Education:-

• Bachelor of Technology in Electronics and Communication Engineering, Andhra University College of Engineering, India. 2020-2024
  Relevant Coursework: Microprocessors, PLCs, Industrial Automation, and Communication Systems
  CGPA: 7.48/10.0


• Intermediate Education, Narayana Junior College, Andhra Pradesh, India. 2018-2020
  CGPA: 8.89/10.0


• Secondary Education, MP & EV English Medium School, Visakhapatnam, India. 2017-2018
  Percentage: 60%

Internships:-

• Intern at Strugger Innovations, India. 2024/06–2024/07


•    Gained hands-on experience in Siemens and Allen Bradley PLCs, designed and configured SCADA systems and HMI interfaces for real-world industrial applications.


• Project Intern at RINL Visakhapatnam, India. 2023.06–2023.07


• Studied and analyzed the application of microprocessors and PLCs in industrial environments, focusing on automation systems.

Certifications & Awards:-

• MERN Stack Development Course. NxtWave. 2024.02–Ongoing
• Currently enrolled in a comprehensive MERN stack course to enhance full-stack web development skills.


• PLC and SCADA Training Certification. Strugger Innovations. 2024
• Received specialized training in automation technologies, focusing on Siemens and Allen Bradley PLCs.


• Class Representative. Andhra University College of Engineering. 2020–2024
• Elected as Class Representative for 5 semesters, demonstrating leadership and communication skills.


• Volunteer at Job Mela. Andhra Pradesh Government. 2023
• Assisted in organizing and managing the Job Mela event, contributing to its success.

Projects:-

• IoT Project on Arduino Uno with LDR Sensor. 2024
• Developed an automated lighting system using an Arduino Uno and LDR sensor to adjust lighting based on ambient light levels.
• Enhanced energy efficiency by automating lighting control, contributing to smart home automation.


• Fake Currency Detection Using Machine Learning. 2023
• Designed a counterfeit detection system using image processing and machine learning algorithms, achieving high accuracy in identifying fake currency notes.
• Implemented advanced data processing techniques for precise detection and validation.