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Issues of Sustainability in AI and New-Age Thematic Investing

Mohammad Irfan Khaled Hussainey Syed Ahmad Chan Bukhari Yunyoung Nam

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English
Business Science Reference
18 March 2024
In the face of an evolving global landscape characterized by climate change and a pressing need for sustainable development, the finance sector remains at a critical juncture. Traditional financial models struggle to address the challenges posed by the transition to a low-carbon economy, and unlocking private investments for sustainable initiatives remains an uphill battle. The integration of Artificial Intelligence (AI) and Machine Learning (ML) into financial systems presents both promise and peril, with the potential to reshape the industry while posing unprecedented challenges. Issues of Sustainability in AI and New-Age Thematic Investing is a beacon of insight and solutions in the realm of green finance and AI/ML integration. Geared toward academic scholars, policymakers, and industry experts, this book serves as a comprehensive guide to navigating the intricacies of sustainable development and energy transition. By highlighting the pivotal role of AI/ML in green finance, the publication bridges the gap between theoretical understanding and practical implementation, offering actionable solutions for unlocking private investments. Tailored for researchers and decision-makers across environmental economics, finance, and sustainability, the book is not just a repository of knowledge—it is a roadmap to a sustainable future. Covering an array of topics from renewable energy to Blockchain and Data Science, it is poised to become an indispensable resource for those seeking to make significant contributions to the global effort against climate change. Issues of Sustainability in AI and New-Age Thematic Investing’s emphasis on practical solutions positions it as a vital tool in shaping the future of finance, where AI and sustainable development converge to pave the way for a resilient and green economy.
Edited by:   , , ,
Imprint:   Business Science Reference
Country of Publication:   United States [Currently unable to ship to USA: see Shipping Info]
Dimensions:   Height: 254mm,  Width: 178mm,  Spine: 17mm
Weight:   558g
ISBN:   9798369346990
Pages:   295
Publication Date:  
Audience:   College/higher education ,  Professional and scholarly ,  Primary ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active

Mohammad Irfan is presently working as an Associate Professor at School of Business and Management, Christ University, Bengaluru, India. Dr. Irfan has done his Ph.D. from the Central University of Haryana. He is MBA (Finance), M.Com (Account and Law), and MA (Economics). He has qualified UGC-JRF/SRF/NET in Management and Commerce. Dr. Irfan certified NSEs (NCFM) and BSEs certification. He has experience of more than sixteen years in the area of SAPM, Artificial Intelligence, Machine Learning, Blockchain, Cryptocurrency, Financial Engineering, Fintech, Green Finance, and Alternative Finance. He has to his credit more than 61+ Scopus Indexed articles, includes The Journal of Economic Cooperation and Development (Q2), International Journal of Business Excellence (IJBEX), International Journal of Economics and Management (IJEM), Montenegrin Journal of Economics (Q2), Cogent Business & Management (Taylor & Francis) (Q2), Indian Journal of Finance (IJF) and Journal of Islamic Monetary Economics and Finance (JIMF). His citations reached 404+ along with 13 H-index. Dr. Irfan has published 9 books in Springer, IGI Global Publication (Scopus indexed). Khaled Hussainey is currently affiliated with the University of Portsmouth in the UK. Syed Ahmad Chan Bukhari is as an Assistant Professor and Director of Healthcare Informatics at St. John's University, New York. He received his Ph.D. in Computer Science from the University of New Brunswick, Canada and then went on to complete his postdoctoral fellowship at Yale School of Medicine where he worked with Stanford University- Center of Expanded Data Annotation and Retrieval (CEDAR) to develop FAIR (Findable, Accessible, Interoperable and Reusable) data submission pipelines to improve scientific experimental reproducibility. His current research efforts are concentrated on addressing several core problems in the area of healthcare informatics and data science. More htttp://ahmadchan.com. Yunyoung Nam (Member, IEEE) received the B.S., M.S., and Ph.D. degrees in computer engineering from Ajou University, South Korea, in 2001, 2003, and 2007, respectively. He was a Senior Researcher with the Center of Excellence in Ubiquitous System, Stony Brook University, Stony Brook, NY, USA, from 2007 to 2010, where he was a Postdoctoral Researcher, from 2009 to 2013. He was a Research Professor with Ajou University, from 2010 to 2011. He was a Postdoctoral Fellow with the Worcester Polytechnic Institute, Worcester, MA, USA, from 2013 to 2014. He was the Director of the ICT Convergence Rehabilitation Engineering Research Center, Soonchunhyang University, from 2017 to 2020. He has been the Director of the ICT Convergence Research Center, Soonchunhyang University, since 2020, where he is currently an Assistant Professor with the Department of Computer Science and Engineering. His research interests include multimedia database, ubiquitous computing, image processing, pattern recognition, context-awareness, conflict resolution, wearable computing, intelligent video surveillance, cloud computing, biomedical signal processing, rehabilitation, and healthcare systems.

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