Emerging Hybrid Models for Neuromorphic AI and Quantum Computing

As artificial intelligence (AI) systems confront the limits of classic computing, emerging models that integrate neuromorphic AI with quantum computing create a compelling path forward. Neuromorphic tools inspire the dynamics of the human brain, while quantum computing promises speedups for certain classes of complex optimization and probabilistic problems. By uniting these models, hybrid neuromorphic-quantum models aim to overcome efficiency and learning constraints that challenge each approach in isolation. Emerging Hybrid Models for Neuromorphic AI and Quantum Computing explores two technological revolutions, AI, powered by intricate networks of artificial neurons, and quantum computing, which harnesses the counterintuitive principles of quantum mechanics. It examines the future of computation within sophisticated hybrid models. Covering topics such as AI, quantum computing, and hybrid models, this book is an excellent resource for software developers, technology developers, business organizations, academicians, researchers, and graduate students.

Dr. Surbhi B. Khan is working in the School of Science, Engineering and Environment at the University of Salford, United Kingdom. She is Project Management Professional Certified from PMP, USA. She is ranked among the top 2% of scientists globally for the second year in a row (2023 and 2024). She is supervising/co-supervising a number of PhDs and research associates. She has published over 250 articles and books in high indexed outlets with her students and colleagues and also has been granted patents from USA. She is also serving as Deputy EIC in TCE letters, Associate editor in IEEE Transactions on Consumer Electronics, HCIS and EAAI journals and Guest editor in many other reputed journals. She is working in KTP Projects Innovate UK and has submitted grants as a CO-PI in HORIZON-EIC-2025-PATHFINDEROPEN. She is also working in external funding from India, and Middle Eastern Institutes. She is a senior member of IEEE and has been serving as session chairs in many IEEE conferences, been invited as a resource person at International Conferences and FDP 39s and has holds honorary positions, providing guidance to universities in pursuit of research and teaching excellence. She is also a member in the Women in Data Science Ambassador. Her research interests are Machine Learning/Deep learning, Data Science in Healthcare and IoT, Text analytics and detection, and Sentiment Analysis.

Shikha Khullar is an accomplished academic and researcher with more than 14 years of experience in computer science and emerging technologies. Her expertise lies in artificial intelligence, computational intelligence, and their applications in areas such as fraud detection, intelligent agriculture, cloud security, federated learning, and blockchain. She has authored and contributed to several international publications and book chapters with reputed publishers including IGI Global and Wiley–Scrivener. Alongside her research, Dr. Khullar is deeply committed to teaching and mentoring, guiding students to apply technology for real-world problem-solving. Her vision emphasizes innovation, sustainability, and bridging the gap between academia and industry.

Udit Mamodiya is an accomplished academician, researcher, and innovator currently serving as Associate Professor and Associate Dean (Research) at Poornima University. With more than a decade of experience in teaching, research, and academic administration, he has made notable contributions to engineering and emerging technology research. His primary research interests include renewable energy systems, smart solar photovoltaic technologies, industrial automation, Internet of Things (IoT), artificial intelligence, and machine learning applications. Dr. Mamodiya has an impressive academic record with numerous research publications in SCI, Scopus, and UGC-CARE indexed journals, along with several book chapters and conference papers in the fields of intelligent systems and sustainable technologies. His work has received hundreds of citations, reflecting the growing impact of his research in renewable energy optimization, AI-driven systems, and smart infrastructure. In addition to his research output, Dr. Mamodiya is actively involved in innovation and technology development, holding multiple patents, design registrations, and copyrights. He has also contributed to academia as an editor, reviewer, and technical committee member for various international journals and conferences. Through his teaching, research leadership, and innovation initiatives, Dr. Mamodiya continues to promote sustainable technology solutions and interdisciplinary research, advancing engineering education and technology-driven societal development. If you want, I can also prepare:

Dr. Manju Lata Joshi , Professor, Poornima University, India holds an M.Tech. and a Doctorate in Computer Science from Banasthali Vidyapith. Her current research interests encompass Artificial Intelligence, Natural Language Processing, Information Retrieval, and Text Mining. With over 17 years of experience in teaching and research, she has published research papers in prestigious journals indexed in the Science Citation Index (SCI) and Scopus, both nationally and internationally. Furthermore, she serve on the review and advisory committees of several refereed journals and conferences. She has contributed to multiple institutions, mentored students, and led research in AI-based document clustering, sentiment analysis, and information retrieval. She is also actively involved in academic advisory boards, technical committees, and conferences.