Welcome to the about page of a passionate tech enthusiast whose journey into the world of technology began at Heritage Convent, where he completed his HSLC education. Even in those early years, his curiosity for understanding how things work sparked countless hours spent experimenting with computers and imagining innovative solutions.
It was at Heritage Convent that he first discovered his love for building, tinkering with hardware, and diving into programming languages laying the essential foundation for his future in technology.
After completing HSLC, he pursued higher secondary education under COHSEM at MECI Explorer Academy. There, he deepened his programming knowledge, especially in C and C++, and brought several small-scale projects to life each one fueling his ambition and curiosity further.
Driven to expand his horizons, he went on to pursue a B.Tech in Computer Science and Engineering at Royal Global University, marking a major step toward his goal of becoming a full-stack developer. His time at RGU has been characterized by continuous learning, exploration, and hands-on project work.
Throughout his academic journey, he has remained committed to mastering the full software development lifecycle. With a strong passion for learning and a hunger to innovate, he continually embraces new technologies and challenges himself to build solutions that make a meaningful impact.
As the field of AI/ML started gaining momentum, he found himself naturally drawn to its potential. His first hands-on experience came at NIELIT as an academic intern, where he gained foundational knowledge in AI and machine learning and built a digit recognition system. Building upon this, he conducted a comparative study of deep learning models for skin cancer classification using the HAM10000 dataset.
His interests later expanded into the Internet of Things (IoT), leading to an internship at CubeTen Technologies. There, he helped develop a MERN-stack web application and engineered an IoT-based smart irrigation system using dual ESP8266 modules. This project featured real-time sensing and remote accessibility for smarter, more efficient agricultural practices.
Back in college, he continued pushing boundaries with a deep learning project focused on healthcare: building a hybrid model to classify the severity of knee osteoarthritis from X-ray images, further showcasing his growing expertise in AI-driven medical imaging.
Now he is currently learning JAVA and practicing DSA