Transforming Data into Actionable Insights
Final-year Data Science undergraduate passionate about leveraging AI and machine learning to solve real-world problems. Skilled in Python, data visualization, and creating innovative solutions.
Final-year Data Science undergraduate passionate about leveraging AI and machine learning to solve real-world problems. Skilled in Python, data visualization, and creating innovative solutions.
Get to know my background, skills, and what drives me in the field of data science
I'm a final-year Data Science undergraduate passionate about transforming raw data into actionable insights. With a strong foundation in Python, Machine Learning, and Data Visualization, I'm dedicated to solving real-world problems through innovative data-driven solutions.
My journey in data science began with a fascination for patterns and problem-solving. I continuously learn to stay updated with industry trends and technologies, ensuring I can deliver cutting-edge solutions.
Projects
AI Models
Volunteering Roles
My professional background and qualifications
Final year undergraduate specializing in AI and machine learning with a focus on real-world applications. Coursework includes advanced statistics, predictive modeling, and big data technologies.
Physical Science Stream with top results in Mathematics, Physics, and Chemistry. Active participant in science fairs and programming competitions.
Completed hands-on training in ICT infrastructure, covering hardware configuration, network setup, operating systems, and technical troubleshooting, in line with industry standards.
Completed “Programming for Everybody (Python)” on Coursera, gaining foundational skills in Python syntax, data structures, control flow, and problem-solving through practical coding exercises.
Completed a Web Development Certificate Course at SLTC, covering HTML, CSS, JavaScript, and responsive design, with practical projects to build functional and user-friendly websites.
Explore my data science projects that solve real-world problems
A smart system using IoT and AI to detect and analyze crimes in crowded places like airports and bus stations. Watches live video feeds to spot crimes and sends alerts to authorities.
A Flask-based web application that analyzes user comments to classify sentiments as positive or negative using machine learning models and NLP techniques.
A machine learning-based system designed to detect and classify menstrual abnormalities from medical data, assisting healthcare professionals in early diagnosis.
The Student Performance Prediction project aims to predict how students will perform in their studies using data like attendance, test scores, and assignments. By analyzing this data with machine learning models such as Decision Tree, Logistic Regression, and Random Forest, the system can identify students who may need extra help. The best model is chosen based on accuracy and other metrics, helping teachers make better decisions to support student success.
This is an end-to-end data science project demonstrating the full lifecycle of a machine learning application. It involves collecting and preprocessing a large-scale news dataset, training an LSTM model to classify articles as real or fake, and deploying the model within a user-friendly web interface built with Streamlit. The project highlights skills in natural language processing (NLP), model development, and web application deployment.
The Media Unit Event Management System is a web-based application developed with Streamlit and Supabase to streamline media team operations. It efficiently manages member availability, assigns event coverage, and automates scheduling, ensuring smooth coordination and optimal resource use. The system provides real-time tracking, reduces manual errors, and enhances overall team productivity by offering a centralized platform for planning and monitoring events.
This interactive computer vision project uses Python, OpenCV, and MediaPipe to create a virtual canvas where users can draw in real time using hand gestures detected by a webcam. It features real-time hand tracking, pinch-to-draw gesture control, color selection, thickness adjustment, and switchable backgrounds, making it both fun and educational. The project highlights the use of computer vision, gesture recognition, and real-time video processing to build a creative, touch-free drawing experience.
This is a group project that created an IoT-based Pet Feeder web app with water pump control. Users can set top and bottom water levels, add multiple feeding times, and control the pump manually through a simple web interface. Built with PHP, MySQL, and Tailwind CSS, the project shows database integration, dynamic forms, and real-time device control. It is ready for future IoT hardware integration for automated pet feeding.
SL Chat News is a web application that fetches the latest news from multiple Sri Lankan RSS feeds and displays them in a clean, user-friendly interface. The app also sends real-time updates to Telegram, ensuring you never miss important news. Built with Python, Flask, Feedparser, and Telegram Bot API, it’s perfect for news enthusiasts who want Sri Lanka updates in one place.
Explore the machine learning models I've developed to solve various challenges
Developed a model for detecting crimes in crowds using AI and video surveillance, currently in collaboration phase with the police dashboard. This model uses advanced computer vision techniques to identify suspicious activities in real-time.
Built a classifier to analyze user comments and classify sentiments as positive or negative using machine learning techniques. The model processes natural language to understand context and emotional tone.
Created a machine learning system to detect and classify menstrual abnormalities, assisting healthcare professionals in early diagnosis. The model analyzes patterns in medical data to identify potential health concerns.
Developed a deep learning model to detect and classify diseases in potato leaves from images, helping farmers identify crop issues early. The model uses convolutional neural networks for image classification.
Built a convolutional neural network to classify images of cats and dogs with high accuracy, demonstrating image classification skills. This model was trained on a dataset of 25,000 images and achieves near-human accuracy.
My journey as a compere, presenter, and media volunteer
Presented and conducted interviews for the "Kreeda Visithru" program on Jathika Rupavahini and covered the 48th National Sports Festival. Engaged live audiences and contributed to high-quality sports broadcasting.
Assisted the Health Ministry campaign as a presenter and research team member. Supported community awareness efforts and helped organize events for neurodiversity and autism awareness.
Served as a compere and contributed to event management, media coverage, and promotional activities for student events at Sri Lanka Technology Campus. Managed event hosting and live announcements, ensuring professional delivery and audience engagement.
My expertise in data science and related technologies
Experienced in Python for data analysis, automation, AI, and ML projects.
Skilled in creating visual insights using Matplotlib, Seaborn, and Tableau.
Proficient in writing complex queries and managing relational databases.
Ability to present data insights clearly to technical and non-technical audiences.
My contributions to community and campus organizations
Led over 25 charity projects supporting children, pregnant mothers, and community helpers, making a positive social impact.
Managing media coverage and event promotions to engage the student community.
Managed event hosting and live announcements, ensuring professional delivery and audience engagement.
Active team member promoting teamwork and competitive spirit.
Supported leadership and community service initiatives within the Leo Club.
Enhanced student engagement and membership growth in the IEEE branch.
Have a project in mind or want to discuss opportunities? Let's connect!