Tharushi Samarajeewa

A versatile and an adaptive team player with a fun and outgoing personality, who is capable of working in dynamic environments to achieve goals in a realistic time frame.

Course: CS

Web designing, Database, Mobile app development, Music (singing and playing guitar)

Technical Skills: 
Java, Python, PHP, HTML, CSS, JavaScript, MySQL, R, Git, Node.JS, AngularJS, MATLAB, machine learning, image processing

Project Experience

Park Here appHTML, CSS, JavaScript, Bootstrap, Cordova, Ionic, NodeJS, ExpressJS, AngularJS, MySQL, REST API
An internal app for car parking lot management in IFS Colombo.

CBRS HTML, PHP, CSS, JavaScript, MySQL, Bootstrap
A web based system for circuit bungalow reservation in National Savings Bank (NSB).

Rural Lanka HTML, PHP, CSS, JavaScript, Bootstrap
A website developed for a local tourism company to provide information to their customers.

Web based system for Indra Auto SparesHTML, PHP, CSS, MySQL, Bootstrap
A Web based system to automate the activities of the above mentioned business company.

Work Experience

  • IFS R&D International (Private) Limited
    Former Trainee Software Engineer (2016 September – 2017 January)

Achievements | Awards

  • University of Colombo School of Computing – Academic GPA – 3.4879
  • IELTS at band score 6.5 (2013)
  • Completed Prathma, Madhyama, Visharad I examinations in stream instrumental (guitar) stream and Prathma examination in vocal stream, held by Bhatkhande Sangit Vidyapith, Lucknow, India
  • Participant of the 6th International Cultural Festival for World Peace organized by City Montessori Inter College Aliganj, Lucknow, India

Final Year Project

Identifying the distribution of the invasive plant, Lantana camara, using aerial images

Lantana camara distribution is a major threat to natural habitats in a number of countries. Identifying the invaded areas is the first step to eradicate the plant. This project proposes a 2-step identification approach: 1) identify possible Lantana camara patches through texture analysis of far aerial images 2) verify the patches by localizing and classifying the Lantana camara flowers through closer images. Machine learning and image processing techniques are used to achieve these tasks.