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Zhan Fan Quek has a wealth of experience in robotics research and design. Zhan Fan began their career in 2012 as a PhD student at Stanford University, specializing in mechanical design, controls, haptics, and human-machine interface. In 2015, they interned at Tactical Haptics, where they designed haptic feedback using tactile skin stretch for game controllers and implemented infra-camera-based position tracking of game controllers. From 2015 to 2020, they worked as a Research Scientist at the Singapore Institute of Manufacturing Technology, where they designed and controlled robotic manipulators and mobile robotic platforms. In 2020, they were appointed Chief Technical Officer at Transforma Robotics. Most recently, in 2021, they began working as a Senior Robotics Research Scientist at Flexiv Ltd.

Zhan Fan Quek obtained a Bachelor of Science (B.S.) in Mechanical Engineering from the University of Illinois Urbana-Champaign in 2009. Zhan Fan then went on to receive a Master's degree in Mechanical Engineering from Stanford University in 2012. Zhan Fan completed their education in 2015 when they earned a Doctor of Philosophy (Ph.D.) in Mechanical Engineering from Stanford University. In addition, they have obtained various certifications from Coursera, including Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning (2019), Convolutional Neural Networks (2018), Robotics: Computational Motion Planning (2017), Robotics: Aerial Robotics (2017), and Neural Networks and Deep Learning (2017).