logeesan-kj-keesan

Logeesan Jegatheswaran

Enthusiastic undergraduate who is curious to learn new technologies and good team player with strong communication skills. Hard working and responsible person.


Email: kjkeesan@gmail.com
Phone: 0778791127
Course: IS

Interests:Big Data, Data Science, Information Retrieval

Technical Skills: Java/EE, Spring Boot, Spring MVC, Hibernate, Spring JPA, Apache Kafka, MySQL, REST API, Google Map API, Python, PHP,AJAX,Linux

Project Experience

Disconnection Monitoring System(individual internship project)
Assigning and removing labors for disconnection and reconnection of electricity in regions
Technologies: Spring Boot, Spring JPA, AJAX,Google Map API, REST API,Maven,Stored procedures Bootstrap,IBM Informix, Thymeleaf
SponsorBid
Bidding sponsors by the companies to get the ownership of sponsors for the events.
Technologies: Java EE, Spring MVC, Hibernate, JSP, MySQL
Classification of Dogs and Cats
Using Kaggle datasets to distinguish Dogs and Cats using CNN algorithm.
Technologies: keras, Python
E-Procurement (2nd Year Group Project)
E-Procurement system for Ministry of Digital Telecommunication and Infrastructure
Technologies: Bootstrap, PHP, JSON, AJAX, Chart js, MySQL

Work Experience

• Software Engineering Trainee | Ceylon Electricity Board (August 2019-January 2019)

Achievements | Awards

• Gold medalist in Sri Lanka University Games 100*4 Track & Field(2018) with PB: 11.5 sec
• University of Colombo Colors Award holder (2016,2017,2018)
• Consecutive Bronze medalists in Sri Lanka University Games for 100*4 Track and Field (2016,2017)
• Student Representative (2016/2017) of University of Colombo School of Computing
• Senior Prefect(2013/2014) Colombo Hindu College

Final Year Project

Summarization of Stock News Article Using Graph Based Approach (Feb 2019 – Present)

• Financial news articles can be used to identify the stock movements of a company. It is read by many stock traders to carry out their stock trading activities on the next day. Our research focuses on identifying how far summarized article can help the stock traders to do stock markets effectively and efficiently. Carried out using extractive and graph based summarization approach.
Technologies: python(NLTK, NetworkX) , Gephi(Graph Visualization)