Rate My Professor Norman Hendrich

Dr. Norman Hendrich is a Senior Lecturer in the Department of Informatics at the University of Hamburg (UHH), within the Faculty of Mathematics, Informatics, and Natural Sciences. His work in Computer Science centers on the TAMS group, focusing on Technical Aspects of Multimodal Systems. He received his B.Sc. degree in physics in 1986, M.Sc. degree in physics in 1991, and Ph.D. degree in computer science in 1996 from UHH. His dissertation, published as "Mustererkennung mit Neuronalen Assoziativspeichern" in 1996, addressed pattern recognition using neural associative memories. He also authored the book "Java für Fortgeschrittene" in 1997.

Hendrich's career includes developing the Hades interactive digital systems simulator for VLSI and computer architecture education, which was a finalist for the 1998 European Academic Software Award. He led e-learning initiatives under the ELCH consortium and managed the EU FP6 MING-T project. Since 2009, his research has emphasized software for autonomous robots, particularly dexterous grasping and manipulation with the Shadow hand in EU FP7 HANDLE and Echord HYFLAM projects. He derived precision grasp synergies for eight classes, integrated into the ROS manipulation stack and MoveIt! framework. Current interests encompass tactile sensor design, 3D-printed flexible sensors and circuits, hand-arm teleoperation, reinforcement learning for pushing and grasping, and human-robot collaboration.

Key publications include "Pluck and Play: Self-supervised Exploration of Chordophones for Robotic Playing" (ICRA 2024), "Efficient Human Motion Reconstruction from Monocular Videos with Physical Consistency Loss" (Siggraph Asia 2023), "Multifingered Grasping Based on Multimodal Reinforcement Learning" (ICRA 2023), "Low-Cost Fabrication of Flexible Tactile Sensor Arrays" (HardwareX 2022), and "Topology-Aware Routing of 3D-Printed Circuits" (Additive Manufacturing 2020). His papers earned highly commended awards at CLAWAR 2017 and 2015, best paper at ROBIO 2013, with over 1,500 citations demonstrating impact in robotics.