Portfolio
Full-stack developer
Mechatronics Engineering student and Tech Lead with a proven track record in developing AI-driven systems, commercial SaaS products, and scalable IoT architectures. Experienced in managing cross-functional teams and complex digital deployments, from algorithmic trading systems to large-scale cultural events. Passionate about bridging advanced engineering with creative problem-solving, hardware-software integration, and user-centric design to create high-impact solutions.
Selected work
Teach foundational programming concepts and software development to elementary through high school students using Scratch, MIT App Inventor, and Python. Facilitate interactive project-based learning sessions where students build functional games, mobile applications, and Python scripts.
Instructed comprehensive courses on Robotics Systems and IoT. Evaluating technical projects for strict adherence to hardware wiring guidelines and coding standards
Developing purely in Java and compiling into an Android APK, I engineered the robot's autonomous execution sequence. The core algorithmic challenge involved computing spatial navigation to capture target QR codes, analyzing the data, and calculating the exact 3D trajectory to fire a laser at designated coordinates. This required highly optimized image processing and movement logic to maximize the score while preventing resource exhaustion on the Astrobee's hardware before the time limit expired.
Anticipating a massive turnout of Gen Z and local communities at Lokananta Bloc, I took charge as the Tech Lead to engineer an independent, high-speed digital ticketing platform—making ticket sales seamless and completely eliminating the need for third-party services. To ensure attendee security and prevent gate bottlenecks, I built a custom gate entry system with real-time QR validation, maintaining zero server downtime during peak loads.
An artificial intelligence-based forex trading system engineered to analyze market trends and predict real-time price movements. The architecture deploys machine learning algorithms to process historical data and technical indicators. This computational approach systematically optimizes automated trade execution strategies.
The short-form content phenomenon moves at lightning speed, but complex editing workflows hold creators back. AWSM AI Clipper is an innovative desktop application that turns raw video links into viral, ready-to-use and ready to post and giving full control back to the user without the monthly subscriptions.
Oxygenix provides early detection for Chronic Obstructive Pulmonary Disease (COPD) risks. The system utilizes machine learning algorithms trained on pulmonary health parameters. It executes fast and accurate risk analyses. This computational tool directly assists medical professionals and users in preventive health monitoring.
Dermascan engineers an automated diagnostic tool for skin disease classification. The system implements Convolutional Neural Networks (CNN) to process and analyze dermatological images. The model extracts structural features from clinical photographs to predict specific skin conditions accurately. This computational framework accelerates preliminary diagnoses and supports clinical decision-making.