About Me
Motivated and innovative Machine Intelligence student at Digital University Kerala with a solid foundation in computer science and a passion for solving real-world problems using AI/ML technologies. Skilled in Python programming, deep learning, data analytics, and web development.
Current Education
M.Sc. in Computer Science (Machine Intelligence)
Kerala University of Digital Sciences, Innovation and Technology
2024 – 2026 (Ongoing)
Previous Education
B.Sc. in Computer Science
College of Applied Science IHRD, Kozhikode
Completed: 2024
Contact Information
Technical Skills
Hover over each category to explore my expertise and experience
Programming Languages
Proficient in multiple programming paradigms with strong problem-solving abilities
Python
JavaScript
C
C++
Web Development
Full-stack development with modern frameworks and responsive design principles
HTML/CSS
Django
React
Node.js
AI/ML & Data
Specialized in machine learning, deep learning, and data analysis with practical applications
Deep Learning
TensorFlow
Computer Vision
Data Analytics
Cognitive Computing
Tools & Databases
Experienced with development tools, database management, and cloud platforms
PostgreSQL
MySQL
VS Code
Google Colab
Featured Projects
A showcase of my recent work in AI/ML, web development, and innovative tech solutions







AI-Enhanced PREDICT-ASD is a web-based platform designed to support early screening and management of Autism Spectrum Disorder (ASD) in children. It integrates standardized questionnaires, interactive game-based assessments, AI-assisted preliminary risk evaluation, and real-time caregiver–clinician communication within a secure, role-based system. The platform aims to improve accessibility, engagement, and coordination in early ASD screening and intervention.

This project investigates how sleep deprivation disrupts brain network stability by modeling the brain as a dynamic functional connectome. Using time-resolved fMRI connectivity and Graph Attention Networks, the study aims to predict hallucination-prone states and identify critical prefrontal–sensory disconnections responsible for reality-monitoring failure.