

Bank Security Application (Nov 2024 – Dec 2024)

Developed a secure banking system with userregistration, account management, card services, and investments. Built Admin Panel with JWT authentication and role-based access control, accessible only to users with admin roles.

SegFormer Based UNet Model For ICH Segmentation (Feb 2024 – Jul 2024)

Designed a Transformer-based U-Net model, surpassing U-Net, U-Net++, and other variants in segmentation performance achieving a DSC score of 86.80% and IoU of 85.90%.

Transformer Based Human Activity Recognition Model (Jul 2023 – Jan 2024)

Adapted the Transformer model fortime-series analysis of motion sensor data, utilizing self-attention to achieve 99.2% accuracy, outperforming conventional ML methods.


🔧 Skills:

Languages: Java, Python, SQL, HTML/CSS, JavaScript

Frameworks: Spring Core, Spring Boot, Spring Data JPA, RESTful APIs, Spring Security, Spring Cloud

Databases: MySQL, PostgreSQL

Tools & Technologies: Git, Maven, Gradle, IntelliJ, Jira, Postman

Other: Data Structures & Algorithms (DSA), Operating Systems (OS), Computer Networks, Database Management Systems (DBMS).


Popular repositories Loading

  1. ICH-Segmentation ICH-Segmentation Public

    SegFormer based UNet Model for ICH Segmentation using CT scan Images

    Jupyter Notebook

  2. HAR-Transformer HAR-Transformer Public

    Transformer for Human Activity Recognition

    Jupyter Notebook

  3. E-commerce-Website E-commerce-Website Public

    Complete E-Commerce Website project showcasing HTML, CSS, and JavaScript functionalities.

    HTML

  4. Iris-Species-Classification Iris-Species-Classification Public

    Jupyter Notebook

  5. Fake-News-Detection Fake-News-Detection Public

    Jupyter Notebook

  6. github-profile github-profile Public