Researcher, University of Southern Queensland, AustraliaĀ š
Lakmini Mudiyanselage is a dedicated researcher and academic with a passion for data science and artificial intelligence, specializing in hydrological forecasting and environmental applications. Based in Toowoomba, Queensland, she leverages her expertise to develop predictive models that address critical climate challenges in Australia, particularly in drought-prone regions. With a Ph.D. in Artificial Intelligence and a background in mathematics, Lakmini is committed to advancing scientific research through innovative data-driven methodologies and deep learning techniques.
Profile
Scopus
Education š
Lakmini Mudiyanselage has a solid academic foundation marked by her advanced studies in artificial intelligence and mathematics. She earned her Doctor of Philosophy in Artificial Intelligence from the University of Southern Queensland in 2023, where she focused on cutting-edge AI applications to solve environmental challenges. Prior to this, she completed a Master of Philosophy in Mathematics in 2014 and a Bachelor of Science in Mathematics in 2008, both from the University of Kelaniya. This extensive background in mathematics and AI equips Lakmini with the analytical and computational skills needed to contribute significantly to data science and environmental studies, enabling her to develop sophisticated predictive models and insights that address critical climate issues.
Experience š§āš«
Researcher | UniSQ Advanced Data Analytic Lab (2020 – Present)
Lakmini leads efforts in predictive model development for hydrological parameters, working with extensive climate datasets to advance environmental forecasting. Her work has attracted significant funding and collaborative support, demonstrating her impact on hydrological research.
Senior Lecturer in Mathematical Sciences | Wayamba University of Sri Lanka (2010 – 2020)
In her decade-long academic career, Lakmini contributed to curriculum development and student mentorship. She also supervised student research and served as Acting Head of the Department, guiding students in mathematical modeling and AI-driven solutions.
Research Interest š
Lakminiās research focuses on leveraging artificial intelligence for environmental forecasting, with special attention to climate and hydrological data modeling. Her projects utilize hybrid machine learning models, such as Long Short-Term Memory networks, to enhance predictions related to evaporation, soil moisture, and evapotranspiration in regions affected by climate variability.
Awards š
Lakmini Mudiyanselage has been honored with prestigious awards that reflect her academic excellence and research contributions. In 2023, she received the Award of Excellence in Doctoral Research from the University of Southern Queensland, recognizing her achievement of the highest possible result in her doctoral research examination. Earlier, in 2008, she was awarded the Physical Science Award in Mathematics by the Sri Lanka Association for the Advancement of Science for her groundbreaking work on confluent hypergeometric differential equations. These accolades underscore her dedication to advancing mathematical and AI-driven research, particularly in fields with impactful applications.
Publications š
āDevelopment and Evaluation of Hybrid Deep Learning Long Short-Term Memory Network Model for Pan Evaporation Estimationā ā Journal of Hydrology, 2022
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Cited by multiple research articles examining predictive environmental modeling.
āDeep Multi-Stage Reference Evapotranspiration Forecasting Model: Multivariate Empirical Mode Decomposition Integrated with Boruta-Random Forest Algorithmā ā IEEE Access, 2021
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Referenced in studies focused on data-driven environmental predictions.
āForecasting Multi-Step Soil Moisture with Three-Phase Hybrid Wavelet-Least Absolute Shrinkage Selection Operator-Long Short-Term Memory Network (moDWT-Lasso-LSTM) Modelā ā MDPI Water, 2023
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Influential in soil moisture forecasting literature and widely cited in AI-based hydrological research.
Conclusion
Lakmini Mudiyanselage is an exceptional candidate for the Best Researcher Award. Her groundbreaking work in artificial intelligence and environmental data science addresses pressing global challenges, and her commitment to academic mentorship further underscores her dedication to scientific advancement and community service. Her accomplishments align well with the awardās objectives, making her highly deserving of this recognition.