Prof. Kenji Suzuki

University of Chicago, United States of America

Kenji Suzuki received his Ph.D. degree in information engineering from Nagoya University in 2001. From 1993 to 2001, he worked at Hitachi Medical Corporation, and then Aichi Prefectural University as faculty. In 2001, he joined Department of Radiology at University of Chicago. Since 2006, he has been Assistant Professor of Radiology, Medical Physics, and Cancer Research Center there. Dr. Suzuki’ research interests include computer-aided diagnosis and machine learning. He has published 220 papers (including 88 peer-reviewed journal papers). He has been serving as the Editor-in-Chief and an Associate Editor of 23 leading international journals including Medical Physics, International Journal of Biomedical Imaging, and Academic Radiology. He has received Paul Hodges Award, three RSNA Certificate of Merit Awards and Research Trainee Prize, Cancer Research Foundation Young Investigator Award, SPIE Honorable Mention Poster Award, IEEE Outstanding Member Award, and Kurt Rossmann Excellence in Teaching Award. He has been a Senior Member of IEEE since 2004.

Fields of Research

Experience

Edited Books

  • Artificial Neural Networks - Industrial and Control Engineering Applications

    Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications. The purpose of this book is to provide recent advances of artificial neural networks in industrial and control engineering applications. The book begins with a review of applications of artificial neural networks in textile industries. Particular applications in textile industries follow. Parts continue with applications in materials science and industry such as material identification, and estimation of material property and state, food industry such as meat, electric and power industry such as batteries and power systems, mechanical engineering such as engines and machines, and control and robotic engineering such as system control and identification, fault diagnosis systems, and robot manipulation. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks in industrial and control engineering areas. The target audience includes professors and students in engineering schools, and researchers and engineers in industries.

  • Artificial Neural Networks - Methodological Advances and Biomedical Applications

    Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications in various areas. The purpose of this book is to provide recent advances of artificial neural networks in biomedical applications. The book begins with fundamentals of artificial neural networks, which cover an introduction, design, and optimization. Advanced architectures for biomedical applications, which offer improved performance and desirable properties, follow. Parts continue with biological applications such as gene, plant biology, and stem cell, medical applications such as skin diseases, sclerosis, anesthesia, and physiotherapy, and clinical and other applications such as clinical outcome, telecare, and pre-med student failure prediction. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks in biomedical areas. The target audience includes professors and students in engineering and medical schools, researchers and engineers in biomedical industries, medical doctors, and healthcare professionals.

  • Artificial Neural Networks - Architectures and Applications

    Artificial neural networks may probably be the single most successful technology in the last two decades which has been widely used in a large variety of applications. The purpose of this book is to provide recent advances of architectures, methodologies, and applications of artificial neural networks. The book consists of two parts: the architecture part covers architectures, design, optimization, and analysis of artificial neural networks; the applications part covers applications of artificial neural networks in a wide range of areas including biomedical, industrial, physics, and financial applications. Thus, this book will be a fundamental source of recent advances and applications of artificial neural networks. The target audience of this book includes college and graduate students, and engineers in companies.

Publications