CLS welcomes Wenqi Hu and Wieland Brendel as associate faculty members. Both are new junior group leaders at the Max Planck Institute for Intelligent Systems.
Dr. Wenqi Hu (shown left) founded his new independent group on "Bioinspired Autonomous Miniature Robots" at MPI-IS as of June 1, 2022. He and his future team will be supported by Cyber Valley, Europe's largest AI research consortium in the field of robotics, machine learning, and computer vision.
The group will focus on two areas. Firstly, on developing fabrication and integration methods of components made of various smart materials. Secondly, based on these newly developed fabrication methods, Wenqi Hu plans to investigate how to design bioinspired miniature soft machines, ranging from a few millimeters in size to tens of centimeters. The aim is to make such small untethered robots autonomous.
Wenqi Hu received his Bachelor's degree in 2009 specializing in microelectronics. In 2014 he received his Ph.D. from the Electrical Engineering Department at the University of Hawaii at Manoa. In July 2014, Hu joined the Max Planck Institute for Intelligent Systems and the Physical Intelligence Department. His work has been widely cited and featured in the popular press ( including New York Times, the Wall Street Journal, Galileo TV, Der Spiegel, Nature News, and IEEE Spectrum Magazine). He has received many awards for his scientific contributions, including Best Conference Paper Award Finalist at ICRA 2012, the Humboldt Postdoctoral Research Fellowship between 2015 and 2018, the Best Paper Award at Robotics Science and Systems 2019 (RSS), and the Günter Petzow Prize in 2018. You can read more about Wenqi Hu's appointment here.
Dr. Wieland Brendel (shown right) joined MPI-IS on May 1, 2022 as head of the new independent Max Planck Research Group "Robust Machine Learning".
Wieland’s research on “Towards Machines that See the World like Humans” ties together adversarial machine learning, disentanglement, interpretability, self-supervised learning, and theoretical approaches like nonlinear Independent Component Analysis to develop theoretically grounded yet empirically successful visual representation learning techniques that can uncover the underlying structure of our visual world and close the gap between human and machine vision.
Wieland Brendel received his Diploma in physics from the University of Regensburg (2010) and his Ph.D. in computational neuroscience from the École normale supérieure in Paris (2014). He joined the University of Tübingen as a postdoctoral researcher in the group of Matthias Bethge, became a Principal Investigator and Team Lead in the Tübingen AI Center (2018) and has been an Emmy Noether Group Leader for Robust Machine Learning since 2020. Besides working on robust, generalizable and interpretable machine vision, he co-founded a nationwide school competition and a machine learning startup focused on visual quality control. You can read more about Wieland Brendel's appointment here.