Fullstack Engineer with less than a year in Java, Spring Boot & MERN Stack.
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
Information Science Engineering graduate with a strong foundation in full-stack development, Core Java, and web technologies. Experienced with Spring Boot, JavaScript, HTML5/CSS3, and MySQL. Proficient with Git, GitHub/GitLab, and Maven across the development lifecycle. Known for writing clean, logical code with a strong enthusiasm for building practical software solutions.
Rajeev Institute of Technology
Bachelor of Engineering · Information Science and Engineering
August 1, 2022 – June 30, 2026
G H S Jalmangala
Secondary School Leaving Certificate (SSLC)
N/A – May 31, 2020
B G S College, Magdi
Pre-University Course (PUC)
N/A – May 31, 2022
JSpiders Software Testing and Development Institute
Java Full Stack Training
January 1, 2026 – April 1, 2026
Bengaluru, Karnataka, India
MindMatrix.io (Product of CL Infotech Pvt. Ltd.)
Android App Development Intern (GenAI)
September 1, 2025 – December 1, 2025
Bengaluru, Karnataka, India
Expense Tracker
June 24, 2026 – Present
• Developed a full-stack Expense Tracker application to record, categorize, and analyze personal expenses. • Built a responsive React.js frontend with intuitive forms and dashboards for viewing expenses and summaries. • Implemented RESTful APIs using Node.js and Express.js to handle expense CRUD operations and user management. • Designed MongoDB schemas for users, expenses, and categories with efficient data retrieval.
Website Audit Tool Security & Performance Analysis
June 24, 2026 – Present
• Developed backend services using Java and Spring Boot to analyze website security headers and performance metrics. • Implemented features to check HTTP security headers, SSL status, open ports, and basic vulnerability indicators.
Fake Face Detection in Video Frames Using Deep Learning
June 24, 2026 – Present
• Built a web app to classify videos as real or fake using ResNext CNN + LSTM deep learning architecture achieving up to 97.76% accuracy. • Preprocessed 6,000 videos across 3 datasets using OpenCV for face detection, cropping, and frame extraction. • Applied transfer learning with pre-trained ResNext-50 for feature extraction and LSTM for temporal inconsistency detection. • Deployed the application on Google Cloud Platform (GCP).
Cultural Fit Analysis
The candidate has engaged in diverse academic projects spanning full-stack web development, deep learning, and security analysis, indicating a broad interest in technology. The internships, though short, show an eagerness to gain practical experience. This diversity suggests adaptability and a willingness to learn new domains, which can be a good cultural fit for dynamic environments. However, the experience level is very low (0 years), which might require significant mentorship in a senior role.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex problems and deploy solutions, suggesting problem-solving and execution skills. The academic projects and internships show a proactive learning attitude. However, without specific behavioral assessment data, a detailed analysis of soft skills like teamwork, leadership, or conflict resolution is not possible.