Frontend Developer | JavaScript | ML Enthusiast | Ex-Intern Apex Planet & Pinnacle Labs
Aspiring Frontend Developer with a strong foundation in HTML, CSS, and JavaScript, along with hands-on experience in building responsive web applications. I have practical exposure to AI/ML concepts, where I have developed and compared machine learning models achieving up to 96% accuracy. During my internships at Apex Planet and Pinnacle Labs, I worked on real-world projects including a mini blog application and Java-based tools, while improving performance through optimization techniques like lazy loading and reducing HTTP requests. I am comfortable with core frontend development, basic backend workflows, and data analysis using Python libraries such as Pandas and NumPy. I enjoy solving problems, building projects, and continuously learning new technologies. Currently, I am seeking opportunities to apply my skills in real-world environments, contribute to impactful projects, and grow as a developer.
ApexPlanet Software Pvt Ltd
2 mos
Built a responsive Mini Blog application using HTML, CSS, and JavaScript Optimized frontend performance using lazy loading and reduced HTTP requests Worked in a structured environment with deadlines and collaborative tasks
Pinnacle Labs
2 mos
Developed a currency converter application in Java Built a Tic-Tac-Toe game demonstrating core programming concepts
APEX PLANET
Aug 2025-Sept 2025
Built a responsive Mini Blog application using HTML, CSS, and JavaScript. Collaborated on tasks and met project deadlines in a structured internship environment. Optimized frontend performance using lazy loading, reduced HTTP requests, and a custom load-time analyzer.
Pinnacle Labs
July 2025-Aug 2025
Developed a Java program for quick and accurate currency conversion and created a classic Tic-Tac-Toe game in Java.
Bachelor of Technology - BTech, Computer Science
Sep 2023 - Jul 2027
Bachelor of Engineering, Production
Sept 2023 – June 2027
SGPA – 7.5; Bhubaneshwar, India
Secondary Examination (CBSE)
2021
Percentage – 80.2%; Bihar, India
Secondary School Certificate (CBSE)
2023
Percentage – 74.8%; Bihar, India
Developed an end-to-end machine learning pipeline with data cleaning, exploratory data analysis, feature engineering, and modeling. Built and compared Logistic Regression, Random Forest, and Gradient Boosting models, achieving 96% accuracy and evaluating linear versus non-linear performance on imbalanced data. Analyzed factors affecting mobile pricing, market trends, and feature importance.