2015se121_sandali-sandali-samarawickrama

Sandali Samarawickrama

Self-motivated, Dynamic and Enthusiastic individual who is willing to accept challenges in the field of Computer Science and Software Development. Fast learner and a good team player.


Email: samarawickramasandali@gmail.com   
Phone: 0717265720
Course: SE

Interests:Web Development, Machine Learning, Swimming, Movies

Technical Skills: Java, C++, Python, JavaScript, TypeScript, Node js, MySQL, MongoDB, Ionic, Android, Docker, Git, AWS

Project Experience

StudentMate
An online web portal for the students of UOC.It is to help the students with their day today problems .
HTML, CSS, Javascript, php Codeignitor
SchoolDrop
An app that connects parents and school van drivers. Parents can register their children, find them a school van in in-app marketplace, set schedule, school van location tracking, alerting when the van is near to pick-up or drop child etc.
Ionic 3, AWS EC2, AWS RDS, Firebase, OneSignal, Barcode reading
Snake and Ladder
A game that tweaks the traditional snake and ladder concept to learn account and accountancy concepts in a new and exciting way.
Angular, HTML Canvas, Firebase
Keshi Foods
Keshi foods is a small sector sweet company situated in Nittabuwa.They own 15 major products.This is a web portal for handling sales, stocks and employee management in the factory.
Bootstrap, php-Codeignitor
Hospital Management System
Developed for employee management and patient management of a Hospital.
Java, mysql

Work Experience

Software Engineer – Intern at IFS R&D International

Achievements | Awards

• Winners – SHECODERess 1.0 2018 – held by WIE branch Uwa Wellassa University

Final Year Project

Extensible Audio Streaming mobile application

• Android mobile application for Sri Lankan music listening community as well as Sri Lankan artists where artists can publish their songs and get an income out of the system. Application includes audio streaming, user streaming analytics , auto suggestion and dynamic recommendation of songs for user preferences. Research attempt is to optimize suggesting songs and creating dynamic playlists according to user preference and listening history.
Android, Node, AWS, Python