Prof. Rosendo is an Assistant Teaching Professor responsible for courses where students combine theoretical components of robotics to a hardware. He was an Assistant Professor at ShanghaiTech University, where he created syllabi for two courses and taught them for over four years. His courses combine theory and applications, and it is quite common for students to develop a hardware to instantiate the theoretical knowledge seen in class. While in China he organized outreach activities, teaching Scratch programming to children from low-income neighborhoods in Shanghai. His research/MQPs combine machine learning algorithms and legged robots/manipulators to create robots capable of learning while interacting with their environment. Beyond software implementations to hardware, he believes that truly intelligent robotic behavior emerges from well designed structures, easing the computational burden of controlling algorithms. He focuses on the mechanical/biomimetic development of robots and soft robots, and on the application of Bayesian learning (Gaussian Processes and Bayesian Neural Networks) to efficiently search morphological and control parameters for soft manipulators and legged/whegged robots. He received the 2019 National Natural Science Foundation of China Grant, the 2019 Young Oriental Talent Grant, and the 2021 Shanghai Young Talent Award. He published over 45 peer-reviewed papers with over 820 citations, and has an Erdos number of 5.