Neuro-Symbolic AI

Dr. Sarika Jain graduated from Jawaharlal Nehru University (India) in 2001. Her doctorate is in the field of Knowledge Representation in Artificial Intelligence which was awarded in 2011. She has served in the field of education for over 19 years and is currently working at the National Institute of Technology Kurukshetra (Institute of National Importance), India. Dr. Jain has authored / co-authored over 100 publications including books. Her current research interests include Knowledge Management and Analytics; Semantic Web; Ontological Engineering; and Intelligent Systems.Dr. Jain has supervised two doctoral scholars (5 ongoing) who are now pursuing their post doctorates, one in Spain and the other in Germany. Currently, she is guiding 15 students for their Master’s and Doctoral research work in the area of Knowledge Representation. She is serving as a reviewer for Journals of IEEE, Elsevier, and Springer. She has been involved as a program and steering committee member in many prestigious conferences in India and abroad.She has two research-funded projects: one ongoing project is funded by CRIS TEQUIP-III worth Rs 2.58 lakhs, and the other completed project is funded by DRDO, India worth Rs 40 lakhs. She has also applied for a patent in Nov 2019. Dr. Jain has held various administrative positions at department as well as at institute level in her career like HOD, Hostel Warden, Faculty Incharge of technical and cultural fests, member of Research Degree Committee, and Center Incharge Examinations.Dr. Jain has visited the United Kingdom and Singapore for presenting her research work. She has constantly been supervising DAAD interns from different German universities and many interns from India every summer. She works in collaboration with various researchers across the globe including Germany, Austria, Australia, Malaysia, the United States, Romania and many others. She has organized various challenges, conferences and workshops including NITC, GIAN by MHRD, ISIC, ICSCC, ICACCT, ICECCS, and EWAD. She is a member of IEEE and ACM and a Life Member of Computer Society of India (CSI), International Association of Engineers (IAENG), and the International Association of Computer Science and Information Technology (IACSIT).Dr. Jain is highly interested in world-wide collaborations and seeking scholars and interns in her research group. Houbing Song, Security and Optimization for Networked Globe Laboratory, University of Maryland, Baltimore County (UMBC), Baltimore, USA. His research interests include cyber-physical systems, cybersecurity and privacy, IoT, big data analytics, connected vehicles, smart health, wireless communications, and networking. Dr. Song has edited and authored several books in the field, including Cyber-Physical Systems: Foundations, Principles and Applications. Dr. Sonika Malik has done her doctorate from National Institute of technology, Kurukshetra in 2022. She did her Masters from MMU in 2010 and B. Tech from Kurukshetra University, India in 2004. She has served in the field of education from last 17 years and is currently working as an Assistant Professor in Maharaja Surajmal Institute of Technology since 2007. Her current research interests are in the area of Semantic Web, Knowledge representation and Ontology Engineering and Design. A talented professional who has good teaching skills developed as a result of 17 years of experience in teaching computer and IT related subjects and concepts in engineering graduate students. She has extensive research experience in semantic web and published research articles in various international journals/conferences and in book of international repute as book chapters. She has also reviewed also reviewed papers in various journals and conferences. She has also organized special sessions in international conferences. Dr. Pascal Hitzler is University Distinguished Professor and endowed Lloyd T. Smith Creativity in Engineering Chair at the Department of Computer Science at Kansas State University, one of the Directors of the Institute for Digital Agriculture and Advanced Analytics (ID3A), and Director of the Center for Artificial Intelligence and Data Science (CAIDS). Until July 2019 he was endowed NCR Distinguished Professor, Brage Golding Distinguished Professor of Research, and Director of Data Science at the Department of Computer Science and Engineering at Wright State University in Dayton, Ohio, U.S.A. He is director of the Data Semantics (DaSe) Lab. From 2004 to 2009, he was Akademischer Rat at the Institute for Applied Informatics and Formal Description Methods (AIFB) at the University of Karlsruhe in Germany, and from 2001 to 2004 he was postdoctoral researcher at the Artificial Intelligence institute at TU Dresden in Germany. In 2001 he obtained a PhD in Mathematics from the National University of Ireland, University College Cork, and in 1998 a Diplom (Master equivalent) in Mathematics from the University of Tübingen in Germany. His research record lists over 400 publications in such diverse areas as neurosymbolic artificial intelligence, semantic web, knowledge graphs, knowledge representation and reasoning, denotational semantics, and set-theoretic topology. His research is highly cited. He was founding Editor-in-chief of the Semantic Web journal, the leading journal in the field, and is founding Editor-in-chief of the new Neurosymbolic Artificial Intelligence journal, and of the IOS Press book series Studies on the Semantic Web. He is co-author of the W3C Recommendation OWL 2 Primer, and of the book Foundations of Semantic Web Technologies by CRC Press, 2010, which was named as one out of seven Outstanding Academic Titles 2010 in Information and Computer Science by the American Library Association's Choice Magazine, and has translations into German and Chinese. He is author of 5 books, editor of 9 books that provide state-of-the-art overviews on specific topics, and editor of 15 conference proceedings books. He is on the editorial board of several journals and book series and a founding steering committee member of the Neural-Symbolic Learning and Reasoning Association and the Association for Ontology Design and Patterns, and he frequently acts as conference chair in various functions.

• Section I. Foundations of Neuro-Symbolic AI1. Neuro-Symbolic AI. Origins, Evolution, and Future Outlook2. Knowledge Representation in AI3. Evolution of Neural Networks. From Basic Perceptrons to Advanced Deep Learning4. Neural vs. Symbolic Approaches to AI. an Analysis5. Neuro-Symbolic Advantages. Enhanced Generalization via Integrated ArchitecturesSection II. Neuro-symbolic AI Models and Techniques6. Hybrid Models and Integrative Techniques7. Representation Learning in Hybrid Systems8. From Propositionalization to Deep Relational Machines9. Embedding Logic into Neural Networks10. Neuro-Symbolic Toolkit. Using Logic Tensor Networks (LTN) and Related Platforms11. Logic-Driven Learning. Merging Neural Networks with Formal RulesSection III. Applications and Use Cases12. Neuro-Symbolic AI in Natural Language Processing13. FAIR Neuro-Symbolic Pipelines for Transparent Semantic Annotation. A Framework for Structured and Explainable Knowledge Extraction14. Visual Reasoning and Robotics15. Neuro-Symbolic for Scientific Discovery through Physics-Informed Simulation16. Neuro-symbolic AI for Explainable and Interpretable Systems17. Concept based Alignment and Explainability in Neurosymbolic Systems18. Real-World Applications of Neuro-Symbolic AI. Bridging Reasoning and Learning for Intelligent Systems19. Case Studies in Healthcare, Cybersecurity, and EducationSection IV. Challenges, Ethics, and Future Directions20. Positioning This Book Among Existing Titles21. Neurosymbolic Agentic AI. Architectures, Integration Patterns, Applications, Open Challenges and Future Research Directions22. Scalability and Optimization of Hybrid Models23. Ethics, Trust, and Transparency in AI Systems24. Sustainability, Security, and the Road Ahead25. Neuro-Symbolic AI’s Role in Achieving General AI26. Looking Ahead. Neuro-Symbolic AI’s Role in Achieving the long-term goal of human and machine co evolution27. Concluding Chapter