Handbook of Probabilistic Models

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). In 2010, Dr. Pijush joined in the Center for Disaster Mitigation and Management at VIT University as an Associate Professor. He was promoted to full Professor in 2012. Dr. Pijush is the recipient of the prestigious CIMO fellowship (2009) from Finland, for his integrated research on the design of railway embankment. He was awarded Shamsher Prakash Research Award (2011) by IIT Roorkee for his innovative research on the application of Artificial Intelligence in designing civil engineering structure. He was selected as the recipient of IGS Sardar Resham Singh Memorial Award – 2013 for his innovative research on infrastructure project. He was elected Fellow of International Congress of Disaster Management in 2010. He served as a guest in disaster advance journal. He also serves as an editorial board member in several international journals. He has been selected as an adjunct professor at Ton Duc Thang University (Ho Chi Minh City, Vietnam). He has been Visiting Professor at Far East Federal University (Russia).

Dieu Tien Bui is currently an Associate Professor at the GIS group, University of South-Eastern Norway, Norway. An editor for several scientific journals, he received his M.Sc. degree in Cartographic Engineering from Hanoi University of Mining and Geology, Hanoi, Vietnam, in 2004, and his Ph.D. in Geomatics from the Norwegian University of Life Sciences, Aas, Norway, in 2013. He was a postdoctoral researcher at the Norwegian University of Life Sciences from 2013 to 2014. In 2007-2008, he was a geospatial analyst at Ugland IT Group, a geographic information services company in Lysaker, Oslo, Norway. He has more than 120 publications to his credit, including 85 articles published in Science Citation Index (SCI/SCIE) scientific journals. His research interests include GIS, remote sensing, and artificial intelligence and machine learning for natural hazards and environmental problems such as landslides, floods, forest fires, ground biomass, and structural displacement.

Dr. Subrata Chakraborty is currently a Professor and former Head of Civil Engineering Department at the Indian Institute of Engineering Science and Technology, Shibpur. He is a fellow of the Indian National Academy Engineering. Prof. Chakraborty did his Bachelor in Civil Engineering from Bengal Engineering College, Shibpur, M. Tech. and PhD from IIT Kharagpur. He was a postdoctoral researcher at University of Cambridge, UK and University of Arizona, USA and Technical University of Aachen, Germany. In general, Prof. Chakraborty’s research interests are in the field of computational mechanics under uncertainty, structural health monitoring, vibration control, composite mechanics etc. He has published extensively in peer reviewed journals, authored textbook and book chapters and reviewed research articles for various national and international journals. As an independent researcher, he has completed a number of research projects funded by various agencies and is also active in important industrial consultancy. While his inspiring teaching coupled with innate urge for intensive research has already established him as a distinguished academician at the national level, several awards and laurels have come his way. The Humboldt Fellowship for Experienced Researchers, the V. H. Joshi Award for Significant Contributions in Structural Dynamics, the INAE Young Engineer Award, the BOYSCAST Fellowship, and the Young Faculty Research Award deserve special mention.

Professor Ravinesh Deo is an Associate Professor at University of Southern Queensland, Australia, Program Director for Postgraduate Science Program and Research Leader in Artificial Intelligence. He also serves as Associate Editor for two international journals: Stochastic Environmental Research and Risk Assessment and the ASCE Journal Hydrologic Engineering journal (USA). As an Applied Data Scientist with proven leadership in artificial intelligence, his research develops decision-systems with machine learning, heuristic and metaheuristic algorithms to improve real-life predictive systems especially using deep learning explainable AI, convolutional neural networks and long short-term memory networks. He was awarded internationally competitive fellowships including Queensland Government U.S. Smithsonian Fellowship, Australia-India Strategic Fellowship, Australia-China Young Scientist Exchange Award, Japan Society for Promotion of Science Fellowship, Chinese Academy of Science Presidential International Fellowship and Endeavour Fellowship. He is a member of scientific bodies, won Publication Excellence Awards, Head of Department Research Award, Dean’s Commendation for Postgraduate Supervision, BSc Gold Medal for Academic Excellence and he was the Dux of Fiji in Year 13 examinations. Professor Deo held visiting positions at United States Tropical Research Institute, Chinese Academy of Science, Peking University, Northwest Normal University, University of Tokyo, Kyoto and Kyushu University, University of Alcala Spain, McGill University and National University of Singapore. He has undertaken knowledge exchange programs in Singapore, Japan, Europe, China, USA and Canada and secured international standing by researching innovative problems with global researchers. He has published Books with Springer Nature, Elsevier and IGI and over 190 publications of which over 140 are Q1 including refereed conferences, Edited Books and book chapters. Professor Deo’s papers have been cited over 4,000 times with Google Scholar H-Index of 36 and a Field Weighted Citation Index exceeding 3.5.