chathura-ranaweera

Chathura Ranaweera

I’m a self-driven, versatile individual with hard working and fast learning abilities. My aim is to achieve excellency in IT industry as a dedicated, dynamic & adaptable role player whilst enhancing my knowledge and abilities.


Email: cham92ran@gmail.com
Course: IS

Interests: Business Analysis, UX/UI Design, IoT, ERP, Project Management, R&D

Technical Skills: UML, Bizagi Process Modeling, Python, PHP, JavaScript, Ajax, jQuery, HTML/CSS, MySQL, Bootstrap, Joomla, MATLAB, Machine learning, Image processing

Project Experience

Sales & Stock Management System : A web based inventory management and online shopping portal for H&L Electronics (Pvt) Ltd.

Sonit-Taxi Locator : An automated taxi tracking system with a web portal and Android application deployed for Sonit Taxi
service provider to achieve maximum utilization of taxies, resources and efficiency in all operations.

Multi-Channel Internet Payment Interface : An integrated payment gateway which facilitates third-party payment processing services available for the merchants to enable online payments on their websites.

Work Experience

IT Systems Development Department of Sampath Bank PLC- Trainee Business Analyst (06 months Internship).
Worked as part of an agile team where I have committed myself for handling client meetings, requirements engineering, design & documentation, and functional testing & verification of the solution.

Achievements | Awards

• Degree in Bachelor of Information Technology (BIT) External- UCSC (2016)
• Diploma in Animations & Graphic Designing- Distinction Pass- Esoft Metro Campus Colombo (2014)
• Treasurer of Esoft Colombo Student Union (2012-2013)
• 1st Runners-Up at all Island Quiz Competition Organized by D.S.Senanayake College (2011)
• Best Performance- Nalanda College Annual Prize Giving (2007-2009)

Final Year Project

Artificial Neural Network Application in Classifying the Left Ventricular Function of the Human Heart Using Echocardiography

This research studies on fast and accurate interpretation of heart condition for the decision making process of acute care physicians in Emergency medical settings. The purpose of this research is to find a methodology to automatically diagnose the heart condition by applying image processing and machine learning algorithms for the echocardiography images to save lives of patients in critical condition.