Artificial Intelligence in Biomaterials Design and Development (Woodhead Publishing Series in Biomaterials) - Softcover

Über die Autorinnen und Autoren

Mohsen Khodadadi Yazdi is an experienced chemical/polymer engineer who received his BSc degree (chemical engineering) from the Ferdowsi University of Mashhad, Iran, followed by a MSc (2010) from the Sharif University of Technology, Tehran, Iran. He received his PhD (2017) in polymer engineering from the University of Tehran, Iran. He is currently a Senior Researcher at the Center of Excellence in Electrochemistry, University of Tehran, Iran. His research interests include smart hydrogel/biopolymers, carbon-based nanomaterial, conducting polymers, and machine learning for utilization in biomedical applications. He has contributed to >20 scientific papers and book chapters.

Payam Zarrintaj is Principal Scientist in the Biomedical and Pharmaceutical Science Department at the University of Montana, Montana, United States. He is an experienced polymer engineer; he received his BSc degree from Amirkabir University of Technology, Iran, followed by a MSc (2013) and PhD (2018) from Tehran University, Iran. His research interests include smart hydrogel/polymers and nanoparticles with well-controlled microstructures and properties for biomedical applications. He has contributed to >90 scientific papers and book chapters.

Dr. Mohammad Reza Saeb received his PhD in 2008 from Amirkabir University of Technology (Iran) and is currently a Professor at the Department of Pharmaceutical Chemistry, Medical University of Gdańsk (Poland). His research focuses on advanced materials and manufacturing processes, including polymer blends, composites, and nanocomposites, with particular emphasis on biomaterials and flame-retardant polymers, as well as the recycling and upcycling of polymer and biowastes. He has authored or co-authored more than 500 articles in high-impact journals and is currently serving as the Editor-in-Chief of Polymers from Renewable Resources, published by SAGE.

Dr. Masoud Mozafari is a Fellow at Lunenfeld Tanenbaum Research Institute, Mount Sinai Health Hospital, University of Toronto. He was previously Assistant Professor and Director of the Bioengineering Lab, at the Nanotechnology and Advanced Materials Department, Materials and Energy Research Center, Cellular and Molecular Research Center, and Department of Tissue Engineering and Regenerative Medicine of the Iran University of Medical Sciences (IUMS), Tehran, Iran. Dr. Mozafari’s research interests range across biomaterials, nanotechnology, and tissue engineering, and he is known for the development of strategies for the treatment of damaged tissues and organs, and controlling biological substances for targeted delivery into the human body. Dr. Mozafari has received several awards, including the Khwarizmi Award and the Julia Polak European Doctorate Award for outstanding translational research contributions to the field of biomaterials. He has also received the WIPO Medal for Inventors from The World Intellectual Property Organization (WIPO), in recognition of his contributions to economic and technological development. Dr. Mozafari is currently working on the editorial board of several journals.

Dr. Sidi A. Bencherif earned a Ph.D. in Chemistry from Carnegie Mellon University in 2009 and is a Senior Researcher at CNRS. A world-renowned expert in biomaterials, he is recognized among the top 2% of scientists worldwide by Stanford University and Elsevier. His research focuses on the design of advanced biomaterials for therapeutic applications, with an emphasis on regenerative medicine, drug delivery, and cancer immunotherapy. Dr. Bencherif’s work bridges cutting-edge materials science with clinical outcomes, addressing key medical challenges by integrating innovative biomaterials into clinical practice.

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Artificial intelligence in Biomaterials Design and Development explores the importance of artificial intelligence, especially machine learning methods, in the development of new biomaterials. Challenges in biomaterials development, such as chemical waste, space and lack of appropriate tools have impeded the rapid design and synthesis of versatile biomaterials. Machine learning enhances the discovery and development process, increasing throughput and reducing time, costs, and wastage. Novel generative models can generate novel molecular structures with desired properties, which make inverse materials design more feasible.

Artificial intelligence in Biomaterials Design and Development offers a much-needed exploration of how AI and machine learning can be utilized for rapid and accurate development of novel biomaterials. This book will be of interest to academics and researchers working in the fields of materials science, machine/deep learning, computational engineering, biomedical engineering, and data science.