Namal Rathnayake
Public Library of Science: Cambridge, GB, The University of Tokyo, Kochi Koka Daigaku, University of Salford, Sri Lanka Intitute of Information Technology, University of Wolverhampton
Research areas: Environmental Science · Environmental Engineering · Hydrological Forecasting Using AI · Hydrology and Watershed Management Studies · Smart Agriculture and AI
0000-0002-5235-8552
About
Namal Rathnayake is a passionate machine learning researcher and engineer with more than four years of experience in research, development, and machine learning practices. He currently works as Researcher (Science) / Project Researcher (II) at JAMSTEC (Japan Agency for Marine-Earth Science and Technology) within the WPI-AIMEC program, and previously held a Project Researcher position at The University of Tokyo. His doctoral research was completed at Kochi University of Technology under the guidance of Prof. Yukinobu Hoshino, where he proposed the Cascaded Adaptive Network-based Fuzzy Inference System (Cascaded-ANFIS), achieving up to 99.9 % accuracy in his Ph.D. studies.
Namal holds an M.Sc. in Robotics and Automation from the University of Salford (graduated with highest distinction), with a thesis titled “An Effective and Efficient Approach Towards 3D Reconstruction.” He earned his B.Eng. (Hons.) in Electronics and Telecommunication from the University of Wolverhampton (Second Class Upper Division), focusing on an Auto-Piloting System for a UAV.
Since 2019, Namal has freelanced on Upwork.com, working on Arduino-based projects such as a chatbot, an autonomous car parking system, and developing robotics/programming tutorials for non-technical audiences. He consulted on sensor selection for an organic waste project in Saudi Arabia, contributed to a warp drive science project, managed research data collection and logging, and developed toy applications using various microcontrollers. Namal has delivered lectures on C++ and Python, designed and implemented an automatic parachute deployment system for drones, created PCBs for educational satellites and SMD boards, researched vehicle control and dynamics, and studied hydropower forecasting algorithm development.
In academia, Namal has served as a Visiting Lecturer in the Faculty of Engineering Technology at the Open University of Sri Lanka, teaching AI to bachelor’s students. He also worked as an Assistant Lecturer in the Department of Electrical and Electronics (Faculty of Engineering) at the Sri Lanka Institute of Information Technology, conducting experiments and tutorials on electronic engineering, embedded systems, programming, and robotics, while supervising and mentoring research groups.
Employment
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Public Library of Science: Cambridge, GB Academic Editor2023 - Present
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The University of Tokyo Postdoctoral Researcher2023 - Present
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Sri Lanka Intitute of Information Technology Assistant Lecture2016 - 2020
Education
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Kochi Koka Daigaku Ph.D.2020 - 2023
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University of Salford Master of Science2017 - 2019
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University of Wolverhampton B.Sc. in Electronic Engineering2013 - 2016
Projects & Funding
Projects & funding information is unavailable.
Publications (48)
- Effectiveness of Rolling-Sum Preprocessing in River Mouth Water Depth Prediction Using Machine Learning Save
- Beyond wind speed: Integrating oceanic indices and time-lagged features for superior wind energy prediction Save
- Neural Signatures of Speed and Regular Reading: A Machine Learning and Explainable AI (XAI) Study of Sinhalese and Japanese Save
- AI-Powered Soil Temperature Modeling for Sustainable Agriculture in Arid Regions: A Case Study of Bustan, Uzbekistan Save
- Temporal Morphological Analysis of NK Cells Save
- Global Nowcasting of Coral Bleaching with Bagging Ensembles: A 23-Model Benchmark and Explainability Study Save
- UFR-GAN: A lightweight multi-degradation image restoration model Save
- Machine Learning Approaches for Simulating Temporal Changes in Bed Profiles Around Cylindrical Bridge Pier: A Comparative Analysis Save
- Controlling Heterogeneous Multi-Agent Systems Under Uncertainty Using Fuzzy Inference and Evolutionary Search Save
- Explainable artificial intelligence to estimate the Sri Lankan (Ceylon) Tea crop yield Save
- Efficient Hotspot Detection in Solar Panels via Computer Vision and Machine Learning Save
- Hybridizing Fuzzy Clustering and Ensemble Learning for Accurate River Water Level Prediction Save
- Leveraging level data for accurate downstream flow prediction in the Narmada River Basin with advanced machine learning models Save
- Enhancing Water Level Prediction Using Ensemble Machine Learning Models: A Comparative Analysis Save
- Flow Velocity Analysis of Rivers Using Farneback Optical Flow and STIV Techniques With Drone Data Save
- Analyzing the impact of socioeconomic indicators on gender inequality in Sri Lanka: A machine learning-based approach Save
- Impact of economic indicators on rice production: A machine learning approach in Sri Lanka Save
- AI-driven predictions of geophysical river flows with vegetation Save
- Advancing water quality assessment and prediction using machine learning models, coupled with explainable artificial intelligence (XAI) techniques like shapley additive explanations (SHAP) for interpreting the black-box nature Save
- Artificial intelligence to predict soil temperatures by development of novel model Save