Kavinda Athapaththu

Jack of all trades, master of none!

Email: 2015is007@stu.ucsc.cmb.ac.lk
Phone: 071 800 3786
Course: IS

Interests:Reading, Chess, Cyber Security, Machine Learninng

Project Experience

Color Match
An Android color matching game to test your reflexes.

Block Mail Track
A Firefox extenstion to block mail tracking.

Implementing a web portal to facilitate users in learning and practicing soma cube in a virtual classroom environment.

Easy Pay
Implementing a web-based teacher payroll system

ReviewYourHotel (Hotel Reviewing System)
Hotel reviwing sytem to help tourists and travelers

Spectra Vehicle Management System
Implementing a web application to keep track of fuel consumption and millage of vehicles.

Work Experience

Research Assistant Intern
Modeling and Simulation Research Lab – University of Colombo School of Computing

Freelancing Web Developer
• Portfolio www.ksoftlabs.lk

2016 – PRESENT
• Blog www.ksoftlabs.com
• Websites Developed www.ieee.lk, www.jumbonet.lk , www.twelveseeds.com , www.employmentforelders.lk , www.randoms.lk
• Maintaining websites www.humanitariansrilanka.org , www.humanitariancentresrilanka.org
• Web Dev Team member of www.portrayal.ieee.lk
• Maintaining www.careers.ucsc.lk

Achievements | Awards

•Team leader of TeamBrainiancs for IEEE Xtreme 10 (Island Rank 70)

Final Year Project

Forecasting Better Prices for Trip Packages based on Historical Sales Data and Related Factors( In the context of Europe Railway Tourism )

• This study is related to forecasting price optimization using the sales patterns in past decade for the rail based tourism in Europe with the collaboration of selected external data such as weather, seasons and holidays. Currently, the sourced company using their past experience to determine the prices for the trip packages according to the seasons and they have understood that the arrival of the tourists can be varied due to the above mentioned external factors. The final objective is to provide a model using the sales patterns correlated with the external factors to forecast the prices to make future decisions.