Ambarella
Wei (Max) Fang has a diverse work experience in the field of architecture engineering. Wei (Max) started their career in 2013 as a Member of Technical Staff at Ambarella Inc and worked there until 2015. Wei (Max) then progressed to the role of Senior Architecture Engineer from 2015 to 2017, followed by being a Staff Architecture Engineer from 2017 to 2019. From 2019 to 2021, Max served as a Senior Staff Architecture Engineer at Ambarella Inc, and currently, they hold the position of Principal Architecture Engineer since August 2021 at the same company.
Prior to their professional career, Max worked as a Department of ECE Undergraduate Student Tutor at HKUST from September 2010 to December 2010.
Wei (Max) Fang completed their education with the following chronological information:
- From 2011 to 2013, they attended Stanford University and obtained a Master of Science degree in Electrical Engineering.
- From 2007 to 2011, they studied at The Hong Kong University of Science and Technology, where they earned a Bachelor of Engineering (B.Eng.) First Class Honors degree in Electronic and Computer Engineering.
- Between 2004 and 2007, they attended Beijing No.4 High School.
- Lastly, from 2001 to 2004, they studied at Beijing No.8 High School, completing their Middle School education.
Ambarella
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Ambarella, Inc. is engaged in the development of high-definition (HD), ultra HD video compression, image processing and computer vision solutions. Its products are used in a variety of human and computer vision applications, including security camera, advanced driver assistance (ADAS), electronic mirror, drive recorder, driver/cabin monitoring, autonomous driving, and other robotic applications. Its low-power, high-resolution video compression, image processing, and neural network processors and software enables cameras to extract data from high-resolution video streams. It provides driver assistance systems, smart electronic mirrors, drive recorders and autonomous vehicles. Its CVflow architecture supports a variety of computer vision algorithms, including stereo obstacle detection and terrain mapping technology, and allows customers to differentiate their products by porting their own algorithms and neural networks to its CVflow-based chips.