Yue Hu

Yue Hu is an Assistant Professor at the Department of Mechanical and Mechatronics Engineering at the University of Waterloo, where she directs the Active & Interactive Robotics Lab. Prior to joining The University of Waterloo, Yue had a largely international experience. She obtained her master's degree in Advanced Robotics from the University of Genova, Italy, and Ecole Centrale de Nantes, France, in 2013. She then carried out her PhD in robotics at Heidelberg University, Germany, receiving her degree in 2017. She was a postdoc first at Heidelberg University, then at the Italian Institute of Technology (IIT), in Italy. Between 2018 and 2021 she was first a JSPS (Japan Society for the Promotion of Science) fellow at the National Institute of Advanced Industrial Science and Technologies (AIST) in Japan, and then an Assistant Professor at the Department of Mechanical Systems Engineering, Tokyo University of Agriculture and Technology (TUAT). Yue is one of the co-chairs of the IEEE-RAS Technical Committee on Model-based Optimization for Robotics, an Associate Vice-President of the IEEE-RAS Members Activities Board (MAB), and an advisor for the organization Women in AI & Robotics. Her research interests include physical-social human-robot interaction, collaborative robots, humanoid robots, and optimal control.

• Robotics
• Collaborative robots
• Human-robot interaction
• Human Motion Analysis
• Humanoid Robots
• Optimal control

• 2017, Doctorate Computer science (Dr. rer. nat.), Heidelberg University, Germany
• 2013, Master of Science European Master in Advanced Robotics, Ecole Centrale de Nantes, University of Genova, France, Italy
• 2011, Bachelor's Electronics Engineering, University of Genova, Italy

• MTE 544 - Autonomous Mobile Robots
  • Taught in 2024

* Only courses taught in the past 5 years are displayed.

• Tang C., Feng Y., and Hu Y., RoboSync: Efficient Real-Time Operating System for Social Robots with Customizable Behaviour, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 127, 204-216, Canada, 2024.
• Abdulazeem N., and Hu Y., The Impact of Robots Facial Emotional Expressions on Light Physical Exercises, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 127, 216-229, Canada, 2024.
• Wensing P.M., Posa M., Hu Y., Escande A., Mansard N., and Prete A.D., Optimization-Based Control for Dynamic Legged Robots, IEEE Transactions on Robotics, Volume 40, 43-63, United States, 2024.
• Hu Y., Abe N., Benallegue M., Yamanobe N., Venture G., and Yoshida E., Toward Active Physical Human-Robot Interaction: Quantifying the Human State During Interactions, IEEE Transactions on Human-Machine Systems, Volume 52, 367-378, Japan, 2022.
• Yamamoto M., Hu Y., Coronado E., and Venture G., Impression evaluation of robot's behavior when assisting human in a cooking task, 2021 30th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2021, 743-748, Japan, 2021.
• Hu Y., Benallegue M., Venture G., and Yoshida E., Interact with Me: An Exploratory Study on Interaction Factors for Active Physical Human-Robot Interaction, IEEE Robotics and Automation Letters, Volume 5, 6764-6771, Japan, 2020.
• Romualdi G., Dafarra S., Hu Y., Ramadoss P., Chavez F.J.A., Traversaro S., and Pucci D., A Benchmarking of DCM-Based Architectures for Position, Velocity and Torque-Controlled Humanoid Robots, International Journal of Humanoid Robotics, Volume 17, Italy, 2020.
• Elobaid M., Hu Y., Romualdi G., Dafarra S., Babic J., and Pucci D., Telexistence and teleoperation for walking humanoid robots, Advances in Intelligent Systems and Computing, Volume 127, 1106-1121, Italy, 2020.
• Romualdi G., Dafarra S., Hu Y., and Pucci D., A Benchmarking of DCM Based Architectures for Position and Velocity Controlled Walking of Humanoid Robots, IEEE-RAS International Conference on Humanoid Robots, Volume 127, 966-973, Italy, 2019.
• Clever D., Hu Y., and Mombaur K., Humanoid gait generation in complex environments based on template models and optimality principles learned from human beings, International Journal of Robotics Research, Volume 37, 1184-1204, Germany, 2018.

• Researchers awarded funding for cybersecurity innovations
• Researchers make final of robotics innovation competition
• Seven researchers receive Graham Seed Fund awards
• Faculty researchers awarded $900K from government