DR. ELAYARAJA A/L ARUCHUNAN
Department of Decision Science
Faculty of Business and Economics
elayarajah@um.edu.myView CV | |
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Biography | |
Dr. Elayaraja Aruchunan is a distinguished academic and researcher with over 16 years of expertise in numerical analysis, computational applied statistics, and applied machine learning. His illustrious research journey began at Curtin University Malaysia (2008-2012), where he made significant strides that earned him a prestigious Australian Government scholarship in 2012. This opportunity led him to pursue his doctorate at Curtin University in Australia. After completing his Ph.D., Dr. Aruchunan continued his academic career at Curtin University until 2020, when he joined the Universiti Malaya. Currently, he is a faculty member in the Department of Decision Science within the Faculty of Business and Economics. His research interests span the development of innovative algorithms and methodologies to address complex real-world challenges, with notable contributions in applied machine learning, big data analytics, and applied mathematics. His work has been widely published in esteemed WoS journals and at prestigious conferences, attracting research funding from both domestic and international sources. Beyond his research, Dr. Aruchunan is a passionate educator and mentor, guiding postgraduate research scholars and teaching undergraduate and graduate courses in data science and machine learning. He is also committed to outreach activities promoting STEM education among high school students. An advocate for collaboration and knowledge exchange, Dr. Aruchunan actively engages with researchers from local and international institutions to advance data science and machine learning. He holds memberships in professional societies such as the IEEE, PERSAMA, IAENG, and IACSIT. Dr. Aruchunan's remarkable contributions have established him as a leading expert in his field, and he remains dedicated to making a positive impact through his research and teaching. |
Publication
Finance
Project Title | Progress | Status |
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Hybrid Machine Learning Model To Build A Rigid Pedestrian Walkway Pavement From Plastic Waste |
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This information is generated from Research Grant Management System |
A new fractional integration approach based on neural network nonlinearity with an application to testing unemployment hysteresis
Identifying Multiple Outliers in Linear Functional Relationship Model Using a Robust Clustering Method
Thermocapillarity in Cross Hybrid Nanofilm Flow Past an Unsteady Stretching Sheet
Improvement of Time Forecasting Models Using Machine Learning for Future Pandemic Applications Based on COVID-19 Data 2020-2022
Efficient Iterative Approximation for Nonlinear Porous Medium Equation with Drainage Model
Thermal Analysis of VLSI System using Successive Over Relaxation (SOR) Method
Solution of Peak Junction Temperature with Crank-Nicolson and SOR Approach
Efficiency Evaluation of Half-Sweep Newton-EGSOR Method to Solve 1D Nonlinear Porous Medium Equations
The Solidarity Role of the “Fearless Cities” Initiative: A Lesson on the Malaysian E-Hailing Sector.
Consumer Behaviour in On-Demand Application-Based Gig Economy Operations-A Conceptual Framework
Effects of the COVID-19 Pandemic on Gig Economy in Malaysia: An Application of ‘Tragedy of the Commons'
The Influence of Brand Loyalty and Perceived Quality on Consumer Buying Behaviour of Smartphones among Politeknik Kota Kinabalu Sabah, Malaysia Students.