Design and Testing of Digital Microfluidic Biochips - Hardcover

Über die Autorin bzw. den Autor

Chengqing Zong received the Ph.D. degree in computer science from Institute of Computing Techonology, Chinese Academy of Sciences, China in March 1998. He is currently a professor with Institute of Automation, Chinese Academy of Sciences, China. His research interests include natural language processing, machine translation, and cognitive language computing. He has published more than 200 papers in top-tier conferences and journals. He has authored and co-authored six books, including Text Data Mining, which was published with Springer in 2021. He is a member of the Academia Europaea, IEEE Fellow, and ACL Fellow. He is President of the Association for Computational Linguistics (ACL) in 2025 and was President of the Asian Federation of Natural Language Processing (AFNLP) from 2019 to 2021. He won many awards such as the Second Prize of the National Scientific and Technological Progress Award of China, 2015, one of the most prestigious and influential awards in China. Yang Zhao received the Ph.D. degree in pattern recognition and intelligent system from Institute of Automation, Chinese Academy of Sciences, China in 2019. He is currently an associate professor with the State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences. His research interests include machine translation and natural language processing. Yanjun Ma received the Ph.D. degree in computer science from Dublin City University in 2009. He currently serves as the General Manager of Baidu AI Platform & Ecosystem, overseeing the development of the open-source deep learning platform PaddlePaddle. His research focuses on natural language processing and deep learning, which is widely used in Baidu's products. Dr. Yanjun Ma has authored and co-authored over 20 research publications and served as the Area Co-Chair for a number of top international conferences. In 2015, Dr. Yanjun Ma received National Technology Advancement Award.

Von der hinteren Coverseite

This book provides a comprehensive methodology for automated design, test and diagnosis, and use of robust, low-cost, and manufacturable digital microfluidic systems. It focuses on the development of a comprehensive CAD optimization framework for digital microfluidic biochips that unifies different design problems. With the increase in system complexity and integration levels, biochip designers can utilize the design methods described in this book to evaluate different design alternatives, and carry out design-space exploration to obtain the best design point.

• Describes practical design automation tools that address different design problems (e.g., synthesis, droplet routing, control-pin mapping, testing and diagnosis, and error recovery) in a unified manner;
• Applies test pattern generation and error-recovery techniques for digital microfluidics-based biochips;
• Uses real bioassays as evaluation examples, e.g., multiplexed in vitro human physiological fluids diagnostics, PCR, protein crystallization.