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OWSD Early Career Fellowship 2023

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Dr. Induni W. Siriwardane has been granted a OWSD Early Career Fellowship 2023, which is offered by the Organization for Women in Science for the Developing World (OWSD) together with the United Nations Educational, Scientific and Cultural Organization (UNESCO). She will receive up to USD 50,000 to lead research projects and establish research at the Center for Advanced Materials and Smart Manufacturing (CAMSM) in the Faculty of Computing and Technology, UOK, and to maintain an international standard of research and attract international collaborators. Funding for the fellowships is generously provided by Canada's International Development Research Centre (IDRC). Her research project will develop value-added nutraceutical products from Sri Lankan elderberry (Sambucus nigra) using nano-encapsulation techniques. The project will have several economic and social benefits to Sri Lanka, and the developed methodology and infrastructure will serve as a platform to implement similar techniques for other active ingredients from Sri Lankan origin, encouraging more competitive food and nutraceutical products to international markets. During the 3-year fellowship, she will receive specific training to build on her leadership and management skills, to develop connections with a variety of public and private sector partners, to improve the communication and outreach skills and to attract new collaborators and potential funders to ensure the sustainability of the research project.

Insight International Research Conference 2024 (IIRC2024)

26 th  on February 2024 Insight Institute of Management and Technology , Sri Lanka

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Supervised Machine Learning Model for Stock Exchange Prediction

S.Dinushan, student bearing number CS/2017/006, won the best Presenter award on the Information Technology track of the Insight International Research Conference 2024 (IIRC2024), organised by the Insight Institute of Management and Technology on 21st January 2024. The research focused on predicting the next month’s Sri Lankan stock market index rates (ASPI and S&P20) more accurately by analyzing influential factors and using machine learning algorithms. The objectives were to identify the influential variables on ASPI and S&P 20 separately, build ML models utilizing them, and determine the best-performing model. This research holds significant potential for improving stock market prediction in Sri Lanka, which can have far-reaching implications for investors, traders, and organizations alike. Moreover, this research offers a promising avenue for more accurate market forecasting, ultimately aiding decision-making processes in the financial sector and beyond. Dr. (Mrs.) M. Carmel Wijegunasekara's supervision likely played a crucial role in successfully guiding the research.

The conference was held on a virtual platform with the participation of an international research and academic community from India, Malaysia, Bangladesh, Brunei, Australia, the United Kingdom, the United States and Sri Lanka. High-calibre research papers were submitted in six themes, namely. Information Technology, Engineering Technology, Technological Interventions and applications in Health, Information Technology and Remote sensing, Technological Interventions and applications in the Environment and Technological Interventions and applications in the Agriculture and Food Industry.

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Faculty of Computing and Technology,
University Drive,
Bulugaha Junction, 

Kelaniya,
Colombo,

Sri Lanka

 

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2024-04-14 09:18
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Last Update on 5/03/2024

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