A developer who thinks in the consumer’s mindset and wonder how things can be done in a better way to improve everyone’s lives using technology. Collaborating with the team members while being kind, peaceful, polite, and appreciating honesty & punctuality to come up with the best solutions and being a fast learning knowledge seeker who is willing to teach others for the betterment of everyone is how I look at myself.
Interests:Artificial Intelligence and Machine Learning, Data Analytics, Web and Mobile App development, SEO, Architectural design and development of IoT Applications, Blockchain and Cryptography
Technical Skills: Python, PHP: Laravel & CodeIgniter, Java SE and Jetty, C# .NET and ASP .NET core MVC, NodeJS and Express JS, AngularJS & jQuery, Material Design Bootstrap, Ionic, MongoDB, SQL, Shell Scripting, C/C++, Arduino, PIC and Raspberry PI.
• Dimento | 2017
A 3D modelling marketplace with 360⁰ – preview for 3D models in the web browser.
• Event Registration Websites | 2016 – 2018
Hackathons and Student Activity event registration websites for CloudHack by UCSC IEEE student branch, and iHack 2.0 & ICS Meetup by ISACA student branch of UCSC.
• Mangomark | 2016 – 2018
A crowdsourced knowledge and Experience sharing platform.
• ImSafe | 2017
An Android application which acts as a panic button in an emergency.
• Medecs | 2018 – 2019
A medical center management system.
• Research Intern – UCSC external project for the Outstanding Song Creators Association | September 2018 – February 2019
• Outsourced Developer – Ayra Group PTY Ltd. | October 2018 – August 2019
• Trainee Software Developer – Sydpro (pvt) Ltd. | January 2015 – August 2015
Achievements | Awards
• Bronze Award at the Best Software Competition 2017 in the UCSC
• Best Academic Student of the year (Common Subject Stream) at D. S. Senanayake College, Colombo 07 in 2014
• Winner at the LetMeHack 2018 inter-university hackathon
• Finalist at the CodeFest 2017 inter-university hackathon
• IEEE Xtreme 2017 | World Rank: 310/3342 |Sri Lankan Rank: 22/303
• Secretary of the Computer Science Society of University of Colombo (CompSoc) | 2018 – 2019
Final Year Project
A Robust Approach to Predict the Popularity of Songs by Identifying Appropriate Properties
• This research focus on using machine learning and data analytics techniques to identify the impactful properties such as the audio frequencies, acoustic features and other song related data, which could be used to predict the popularity of songs at the time of release.