The book Applied Assistive Technologies and Informatics for Students with Disabilities provides a comprehensive guide to assist students with learning disabilities in higher education via modern assistive technologies and informatics. This book will take us on a tour of the various modern assistive technologies, such as artificial intelligence (AI), blockchain, computer vision (CV), text analytics (TA), the metaverse, human-computer interaction (HCI), digital twins (DT), and federated learning (FL), and how they support higher education students with learning disabilities.
This book is intended for students with learning disabilities, scientists and researchers, lecturers and teachers, academic and corporate libraries, practitioners, and professionals who are interested in providing inclusive education to students with learning disabilities through the application of modern assistive technologies and informatics. This book is ideal for readers who are new to the subject and knowledgeable about the principles of inclusive education. In addition, it is a fantastic resource for teachers and parents assisting students with learning disabilities. This book can be a powerful tool to educate more students about learning disabilities, which can help eradicate the bullying of these students.
Chapter 1 Blockchain for handling the data in Higher Education.- Chapter
2 Reshaping the Future of Learning Disabilities in Higher Education with AI.-
Chapter 3 Virtual Environment Role in Higher Education Students Learning
Enhancement with Intellectual Disabilities.
Chapter 4 AI Wizards:
Pioneering Assistive Technologies for Higher Education Inclusion of Students
with Learning Disabilities.- Chapter 5 The Impact of Virtual Reality and
Augmented Reality in Inclusive Educatio.- Chapter 6 Exploring Assistive
Technology for Students with Disabilities in Higher Education.
Chapter
7 Sign Language Recognition based Machine Learning Model for Hearing
Disabilities Person.- Chapter 8 Assistive Technologies in Higher Education
for Special Education.
Chapter 9 Deep Learning Approach for Detection of
Learning Disabilities in Higher Education.
Chapter 10 A Computer Vision
Approach: Enhancing Visual Data for Students with Learning Disabilities in
Higher Education.
Chapter 11 Inclusive Virtual Reality Learning
Environment.- Chapter 12 Deep Learning-Based Automatic Speech and Emotion
Recognition for Students with Disabilities: A review.
Chapter 13 Metaverse
of Learning Disabilities in Higher Educational Institutions.
Chapter
14 Technologies to assist students with specific learning disabilities in
higher education: Concepts, Challenges, and Future Directions.
Chapter
15 Empowering Inclusive Education: Leveraging AI-ML and Innovative Tech
Stacks to Support Students with Learning Disabilities in Higher
Education.- Chapter 16 Systematic Review of Recent Trends of Industry 5.0
with Assistive Technologies in Higher Education and Smart
Healthcare.- Chapter 17 Diagnostic Criteria for Schizophrenia: A Systematic
Review.
Dr. Rajesh Kaluri is familiar with emerging fields like Computer vision, Machine learning, and Big Data analytics. He has completed Ph.D. in Computer Vision and is currently working on multi-disciplinary projects. Currently, he is working as an Associate Professor in the School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore India. He has 12+ years of teaching experience. He was a visiting professor at Guangdong University of Technology, China in 2015 and 2016. Dr. Rajesh Kaluri is an academic journal editor and has published 40+ research papers in various reputed international journals.
Dr Mufti Mahmud is an Associate Professor of Cognitive Computing at Nottingham Trent University (NTU), UK, where he is also a member of the University Shadow Executive Team. He is listed among the top 2% cited scientists worldwide in computer science (since 2020) and a recipient of the NTU VC Outstanding Researcher Award 2021 and the Marie-Curie Postdoctoral Fellowship. He is the coordinator of the Computer Science REF Assessment Unit and the deputy head of the ISRG and CCIS research groups. His research portfolio consists of over 4 million GBP grant capture with the publication of over 225 research outputs in fields that include brain informatics, computational intelligence, applied data analysis, and big data technologies focusing on healthcare applications. He is a section editor of the Cognitive Computation journal, a regional editor (Europe) of the Brain Informatics journal, and an Associate Editor of the Frontiers in Neuroscience journal. Dr Mahmud holds active volunteer roles in BCS, IEEE (CIS and EMBS), ACM, APNNS, and INNS as a (senior) member. He is also actively involved in the organization of leading conferences in the field (e.g., WCCI, IJCNN, SSCI, ICONIP, BI, AII).
Dr. Thippa Reddy Gadekallu is currently working as an Associate Professor in the School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, Tamil Nadu, India. He has been listed among the worlds top 2% cited scientists since 2020. He has more than 100 international/national publications in reputed journals and conferences.
Dr. Dharmendra Singh Rajput has been working as a Professor in the Department of Software and Systems Engineering, School of Computer Science Engineering and Information Systems, VIT, Vellore, since June 2014. He has received various awards from the Indian Government, including DST-SERB, CSIR Travel Grant, and MPCST Young Scientist Fellowship. For academic purposes, he has visited various countries such as UK, France, Singapore, UAE, China, and Malaysia.
Dr. Kuruva Lakshmanna is currently working as an Associate Professor in the School of Computer Science Engineering and Information Systems, Vellore Institute of Technology, Vellore, Tamil Nadu, India. He has 12 years of experience in teaching and has published around 60 papers in various reputed international journals. He has been listed among the worlds top 2% cited scientists for 2023.
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