Hirunika Karunathilaka

A passionate, dedicated and fast self-learner seeking a software engineering position to contribute, coping with new technologies.

Email: hirukarunathilaka@gmail.com  
Phone: 0710629149
Course: CS

Interests:Speech recognition, Web design and development, Volunteering, Blogging, Badminton

Technical Skills: JavaSE, JavaEE, Spring Boot, Spring, Javascript, ReactJS, NodeJS, MySQL, Kaldi

Project Experience

mSMS Premier REST API (Internship project) – JavaEE, Spring Boot & Services, MySQL, Postman
Implementation of secure RESTful web services with new features for the existing SOAP SMS application.
Call blocking app (Internship project) – JSF, Primefaces, MySQL
User interface and backend implementation for managing whitelist numbers of the outgoing call section.
Centralized web management system – PHP, CodeIgniter, HTML, Javascript, CSS, AJAX
A web based solution for a company to manage sales collection and vehicle maintenance of its four outlets.
Vid-Talk – ReactJS, NodeJS, ExpressJS, MongoDB, WebRTC
A video conferencing platform using WebRTC (OpenVidu)
IEEE-UCSC official website – NodeJS, ExpressJS, MySQL
The website was developed for the IEEE Region 10 student branch website contest.
Lab reservation system – Angular, NodeJS, MongoDB, ExpressJS
A web application for reserving UCSC labs.
Sinhala Scrabble (Game) – Unity Game Engine,C#
A word puzzle game for helping the kids to learn words in the Sinhala language through an interactive and interesting way.
Hospital management system – Java Swing Application, NetBeans, MySQL
A desktop application that manages patients’,doctors’ and wards’ Information with features – reserving doctors and wards.

Work Experience

• Software Engineer Intern at Mobitel (Pvt) Ltd (2018 Sept – 2019 Feb)
• Student Mentor – Help to code ICTA school reach program

Achievements | Awards

• Medhack 2017 – Top 5 products
• Dialog Gaming Hackathon 2017 – Finalists
• Codezilla 2018 – Finalists
• Tadhack 2017 – Finalists
• Google Mobile Sites Certification [2018]

Final Year Project

Low-resource Sinhala speech recognition using deep learning

The main aim is to develop a robust continuous speech recognizer for the Sinhala language by experimenting deep learning based models. Use strategies to effectively use the available limited data. Fills the research gap of an open domain continuous Sinhala speech recognizer using deep learning techniques.