Optimizing Heterogeneous Data to Fight Climate Change

Posted November 23, 2021 | Sustainability | Technology |
climate change world
As artificial intelligence (AI) and machine learning (ML) gain attention for their potential to tackle the environmental challenges posed by climate change, their requirement of heterogeneous data takes center stage. This Advisor addresses the fact that while heterogeneous data plays a critical role in the use of AI and ML to combat climate change, there is a dual side that is not environmentally friendly.
About The Author
Rohit Nishant
Rohit Nishant is Associate Professor in the Department of Management Information Systems at Université Laval, Canada, and a Cutter Expert. His research has been published/accepted in several international journals, including MIS Quarterly, MIS Quarterly Executive, Journal of the Association for Information Systems, Journal of Strategic Information Systems, Information Systems Journal, Decision Sciences, and IEEE Transactions on Engineering… Read More
Thompson S.H. Teo
Thompson S.H. Teo is Professor in the Department of Analytics and Operations at National University of Singapore Business School. His research interests include the adoption of IT, strategic IT planning, electronic government, knowledge management, and sustainability. Dr. Teo has published more than 250 papers in international journals and conferences. He has served as Senior Associate Editor for European Journal of Information Systems, Regional… Read More
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