This book addresses topics related to AI, machine learning, deep learning, and cloud computing in materials science. It brings together researchers, developers, practitioners, and users to explore new ideas, techniques, and tools, and to exchange their experiences.
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Dr. Shubham Tayal is Assistant Professor, Department of Electronics and Communication Engineering, SR University, Warangal, India. He has more than 6 years of academic/research experience of teaching at UG and PG level. He has received his B.Tech (ECE) from Maharishi Dayanand University, Rohtak, M.Tech (Electronics) from YMCA University of Science & Technology, Faridabad and PhD from National Institute of Technology, Kurukshetra. He has published several papers in various international journals and conferences of repute and many papers are under review. He is on the editorial and reviewer panel of many international journals. He has received Green ThinkerZ International Distinguished Young Researcher Award 2020. His research area includes semiconductor devices, VLSI design, device-circuit co-design issues, machine learning and IOT.
Dr. Parveen Singla is Professor, Electronics & Communication Engineering, Department of Chandigarh Engineering College- Chandigarh Group of Colleges, Landran, Mohali, Punjab. He received the Bachelor of Engineering in Electronics & Communication Engineering with honors from Maharishi Dayanand University, Rohtak, Master in Technology in Electronics & Communication Engineering with honors from Kurukshetra University, & PhD in Communication Systems from IKG Punjab Technical University, Jalandhar, India. He has 16 years of experience in the field of teaching and research. He has published more than 35 papers in various reputed journals and national and international conferences. He also organised more than 30 technical events for the students in order to enhance their technical skills and received Best International Technical Event Organiser Award. He is the guest editor of various reputed journals. His interest area includes drone technology, wireless networks, smart antenna and soft computing.
Dr. Ashutosh Nandi is Assistant Professor with the Department of Electronics and Communication Engineering, National Institute of Technology Kurukshetra, India. He received the Ph.D. degree from IIT Roorkee, India, in 2015. He has authored more than 50 articles in various international journals and conferences of repute. His current research interests include low-power very large scale integration design, device circuit codesign in the digital/analog domain, and device modeling of multigate semiconductor devices.
Dr. J. Paulo Davim received his Ph.D. degree in Mechanical Engineering in 1997, M.Sc. degree in Mechanical Engineering (materials and manufacturing processes) in 1991, Mechanical Engineering degree (5 years) in 1986, from the University of Porto (FEUP), the Aggregate title (Full Habilitation) from the University of Coimbra in 2005 and the D.Sc. (Higher Doctorate) from London Metropolitan University in 2013. He is Senior Chartered Engineer by the Portuguese Institution of Engineers with an MBA and Specialist titles in Engineering and Industrial Management as well as in Metrology. He is also Eur Ing by FEANI-Brussels and Fellow (FIET) of IET-London. Currently, he is Professor at the Department of Mechanical Engineering of the University of Aveiro, Portugal. He is also distinguished as honorary professor in several universities/colleges. He has more than 30 years of teaching and research experience in Manufacturing, Materials, Mechanical and Industrial Engineering, with special emphasis in Machining & Tribology. He has also interest in Management, Engineering Education and Higher Education for Sustainability. He has guided large numbers of postdoc, Ph.D. and master’s students as well as has coordinated and participated in several financed research projects. He has received several scientific awards and honors. He has worked as evaluator of projects for ERC-European Research Council and other international research agencies as well as examiner of Ph.D. thesis for many universities in different countries. He is the Editor in Chief of several international journals, Guest Editor of journals, books Editor, book Series Editor and Scientific Advisory for many international journals and conferences. Presently, he is an Editorial Board member of 30 international journals and acts as reviewer for more than 100 prestigious Web of Science journals. In addition, he has also published as editor (and co-editor) more than 150 books and as author (and co-author) more than 15 books, 100 book chapters and 500 articles in journals and conferences (more than 250 articles in journals indexed in Web of Science core collection/h-index 55+/9500+ citations, SCOPUS/h-index 60+/12000+ citations, Google Scholar/h-index 77+/19500+ citations).
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Paperback. Zustand: new. Paperback. Advanced materials are essential for economic security and human well-being, with applications in industries aimed at addressing challenges in clean energy, national security, and human welfare. Yet, it can take years to move a material to the market after its initial discovery. Computational techniques have accelerated the exploration and development of materials, offering the chance to move new materials to the market quickly. Computational Technologies in Materials Science addresses topics related to AI, machine learning, deep learning, and cloud computing in materials science. It explores characterization and fabrication of materials, machine-learning-based models, and computational intelligence for the synthesis and identification of materials. This book Covers material testing and development using computational intelligence Highlights the technologies to integrate computational intelligence and materials science Details case studies and detailed applications Investigates challenges in developing and using computational intelligence in materials science Analyzes historic changes that are taking place in designing materials.This book encourages material researchers and academics to develop novel theories and sustainable computational techniques and explores the potential for computational intelligence to replace traditional materials research. This book addresses topics related to AI, machine learning, deep learning, and cloud computing in materials science. It brings together researchers, developers, practitioners, and users to explore new ideas, techniques, and tools, and to exchange their experiences. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9780367640583
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