Description: Federated Learning for the Metaverse: Applications in Virtual Environments provides readers with insights into how federated learning, a decentralized machine learning paradigm, can be strategically applied to address critical aspects of the metaverse. The book covers a wide range of topics, including privacy-preserving personalization, security, collaboration, adaptive learning environments, real-time communication, decentralized governance, language understanding, immersive learning experiences, avatar customization, and dynamic scene rendering.
Brief description: Prof. Jhanjhi is currently working as a Professor in Computer Science (Cybersecurity) and Program Director for the Postgraduate Research Degree Programmes at the School of Computer Science at Taylor's University, Malaysia. He has been nominated as the world's top 2% research scientist globally for 2022 and 2023, received the vice chancellor's highly cited research award, and was nominated as an Outstanding faculty member by the MDEC Malaysia for the year 2022. He has several international Patents on his account, including Australian, German, UK, and Japanese. He edited/authored over 45 research books published by world-class publishers. He has excellent experience supervising and co-supervising postgraduate students, and more than 37 Postgraduate scholars graduated under his supervision. Prof. Jhanjhi serves as Associate Editor and Editorial Assistant Board for several reputable journals, such as PeerJ Computer Science, CMC Computers, Materials & Continua, Computer Systems Science and Engineering CSSE, and Frontier in Communication and Networks. He received Outstanding Associate Editor for IEEE ACCESS. He has been a Keynote/Invited speaker for more than 60 international conferences and chaired international conference sessions globally. His research areas include Cybersecurity, IoT security, Wireless security, Data Science, Software Engineering, and UAVs.