nishani-fernando

Nishani Fernando

I'm a cheerful, courageous individual who is always willing to learn, experiment & embrace challenges. Interested in Science & Tecnologies.


E-mail: nlfernando11@gmail.com | phone: +94712082167 | Course: SE

I am a confident, reliable and self-driven individual who uses her initiative to meet the higher level standards. Also an enthusiastic, energetic quick learner and experimenter as well as a well-presented team player who can work under pressure and always willing to listen and take advice and comments on-board.

Interests: Mathematics, Computer Science, Music and Astronomy

Technical Skills: Java, C# .NET, Python, C, PHP, JavaScript, AJAX, JQuery, KnockoutJS, HTML5, CSS3, AngularJS, JUnit, MVC, Agile SCRUM, SQL Server, NoSQL MongoDB, Web API, GitHub, TFS, DevOps, CI/CD, SignalR, KendoUI

Project Experience

Orca – Dolphin 365 Contract Management
Automate contract management process using office365 technologies, MVC, EntityFramework6, C#, JQuery

Eye Clinic Management System
Web application to automate clinic data processing at an eye clinic: PHP, HTML5, CSS3, JavaScript, JQuery, MYSQL

Suriya Holiday Inn Hotel Reservation System
Web application to promote hotel services and manage online bookings: WordPress, Wow Slider, Flip Gorilla and security plugins

Work Experience

Navantis IT: Trainee Software Engineer(C#.NET), worked in the product Dolphin365 Contract Manager
Bank of Ceylon: Temporary Clerk (School leaver basis)

Achievements | Awards

• Nominated for the award ‘Best Performance in Industrial Placement’ at Navantis IT in 2015
• IEEE Extreme 8.0 and 9.0 : Certificates of participation
• Award for securing Gampaha district rank 66 in GCE A/L 2011
• IEEE SGW Congress 2013 – IEEE Sri Lanka Section: Certificate of participation
• Interschool athletic meet won places in several events
• Champion of Negombo Zonal level commerce quiz in 2008

Final Year Project

Content-based enhancement for Apache Kafka Framework

Apache Kafka is a distributed messaging system with a high throughput and a low latency. Its current topic-based subscription model limits its ability to deliver more expressive information to consumers based on their interests. Our research oriented technical approach is to attribute the content-based subscription model to existing Apache Kafka with the application of JMS Selector concept. In this approach the consumer is allowed to specify his or her interests using consumer API. The interests are captured with MVFLEX expression language (MVEL). The producer produces messages and information about the message content is attached with it. Those messages are transmitted to a cluster of Kafka brokers and are filtered with respect to the interests of each consumer using very efficient matching algorithm. To enable dynamic subscription for consumers in real-time, reactive paradigm is used with Scala. Message transmission happens as streams of bytes, hence memory efficient google flat buffers are used to serialize message streams.

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