Nikhilesh Gandla

As a dedicated and hardworking Computer Science student pursuing a Bachelor's degree at Mahindra University, I possess a strong foundation in programming languages and a passion for contributing to innovative technology projects. Equipped with excellent technical skills in software development and applications, I am eager to further enhance my expertise through a challenging internship. I bring a motivated and responsible approach to ensure efficient and impactful contributions to your team.

Successfully completed Mentorship Program on Data Science from Coratia Technologies, in association with Teachnook.

As a dedicated Computer Science student pursuing a Bachelor's degree at Mahindra University, I excel in programming and problem-solving while maintaining a well-rounded approach to life. Alongside my academic pursuits, I actively engage in daily coding challenges on platforms like CodeChef and LeetCode, continuously improving my technical skills. I also prioritize balancing academics with personal growth by exploring extracurricular interests and collaborating on team projects. This holistic approach reflects my ability to manage multiple aspects of life effectively while striving for excellence in all endeavors.

• Date of Birth : 23/08/2004
• Contact Info : 9963660688
• Email : nikhilesh.gandla@gmail.com

• Enthusiastic about coding and programming
• Passionate coder deeply engaged in competitive programming, consistently honing skills and embracing challenges.
• A dedicated learner with a fervent eagerness to delve deeper into the realms of computer science, languages, and expertise.
• Aspires to make a meaningful impact in the field of computer science and technology
• Staying abreast of cutting-edge technology advancements and discoveries.

• Machine Failure Prediction
  Developed a machine learning model to predict equipment failures using sensor data and historical trends, enabling proactive maintenance and reducing downtime.
• OMR Scanner Using OpenCV
  Designed an Optical Mark Recognition (OMR) system using OpenCV to detect and evaluate marked responses on cards. Implemented image preprocessing, contour detection, and result extraction to automate grading with high accuracy.