Nisansa Dilushan de Silva

I am a lecturer at the Department of Computer Science & Engineering, University of Moratuwa, Sri Lanka. I obtained my Ph.D (2020, advisor: Dejing Dou) and MS (2016) degrees in Computer and Information Science from University of Oregon, USA and my BSc (Hons) in Computer Science & Engineering (2011) degree from University of Moratuwa. I joined University of Moratuwa as a lecturer in 2011. From 2013 to 2014, I worked as a researcher at LIRNEasia. In 2018, I worked as a Givens Associate at Argonne National Laboratory, USA. I have over 80 peer reviewed publications in the field of computer science, mostly under the subfields of Natural Language Processing and Artificial Intelligence, earning more than 1400 citations. I am also an associate member of the IESL.

Professional Experience

  • Present 2020

    Senior Lecturer

    Department of Computer science & Engineering, University of Moratuwa,
    Sri Lanka

  • 2021 2020

    Research Fellow

    LIRNEasia,
    Sri Lanka

  • 2020 2014

    Graduate Research/Teaching Fellow

    University of Oregon, Department of Computer and Information Science,
    USA.

  • 2018 2018

    Givens Associate

    Argonne National Laboratory,
    USA.

  • 2020 2011

    Lecturer

    Department of Computer science & Engineering, University of Moratuwa,
    Sri Lanka

  • 2014 2013

    Researcher

    LIRNEasia,
    Sri Lanka

  • 2014 2013

    Visiting Lecturer

    Northshore College of Business and Technology,
    Sri Lanka

Education

  • Ph.D. 2020

    Ph.D. in Computer & Information Science

    University of Oregon, USA

  • MS 2016

    MS in Computer & Information Science

    University of Oregon, USA

  • BSc2011

    B.Sc Engineering (Hons)in Computer Science & Engineering

    University of Moratuwa, Sri Lanka

Featured Research

Automating the Composition and Scheduling Process for Synoptic Assessment Panels


N. H. N. D. de Silva, S. M. Weerawarana, and A. S. Perera

9th SDC-SLAIHEE Higher Education Conference 2013, 06 2013,

The Bachelor of Engineering (Honours) program of the Department of Computer Science and Engineering at the University of Moratuwa has a compulsory software engineering project course in the 5th semester. This course has been designed to foster creativity and software engineering rigor. Since the design of this course (CS3202) straddles several program ILOs at a 5th semester level, along with a strong emphasis on creativity, a synoptic assessment approach was selected in the course evaluation framework. This involved constituting expert evaluation panels. Previously, compilation and scheduling of evaluator panels aligned with the heterogeneous technology profiles of the student projects was done manually. However, it was a highly tedious and time consuming task which was further complicated due to the limited number of evaluators and conflicting time constraints. The objective of current research was to evaluate the efficiency of automating the process of constituting synoptic assessment panels to evaluate the above mentioned student projects (n=101). An action research methodology was followed in the study. In the research 'planning' phase, data on student project technology profiles, competency and availability of the evaluators, and course dependent restrictions was gathered. In the research 'action' phase, an algorithm was devised with the following primary objective: "Each student will be assigned a 'best-fit' panel of evaluators considering the technologies used in the student's project." The research 'observation phase' showed that 120 of the total 141 feasible student project profiles were successfully matched by the algorithm to the areas of technology expertise of the evaluators, resulting in an 85.12\% success rate. Thus it can be concluded that this approach is a very important improvement over the manual assignment of panels. The future work is to implement an online application. and our recommendation is that other educators could use this application for a similar purpose.