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 distinguished scholar, researcher, and industry expert specializing in data science for ESG (Environmental, Social, and Governance), applied machine learning, and computational analytics. With over 18 years of experience, he has made groundbreaking contributions to numerical analysis, computational applied statistics, and big data analytics, earning a reputation as a thought leader in the field. His academic journey commenced in 2008 at Curtin University Malaysia, where his exceptional research led to the prestigious Australian Government Scholarship in 2012, enabling him to pursue a PhD at Curtin University, Australia. Successfully completing his doctorate in 2018, Dr. Aruchunan continued his tenure at Curtin until 2020 before joining Universiti Malaya, where he currently serves as a senior lecturer in the Department of Decision Science, Faculty of Business and Economics. His work focuses on ESG data science, decision analytics, and AI-driven sustainability solutions, positioning him at the forefront of transformative research in these areas. Dr. Aruchunan’s expertise extends beyond academia into real-world problem-solving through advanced machine learning and deep learning applications. His research is dedicated to developing innovative algorithms and methodologies that address complex challenges in big data analytics, predictive modeling, and applied mathematics. His prolific contributions are widely recognized, with numerous high-impact journal publications, conference presentations, and research projects funded by national and international bodies. A passionate educator, Dr. Aruchunan is also an accredited HRD Corp trainer, conducting specialized training programs for government agencies and industry professionals. His training focuses on big data, data science, machine learning, and deep learning, equipping participants with cutting-edge skills in Python applications, data mining, and applied AI. His programs are meticulously designed to bridge academic theory and industry applications, empowering professionals with practical expertise in the evolving digital landscape. Beyond research and training, Dr. Aruchunan is committed to STEM education outreach and academic collaboration, mentoring postgraduate scholars, and engaging in knowledge-sharing initiatives with both local and international researchers. He is an active member of several esteemed professional bodies, including IEEE, PERSAMA, IAENG, and IACSIT, reinforcing his influence in the global data science community. In recognition of his outstanding contributions, Dr. Aruchunan was appointed to the prestigious Young Scientist Network by the Academy of Sciences Malaysia, a testament to his leadership in scientific research and his dedication to advancing Malaysia’s research capabilities. With an unwavering commitment to data-driven innovation, education, and sustainability, Dr. Elayaraja Aruchunan continues to shape the future of ESG analytics, AI-driven decision-making, and applied machine learning, leaving a profound impact on academia, industry, and society. |
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.