DR. ELAYARAJA A/L ARUCHUNAN
Department of Decision Science
Faculty of Business and Economics
elayarajahum.edu.myView CV | |
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Publons | |
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Biography | |
Dr. Elayaraja Aruchunan is a renowned expert in data science for ESG (Environmental, Social, and Governance) and a distinguished academic and researcher with over 18 years of expertise in numerical analysis, computational applied statistics, and applied machine learning. His academic journey began in March 2008 at Curtin University Malaysia, where his groundbreaking contributions earned him the prestigious Australian Government Scholarship in 2012. This honour allowed him to pursue his PhD at Curtin University, Australia, which he successfully completed in 2018. Following his doctorate, Dr. Aruchunan continued his academic career at Curtin University until 2020, before joining Universiti Malaya. He currently serves as a Senior Lecturer in the Department of Decision Science within the Faculty of Business and Economics, where he continues to drive innovation in ESG data science, decision analytics, and machine learning applications. With a passion for data-driven sustainability solutions, Dr. Aruchunan remains at the forefront of cutting-edge research, shaping the future of ESG analytics and decision science. Dr. Aruchunan's research interests focus on the development of innovative algorithms and methodologies to address complex real-world challenges. His notable contributions span applied machine learning, big data analytics, and applied mathematics. He has extensively published his work in high-impact journals and presented at prestigious conferences. His research has attracted substantial funding from both domestic and international sources, underscoring the importance and applicability of his work. Beyond his research, Dr. Aruchunan is a passionate educator and mentor. He guides postgraduate research scholars and teaches undergraduate and graduate courses in data science, machine learning, and related fields. He is an accredited trainer under HRD Corp, offering professional training in Python applications, data mining, applied machine learning, and big data. His training sessions are designed to bridge the gap between theory and practice, empowering professionals with cutting-edge skills in data science and analytics. Dr. Aruchunan is also deeply committed to outreach activities, particularly in promoting STEM education among high school students. He is an advocate for collaboration and knowledge exchange, actively engaging with researchers from local and international institutions to advance the fields of data science and machine learning. His professional affiliations include memberships in esteemed societies such as IEEE, PERSAMA, IAENG, and IACSIT. Recognized for his contributions to science and academia, Dr. Aruchunan has been appointed to the prestigious Young Scientist Network by the Academy of Sciences Malaysia. This honor highlights his role as a rising leader in scientific research and his commitment to advancing the nation's scientific capabilities. Dr. Aruchunan's remarkable achievements and dedication to his field have established him as a leading expert. Through his research, teaching, and professional development initiatives, he continues to make a positive and lasting impact in academia and beyond. |
Publication
Finance
Project Title | Progress | Status |
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ESG and Sustainability in Malaysia: Navigating the Challenges and Opportunities Ahead |
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on going |
Hybrid Machine Learning Model To Build A Rigid Pedestrian Walkway Pavement From Plastic Waste |
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on going |
This information is generated from Research Grant Management System |
Leveraging dynamics informed neural networks for predictive modeling of COVID-19 spread: a hybrid SEIRV-DNNs approach
Leveraging dynamics informed neural networks for predictive modeling of COVID-19 spread: a hybrid SEIRV-DNNs approach
Intelligent Application of Partial Least Square Algorithm in Developing Model of Fat Depth Measurement
Intelligence Random Forest Application in Developing Regression Model from Lamb Carcass C-Site Fat Depth Data
Intelligence Predictive Model for Lamb Carcass C-Site Fat Depth Using Support Vector Machine
Intelligent LASSO Regression Modelling for Seaweed Drying Analysis
Effectiveness of Cooperative Learning Strategies in Improving Performance for Large Mathematics Classes
Intelligence Random Forest Application in Developing Regression Model from Lamb Carcass C-Site Fat Depth Data
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.