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Early Career Professor Award for Research with Intuitive Cobots
Aug 16 2022
Stefanos Nikolaidis has received the Agilent 2022 Early Career Professor Award for his focus on developing next-generation intuitive, cobots which can augment and enhance human capabilities with superior strength, accuracy and precision as well as data capabilities.
Assistant Professor of Computer Science at the University of Southern California, USC Viterbi School of Engineering, Dr Nikoladis leads the Interactive and Collaborative Autonomous Robotics Systems (ICAROS) lab which has a focus on technologies that enable cobots to interact robustly with users in unconstrained and dynamic environments.
“We are thrilled that Professor Nikolaidis has been recognized with the 2022 Agilent Early Career Professor Award, placing him as the preeminent early career faculty in the world in this area,” said Yannis C. Yortsos, Dean of the USC Viterbi School of Engineering. “We are not surprised with this selection given Professor Nikolaidis’ expertise and accomplishments in AI and robotics and how these will help advance manufacturing in today’s rapidly changing technology landscape. Support from this award will allow him to develop his research program further and to explore new and exciting applications of AI and machine vision technologies.”
“Agilent is excited to leverage the prestigious Agilent Early Career Professor Award to support the development of intuitive collaborative robot technologies,” said Dr. Nahid Chalyavi, Associate Vice President of University Relations and External Research at Agilent. “The scientific advances will boost Agilent’s manufacturing capabilities and bring future innovations to our analytical instruments and lab automation equipment.”
The focus of this years award was determined by Dr Chong Wing Jung, Associate Director of University Relations and External Research at Agilent. The Award is an annual program that recognises and supports promising research from professors who, early in their careers, show outstanding potential for future research in areas of importance to scientific industry communities.
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