Behzad Razavi is an award-winning teacher, researcher, and author. He holds a Ph.D. degree from Stanford University and has been Professor of Electrical Engineering at University of California, Los Angeles, since 1996. His current research encompasses RF and wireless design, broadband data communication circuits, phase-locking phenomena, and data converter design.

Professor Razavi's research and teaching have garnered numerous awards. He received the Beatrice Winner Award for Editorial Excellence at the 1994 ISSCC, the best paper award at the 1994 European Solid-State Circuits Conference, the best panel award at the 1995 and 1997 ISSCC, the TRW Innovative Teaching Award in 1997, and the best paper award at the IEEE Custom Integrated Circuits Conference in 1998. He was the co-recipient of both the Hack Kilby Outstanding Student Paper Award and the Beatrice Winner Award for Editorial Excellence at teh 2001. International Solid-State Circuits conference (ISSCC). He received the Lockheed Martin Excellence in Teaching Award in 2006 and the UCLA Faculty Senate Teaching Award in 2007. He was also recognized as one of the top ten authors in the fifty-year history of ISSCC.

Professor Razavi is an IEEE Distinguished Lecturer, a Fellow of IEEE, and the author of a number of books, including Principles of Data Conversion System Design, RF Microelectronics (translated to Chinese and Japanese), Design of Analog CMOS Integrated Circuits (translated to Chinese and Japanese), Design of Integrated Circuits for Optical communications, and Fundamentals of Microelectronics. he is also the editor of Monolithic Phase-Locked Loops and Clock recovery circuits and Phase-Locking in High-Performance Systems.

Designed to build a strong foundation in both design and analysis of electronic circuits, Razavi teaches conceptual understanding and mastery of the material by using modern examples to motivate and prepare students for advanced courses and their careers. Razavi's unique problem-solving framework enables students to deconstruct complex problems into components that they are familiar with which builds the confidence and intuitive skills needed for success.