Advanced Interdisciplinary Applications of Deep Learning for Data Science

Advanced interdisciplinary applications of deep learning are revolutionizing the field of data science, enabling new solutions across industries. By leveraging neural networks and datasets, deep learning techniques are transforming how businesses analyze, interpret, and gain insights from complex data. In fields like healthcare, finance, engineering, and business, deep learning models can uncover patterns and make predictions to enhance data-driven decision-making while fostering new opportunities in areas like personalized medicine, autonomous systems, and predictive analytics. As deep learning continues evolves, its interdisciplinary impact expands, creating new possibilities for solving challenges in data science. Advanced Interdisciplinary Applications of Deep Learning for Data Science explores innovations of deep learning technology in data science for various industries and sectors. It examines solutions for decision-making and patient or customer service using machine learning, AI, and predictive analytics. This book covers topics such as bioinformatics, environmental monitoring, and medical diseases, and is a useful resource for data scientists, computer engineers, medical professionals, academicians, and researchers.

Soly Mathew Biju - EditorDr Soly Mathew Biju is a Ph.D. in Computer Science and also an MBA in IT management with 25 years of experience including work at industry and academia. She is currently an Associate Professor at the Faculty of Engineering and Information Sciences, University of Wollongong in Dubai. She worked as the Director for Computer Science(aka Discipline leader)2022-2024.Dr Biju has achieved the CEng status awarded by Engineering Council (UK). She also has achieved the Chartered IT Professional status which is a symbol of excellence in the field of IT and is also an ISTQB-certified software testing professional. She is a Fellow BCS (UK) which is the highest professional award given by professional bodies. She is also a Fellow Higher Education Academy, UK. HEA Fellowship demonstrates a personal and institutional commitment to professionalism in learning and teaching in higher education. It demonstrates commitment to teaching, learning and the student experience, through engagement in a practical process that encourages research, reflection and development. Dr Biju has been in the field of the field of teaching, training, network administration and software development since 1999. Prior to joining UOWD, she worked for various universities including University of Wales, Robert Kennedy College and Champlain College. She is a certified online instructor and has worked extensively on online teaching methods and online material design and development. In the industry, Dr Biju was responsible for leading two teams (Windows NT and Lotus Notes) for British Airways at Heathrow UK, and Pune, India She has conducted a number of workshops on e-learning, WebCT and Blackboard at UOWD and at other universities and a number of technical workshops for faculty and students. She was nominated for the Teaching Excellence and Research Excellence awards at UOWD on numerous occasions and received the prestigious Teaching Excellence Award in 2012, 2015 and 2019. She was also awarded the prestigious Amity Global Academic Excellence award in 2020. Her research interests include machine learning, data security, software testing, cryptography, e-learning, innovations in teaching, agile software development, online teaching, network security and programming techniques. She has papers published in reputed journals and books and presented and reviewed papers at national and international conferences and journals. She has been a scientific and organizing committee member and session chair and content chair on various reputed national and international conferences. She has won a number of research grants for her research proposals and is also an editor for various technical books.

Farhad Oroumchian - EditorDr Farhad Oroumchian s Professor of Artificial Intelligence, Natural Language Processing and Machine Learning in University of Wollongong (Dubai Campus). He has 24 years of experience teaching AI, Machine Learning and Databases. Dr Oroumchian has served at various capacities in the university ranging from Acting Chair of College to Associate Dean of Education. He is currently Head of AI & Intelligent Systems Research Cluster. Prof Oroumchian has worked as Senior Research Engineer at TextWise LLC in Syracuse, New York from 1996 till 1999. Prior to 1996, He has worded as project manager and consultant for various companies in US.