Skip to main content

Data Science and Artificial Intelligence (DSAI)

Background of the Group


Artificial Intelligence (AI) and Data Science (DS) are the emergent fields of activity with the most important needs within the digital economy in the coming years. This need is mainly due to the increasing capacities in data acquisition and processing. AI & DS has the potential to transform how we live, work, learn, discover, and communicate. AI & DS based researches can further address our national priorities, including improved educational opportunities and quality of life, and enhanced national security.

DSAI Research Group at the Faculty of Computing research in many areas of Artificial Intelligence and Data Science to serve as a hub for promoting large and medium scale research, in collaboration with eminent and up-and-coming researchers in AI, Data Science and related disciplines and Industries.


Members of the Artificial Intelligence and Data Science Research Group

Team Leader


  • Dr. LS Lekamge- Senior Lecturer Gr. II in Computer Science / Faculty of Computing

  • Dr. UAP Ishanka - Senior Lecturer Gr. II in Computer Science / Faculty of Computing

  • Dr. KPN Jayasena- Senior Lecturer Gr. II in Computer Science / Faculty of Computing

  • Mr. RL Dangalla - Senior Lecturer Gr. II in Computer Science / Faculty of Computing

  • Mr. GACA Herath - Lecturer (Prob.) in Information Systems / Faculty of Computing

  • Mr. K Banujan - Lecturer (Prob.) in Information Systems / Faculty of Computing


Areas of Focus

Members of the group have active interests in: models of intelligent interaction, multi-agent systems, natural language understanding, computational vision, robotics, machine learning (ML), and neural networks, AI and ML applications for cybersecurity, AI and ML applications for gaming, AI and ML applications integrated with cloud computing,  intelligent agents, intelligent  systems, robotics, adaptive and intelligent learning environments, natural language processing, multimedia content data mining, databases, statistical analysis, optimization.


  • To use AI to solve large and complex problem sets that span multiple services; then, ensure the Services and Components have real-time access to ever-improving libraries of data sets and tools.

  • To create impact of AI on the social development of the country can intensify with following advancements in increased access to quality health facilities and providing real-time advisory to address unpredictable factors towards increasing productivity.

  • To support diagnosis in medical imaging, develop models on computer-aided diagnosis in medical imaging based on machine learning.

  • To use AI and data science to create a new field that combines simulation and AI.


Research Projects and Directions
  • The projects on the mathematical tools and theory of artificial intelligence, especially of machine and deep learning, neural network to bridge the gap between mathematical theory and machine learning practice by exploiting newly discovered deep connections between fundamental results related to the study of large networks and the more applied domain of machine learning.
  • The projects on development of super intelligent systems that are reliably aligned with human interests.

  • Pilot interdisciplinary projects that may directly demonstrate the practical applicability of the theoretical research.

  • Develop shared public datasets and environments for AI training and testing.

  • Address the ethical, legal, and societal implications of AI and Data Science based developments.


Full papers published in indexed journals by group members
  • B. T. G. S. Kumara, Incheon Paik, Yuichi Yaguchi , “Context-Aware Web Service Clustering and Visualization” International Journal of Web Services Research (JWSR), Vol. 17, No. 4, 2020.

  • Mohamed Abd Elaziz, Shengwu Xiong, K. P. N. Jayasena, Lin Li, Multiobjective big data optimization based on a hybrid salp swarm algorithm and differential evolution, Applied Mathematical Modelling, 7 th November 2019 (SCI Index)

  • Mohamed Abd Elaziz, Shengwu Xiong, K. P. N. Jayasena, Lin Li, Task scheduling in cloud computing based on hybrid moth search algorithm and differential evolution, Knowledge-Based Systems, 31st January 2019 (SCI Index)

  • Rupasingha A. H. M. Rupasingha, Incheon Paik, and B. T. G. S. Kumara, Specificity-Aware Ontology Generation for Improving Web Service Clustering, IEICE Transactions on Information & Systems, Vol.E101-D,No.8,pp.-,Aug. 2018. 

  • Piumi Ishanka UA and Takashi Yukawa, “ An Analysis of Emotion and user Behavior in Context-Aware Travel Recommendation Systems using Pre-Filtering and Tensor Factorization Techniques”, Global Journal of Computer Science and Technology: D Neural & Artificial Intelligence, 2018

  • K. P. N. Jayasena, Lin Li, Qing Xie:Multi-modal Multimedia Big Data Analyzing Architecture and Resource Allocation on Cloud Platform. Neurocomputing 253: 135-143 (2017)  (SCI Index)

  • Sugeeswari Lekamge, Masaki Nakachi, Shu Sato, Kanetoshi Ito, and Shusaku Nomura, “Alleviation of the Acute Stress Response following Mild Orange Essential Oil Administration,” IEEJ Transactions on Electrical and Electronic Engineering, Vol.12, No.S1, pp.158-163, 05.06.2017.

  • K. R. C. Koswatte, I. Paik, W. Park and B. T. G. S. Kumara, “Innovative Product Design using Metaontology with Semantic TRIZ”, International Journal of Information Retrieval Research (IJIRR), Vol. 5, No. 2, pp. 43-65, 2015.

  • B. T. G. S. Kumara, I. Paik, W. Chen and K. Ryu, “Web Service Clustering using a Hybrid Term-Similarity Measure with Ontology Learning,” International Journal of Web Services Research (JWSR), Vol. 11, No. 2, pp. 24 - 45, 2014.


Research Grants/Research Awards obtained by members
  • "InforBhoomi: VGIS-Based Informed Decision Making for Strengthened Local Land Governance", Acceleration Higher Education Expansion ab Development (AHEAD)/ RIC Grant -  (B. T. G. S. Kumara , Deputy Coordinator )

  • "An Online Platform for Predicting Crops Based on Environmental Variables.", Sabaragamuwa University Grant – (B. T. G. S. Kumara, Member)

Submitted grants
  • Pervasive mental health monitoring system for young adults Indo - indo-sri lanka joint research programme (B. T. G. S. Kumara, K.P.N Jayasena)