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Software Developer with less than a year in MERN Stack, AI/ML & Cybersecurity.
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Software Developer building scalable full-stack web applications using the MERN stack. Developed real-time chat apps and AI/ML models delivering measurable performance and efficiency. Proficient in Java, Python, C, SQL with a solid foundation in DSA and OS, creating clean, maintainable, and high-performance solutions.
Thangal Kunju Musaliar College of Engineering, Kollam, Kerala
B.Tech · Computer Science & Engineering
November 1, 2021 – May 1, 2025
SenseLearner Technologies Pvt Ltd
Cyber Security Intern
September 1, 2023 – October 1, 2023
India
SNN-Based Social Media Threat Detection
June 1, 2026 – June 1, 2026
• Developed an energy-efficient SNN model using LIF neurons for cyber threat detection from social media data. • Engineered multi-modal feature fusion combining text, structural, and URL-based data for robust threat detection. • Validated model performance, achieving 95% test accuracy and a Macro F1-score of 90%, optimized for low-power, real-time detection on constrained devices.
ChitChatty - Full-Stack Real-Time Chat Application
June 1, 2026 – June 1, 2026
• Engineered a scalable full-stack real-time chat application using MERN Stack, implementing bidirectional communication with Socket.io for instant messaging and typing indicators. • Architected predictable state management with Redux and managed scalable image storage using Cloudinary. • Developed and validated all backend endpoints with Node.js + Express, ensuring functionality via Postman testing.
Dr. Green - Cross-Platform Plant Disease Detection
June 1, 2026 – June 1, 2026
• Developed a cross-platform mobile application using Flutter for plant disease detection and prevention. • Trained and integrated a CNN model with Adam optimizer to analyze user-uploaded images, achieving about 92% predictive accuracy. • Delivered automated guidance on preventive measures and disease management strategies.
The Complete Python Programmer: From Scratch to Applications
Udemy
June 1, 2026 – Present
Data Structures and Algorithms using Python
NPTEL
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's diverse project portfolio, including full-stack web development, AI/ML, and mobile application development, suggests a broad interest in technology and a willingness to explore different domains. This aligns well with a dynamic environment that values continuous learning and cross-functional contributions. The internship in cybersecurity also shows a breadth of technical exposure.
Soft Skills & Operational Fit
The candidate demonstrates analytical and problem-solving skills through project development and internship experience. The ability to research and publish findings (Medium articles) suggests good documentation and knowledge-sharing capabilities. The project diversity indicates adaptability and a proactive learning attitude.