Robotics for Cell Manipulation and Characterization - Tapa blanda

Acerca de los autores

Changsheng Dai is currently a professor at Dalian University of Technology. His research focuses on robotic cell manipulation and medical image analysis. Dr. Dai has published over 20 peer-reviewed papers in premium journals and international conference proceedings such as Nature Reviews Urology, IEEE Transactions on Robotics, and IEEE Transactions on Medical Imaging, and has received the Best Paper Award in Automation at 2019 IEEE International Conference on Robotics and Automation (ICRA), Connaught International Scholarship, William Dunbar Memorial Scholarship in Mechanical Engineering, and Weber and Mariano Scholarship in Biomedical Engineering from the University of Toronto. He served as a peer reviewer for several journals such as IEEE Transactions on Robotics and IEEE Robotics and Automation Letters.

Dr. Guanqiao Shan is a Professor at Dalian University of Technology. His research interests include robotic cell manipulation and characterization, automation at micro-nano scales, intelligent control systems, and medical robotics. His research has been recognized by both the robotics and automation society and reproductive medicine society.

Dr. Yu Sun is a Professor at the University of Toronto. He holds a Tier I Canada Research Chair and is the founding Director of Robotic Institute at the University of Toronto. His Advanced Micro and Nanosystems Laboratory specializes in developing innovative robotic and AI technologies for reproductive medicine. His techniques have been applied in clinical centers from multiple countries.

De la contraportada

Robotics for Cell Manipulation and Characterization provides fundamental principles underpinning robotic cell manipulation and characterization, state-of-the-art technical advances in micro/nano robotics, new discoveries of cell biology enabled by robotic systems, and their applications in clinical diagnosis and treatment. This book covers several areas including robotics, control, computer vision, biomedical engineering, and life sciences, using understandable figures and tables to enhance readers’ comprehension and pinpoint challenges and opportunities for biological and biomedical research.