2015is025_eranda-eranda-grero

Eranda Grero

I am an energetic, ambitious person who has developed a mature and responsible approach to take any task that I undertake or situation that I am presented with. As an Undergraduate in Information Systems, I have the potential to work with others to achieve objectives on time and with excellence.


Email: erandagrero@gmail.com
Phone: 0716852981
Course: IS

Interests:Business Analysis, Enterprise Resource Planning, Database Management, Data Analytics, R&D

Technical Skills: SQL, PHP, Python, Angular, Node.js, MongoDB

Project Experience

Forecasting a Better Price for Trip Packages based on Historical Sales Data and Related Factors (In the context of Europe Railway Tourism) [4th Year Research project – 2019]
Constructing a machine learning model for predicting future trip prices based on past sales.
ReviewYourHotel (Hotel Reviewing System) [3rd Year Advanced Web Development Project – 2018]
Developed using Angular, Node.js and MongoDB
Nivahan.lk (Architectural Guide) [2nd Year Group Project – 2017]
Developed front end and back end using PHP, HTML, CSS, Bootstrap, MySQL and JavaScript.
TAVMS Car Sale System [2nd Year Web Development Project 2017]
Developed front end and back end using PHP, HTML, CSS, MySQL and JavaScript.

Work Experience

• Information System Audit and ERP Intern | Sri Lankan Airlines (September 2018 – February 2019)

Achievements | Awards

• Was placed All-Island 2nd in public speaking competition conducted by IEMS
• Participated in IEEEXtreme 10.0 | IEEEXtreme 11.0

Final Year Project

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

• Visit Group (https://www.visitgroup.com/en/) provides a powerful and interconnected e-commerce/travel platform tailored for different segments of the tourism industry, i.e. Tours and Activities, Transport and Activity Packaging, Hotel and Accommodation etc. Currently all pricing strategies are handled manually upon analyzing past data, which is time consuming. The main purpose of our research is to provide better prices for railway trip packages of Flam Railway to Visit Group by extracting hidden sales patterns considering various factors such as season, weather, holidays etc. to maintain a sustainable platform to compete in the competitive sales environment. Our final goal is to propose a machine learning engine that suggest better prices for trip packages of Flam Railway and increase their revenue.