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Alex Lidow CEO and Co-founder, Efficient Power Conversion Corporation 首席执行官兼联合创始人，美国宜普电源转换公司 |
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个人简介 / Biography Alex Lidow is CEO and co-founder of Efficient Power Conversion Corporation (EPC). Since 1977, Dr. Lidow has been dedicated to making power conversion more efficient upon the belief that this will reduce the harm to our environment and increase the global standard of living. Prior to founding EPC, Dr. Lidow was CEO of International Rectifier Corporation for 12 years. A co-inventor of the HEXFET power MOSFET, Dr. Lidow holds many patents in power semiconductor technology including basic patents in power MOSFETs as well as in gallium nitride transistors and integrated circuits. Dr. Lidow has authored numerous publications on related subjects, including industry's first textbook on “GaN Transistors for Efficient Power Conversion (2012, Wiley & Sons), with its latest updated 3rd Edition being published in October 2019. He has also authored numerous peer reviewed publications on related subjects, and received the 2015 SEMI Award for North America for the commercialization of more efficient power devices. Dr. Lidow has been inducted into the IEEE International Symposium on Power Semiconductor Devices and ICs (ISPSD) Hall of Fame 2019 in May 2019 for his contributions to advancing power semiconductor technology. Dr. Lidow received his Bachelor of Science in Applied Physics from Caltech in 1975, and a Ph.D. in Applied Physics from Stanford University in 1977 as a Hertz Foundation Fellow. 摘要 / Abstract GaN power devices, discrete transistors and integrated circuits, have been in production for over 10 years and have made significant inroads in many applications that benefit from the smaller size and the faster switching speed. These devices are several times smaller than their aging silicon MOSFET ancestors and, largely as a result of this size advantage, have also become comparatively less costly to produce. Now GaN devices have found volume applications in cars. Lidar (Light Detection and Ranging) and 48 V power distribution are two key examples that we will discuss. |
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