Applying artificial intelligence (AI) to new fields has made AI and data science indispensable to researchers in a wide range of fields. The proliferation and successful deployment of AI algorithms are fuelling these changes, which can be seen in fields as disparate as healthcare and emerging Internet of Things (IoT) applications. Machine learning techniques, and AI more broadly, are expected to play an ever-increasing role in the modelling, simulation, and analysis of data from a wide range of fields by the interdisciplinary research community. Ideas and techniques from multidisciplinary research are being utilised to enhance AI; hence, the connection between the two fields is a two-way street at a crossroads. Algorithms for inference, sampling, and optimisation, as well as investigations into the efficacy of deep learning, frequently make use of methods and concepts from other fields of study. Cloud computing platforms may be used to develop and deploy several AI models with high computational power. The intersection between multiple fields, including math, science, and healthcare, is where the most significant theoretical and methodological problems of AI may be found. To gather, integrate, and synthesise the many results and viewpoints in the connected domains, refer to it as interdisciplinary research. In light of this, the theory, techniques, and applications of machine learning and AI, as well as how they are utilised across disciplinary boundaries, are the main areas of this research topic.
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Dr. Sukhpal Singh Gill (FHEA) is a Assistant Professor in Cloud Computing at School of Electronic Engineering and Computer Science (EECS), Queen Mary University of London (QMUL), UK and he is a member of Network Research Group. Prior to this, Dr. Gill has held positions as a Research Associate at Evolving Distributed Systems Lab at the School of Computing and Communications, Lancaster University, UK and also as a Postdoctoral Research Fellow at the Cloud Computing and Distributed Systems (CLOUDS) Laboratory, School of Computing and Information Systems, The University of Melbourne, Australia. He has published his PGCAP/PGCert work in highly-ranked Education Conferences and Journals. Before joining CLOUDS Lab, Dr. Gill worked in the Computer Science and Engineering Department of Thapar University, India, as a Lecturer. Dr. Gill received a Doctoral Degree specialization in Autonomic Cloud Computing from Thapar University. He worked as a Senior Research Fellow (Professional) on DST Project, Government of India. Dr. Gill was a research visitor at Monash University, University of Manitoba, University of Manchester and Imperial College London. He has recieved several awards. He has also served as the PC member for various venues. He has co-authored 150+ peer-reviewed papers and has published in prominent international journals and conferences. He serves as a Guest Editor and is a regular reviewer for multiple journals. He has also edited multiple research books He has also written for magazines such as Ars Technica, Tech Monitor, Cutter Consortium and ICT Academy. For further information, visit www.ssgill.me.
In order to gather, integrate, and synthesise the many results and viewpoints in the connected domains, refer to it as interdisciplinary research. In light of this, the theory, techniques, and applications of machine learning and AI, as well as how they are utilised across disciplinary boundaries, are the main areas of this research topic.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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