Springer Big Data in Engineering Applications: 44 (Studies in Big Data, 44)

Product Description This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas. From the Back Cover This book presents the current trends, technologies, and challenges in Big Data in the diversified field of engineering and sciences. It covers the applications of Big Data ranging from conventional fields of mechanical engineering, civil engineering to electronics, electrical, and computer science to areas in pharmaceutical and biological sciences. This book consists of contributions from various authors from all sectors of academia and industries, demonstrating the imperative application of Big Data for the decision-making process in sectors where the volume, variety, and velocity of information keep increasing. The book is a useful reference for graduate students, researchers and scientists interested in exploring the potential of Big Data in the application of engineering areas. About the Author Sanjiban Sekhar Roy is working as an associate professor in School of Computer Science and Engineering, VIT University. He joined this institute in  the year 2009 as an assistant professor. He holds a B.E degree in Information Technology from the University of North Bengal and an M.Tech degree in Computer Science and Engineering from VIT University. He qualified GATE examination, which is a national level engineering entrance test conducted by IITs and IISC. Sanjiban carried out his nine months M.Tech project as an intern student in Indian Institute of Technology (IIT), Kharagpur, India. In the year 2016 he completed his Ph.D. degree in Computer science and Engineering from VIT University. His research interests include machine learning, data mining, and pattern recognitions. He has to his credit around 33 articles published in international journals and international conferences and one edited book with Elsevier publisher. He is an editorial board member of “International Journal of Advanced Intelligent Paradigms”, Inderscience and reviewer for many international journals. Pijush Samui is working as an associate professor in civil engineering department at NIT Patna, India. He graduated in 2000, with a B.Tech. in Civil Engineering from Indian Institute of Engineering Science and Technology, Shibpur, India. He received his M.Sc. in Geotechnical Earthquake Engineering from Indian Institute of Science, Bangalore, India (2004). He holds a Ph.D. in Geotechnical Earthquake Engineering (2008) from Indian Institute of Science, Bangalore, India. He was a postdoctoral fellow at University of Pittsburgh (USA) (2008-2009) and Tampere University of Technology (Finland) (2009- 2010). At University of Pittsburgh, he worked on design of efficient tool for rock cutting and application of Support Vector Machine (SVM) in designing of geostructure. At Tampere University of Technology, he worked on design of railway embankment, slope reliability and site characterization. In 2010, Dr. Pijush joined in the Center for Disaster Mitigation and Management at VIT University as an Associate Professor. He was promoted to a Professor in 2012. Dr. Pijush’s research focuses on the application of Artificial Intelligence for designing civil engineering structure, design of foundation, stability of railway embankm