A self-motivated person who always works hard in any dynamic environment. A good leader, good team player and a good sportsman.
E-mail: email@example.com | phone: +94752754861 | Course: CS
A Self-driven person who always work hard in any dynamic environment. A fast learner and self-motivated to take any challenge. The Strengths are inbuilt leadership qualities and ability to take responsibilities.
Interests: Deep Neural Networks, Machine Learning, Image Processing, Computer Graphics, Cricket, Athletics, Rugby
Technical Skills: Java, C++, C, Python, SQL, CNN, OpenCV, OpenGL, OGRE 3D, OpenCPN, Android, PHP
Refactor and rewrite of basic functions and implemented a new network module with a middleware architecture to support multiple clients and enhanced the ship rudder meter module to work with new Android versions.
SIYARA Electronic Logbook and Fishery Management Support System
System consists of mobile applications for fishermen’s e-Logbook and Fisheries Inspectors’ inspection process. Developed an Android application for Coast Guard officers to inspect fishermen’s instruments.
Vessel traffic management system which was developed to monitor and manage vessel traffic in ports and congested waterways. Enhanced the maps to achieve a better result.
Research Assistant – Modelling and Simulation Research Group– UCSC – August 2015 – February 2016
Junior Clerk – Inventory Control Department, Singer (Sri Lanka) PLC – May 2012 – March 2013
Secretary – Buddhist Society – University of Colombo – May 2014 – April 2015
IT Project Coordinator – Computer Science Society – University of Colombo – Feb 2015 – To date
Achievements | Awards
• Regional best IEEE student branch website contest 2nd place – 2014
• IEEEXtreme – 2013/2014/2015 Best – Country Rank 19th (2015)
• 6.00.1x: Introduction to Computer Science and Programming Using Python, MITx – completed
• Australian National Chemistry Quiz 2008 – Merit
• Inter-faculty open athletic meet in University of Colombo – 2013 – 200m – Second Place
• Senior Cadet Platoon – Nalanda College – Cadet – 2008 – 2009
Final Year Project
Pre-detection of Alzheimer’s Disease from Neuroimaging Data Using Image Processing and Convolutional Neural Networks.
Early detection of Alzheimer’s disease is seen as important because treatment may be most efficacious if introduced as early as possible. But currently diagnosis is largely based on clinical history and examination supported by neuropsychological evidence of the pattern of cognitive impairment. But this is time consuming and diagnosis accuracy is less. The aim of this project is to overcome the problem of pre-detecting Alzheimer’s disease using image processing techniques, Convolutional Neural Networks and neuroimaging data.