Amy Wu P.L.Eng, PhD

Amy R. Wu is an Associate Professor in the Department of Mechanical and Materials Engineering at Queen’s University and the Mitchell Professor in Bio-inspired Robotics. She is the head of the Biomechanics x Robotics Laboratory (BxRL) and a member of Queen’s Ingenuity Labs Research Institute. Her research interests are at the intersection of biomechanics and robotics with the aim of augmenting legged mobility. Prior to joining Queen’s, she was a postdoctoral researcher in the Biorobotics Laboratory at the Ecole Polytechnique Fédérale de Lausanne (EPFL) in Switzerland and completed her Ph.D. in Mechanical Engineering at the University of Michigan.

Research Interests 

• Human biomechanics: control of balance and locomotion 
• Legged robotics 
• Wearable robotics 
• Mechatronics
• Human-robot interaction 

The Biomechanics x Robotics Laboratory (BxRL) is at the intersection of human biomechanics and robotics with the aim of building better assistive technologies. We are interested in utilizing a first-principles approach to understand the mechanics and energetics of human movement and to apply those principles to robots. Likewise, we will leverage robots to reveal the mechanisms behind human behavior. We are also passionate about using maker-style manufacturing techniques to build impactful, openly available robotic devices for both research and education. We are a member of Ingenuity Labs Research Institute and part of the NSERC CREATE ADVENTOR Program.

Fall: MECH 855 Bio-inspired Robot Locomotion

Winter: MECH 210 Electronic Circuits and Motors for Mechatronics, MREN 303 Mechatronics and Robotics Design III

Select Publications 

• A. N. Best, M. Vlutters and A. R. Wu. Stability strategy restrictions do not elicit compensatory mechanisms during mediolaterally perturbed slow walking. IEEE Transactions on Biomedical Engineering, doi: 10.1109/TBME.2025.3630549.
• A. N. Best and A. R. Wu. The energetics and mechanics of trunk angle during flat and inclined walking. J Exp Biol, vol. 228, no. 17, p. jeb249695, 2025.
• T. K. Byles-Ho, A. N. Best, and A. R. Wu, “Reduction of pendular energy exchange at very slow human walking speeds reveals deviations from simple walking models,” J Exp Biol, vol. 228, no. 12, p. jeb250042, 2025.
  
• A. N. Best and A. R. Wu, "Modified stepping behaviour during outdoor winter walking increases resistance to forward losses of stability," Sci Rep 13, 8432, 2023.
• P. M. Riek and A. R. Wu. "Validation of Inertial Sensors to Evaluate Gait Stability," Sensors 23, 1547, 2023.
• T. Huckell and A. R. Wu. "Improved Zero Step Push Recovery with a Unified Reduced Order Model of Standing Balance" in 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 8321–8327, 2022.
• A. R. Wu, “Human biomechanics perspective on robotics for gait assistance: challenges and potential solutions,” Proceedings of the Royal Society B: Biological Sciences, vol. 288, no. 1956, Aug. 2021. 
• V. Ramachandran, F. Schilling, A. R. Wu, and D. Floreano, "Smart Textiles that Teach: Fabric-Based Haptic Device Improves the Rate of Motor Learning," Adv. Intell. Syst., p. 2100043, 2021. 
• A. N. Best and A. R. Wu, "Upper body and ankle strategies compensate for reduced lateral stability at very slow walking speeds," Proceedings of the Royal Society B: Biological Sciences, vol. 287, no. 1936, p. 20201685, Oct. 2020. 
• A. N. Best, J.-P. Martin, Q. Li, and A. R. Wu, "Stepping behaviour contributes little to balance control against continuous mediolateral trunk perturbations, " J Exp Biol, vol. 222, no. 24, Dec. 2019. 
• A. R. Wu, C. S. Simpson, E. H. F. van Asseldonk, H. van der Kooij, and A. J. Ijspeert, “Mechanics of very slow human walking,” Sci Rep, vol. 9, no. 1, pp. 1–10, Dec. 2019. 
• C. Rognon, V. Ramachandran, A. R. Wu, A. J. Ijspeert, and D. Floreano, "Haptic feedback perception and learning with cable-driven guidance in exosuit teleoperation of a simulated drone," IEEE Trans Haptics, vol. 12, no. 3, pp. 375–385, Jul. 2019. 
• S. Faraji, A. R. Wu, and A. J. Ijspeert, "A simple model of mechanical effects to estimate metabolic cost of human walking," Scientific Reports, vol. 8, no. 1, p. 10998, Jul. 2018. 
• A. R. Wu et al., "An Adaptive Neuromuscular Controller for Assistive Lower-Limb Exoskeletons: A Preliminary Study on Subjects with Spinal Cord Injury," Front Neurorobot, vol. 11, Jun. 2017. 

Ontario Early Researcher Award (2025)

Current Students 

• Junhui Li (PhD)
• Jenny Lee (PhD)
• Eden Hauser-Krupat (MASc)
• Taylor Hambleton (MASc)

Former Students 

• Aaron Best (PhD)
• Timothy Byles-Ho (MASc)
• Paul Riek (MASc)
• Thomas Huckell (MASc)
• Juno Aiken  (Undergraduate, USRA)
• Alex Pettipiece  (Undergraduate, USRA)
• Garrett Mcgrattan (Undergraduate, USRA)
• Heath Danylewich (Undergraduate)
• Ilyès Elotreuch (Mitacs Globalink)
• Bianca Wilks (Undergraduate, WiE)
• Lilah Klassen (Undergraduate, USRA)
  
• Muhammad Abdul (Undergraduate, USRA)
• Eden Hauser-Krupat (Undergraduate, USSRF)
• Noah Brandes (Undergraduate, USSRF)
• Sudipta Das (Undergraduate, MECH 461)
• Sydney Garrah (Undergraduate, USRA, MECH 461) 
• Jyotishka Duttagupta (Mitacs Globalink) 
• Xinran Liu (Mitacs Globalink)
• Timothy Byles-Ho (Undergraduate, MECH 461, Summer) 
• Ray Smyth (Undergraduate, USRA) 
• Nathalie Vilchis (Mitacs Globalink Research Internship) 
• Harriet Chorney (Undergraduate, USRA, MECH 461) 
• Zachary Toupin (Undergraduate, MECH 461) 
• Julian Alexander-Cook (Research)
• Matthew Green (Undergraduate, Thesis) 
• Phoebe Tan Hui Ping (Undergraduate, SWEP) 
• Lucas Melanson (Undergraduate, SWEP) 
• Charley McCann (Undergraduate, Summer) 
• Madeleine Liblong (Undergraduate, Summer) 
• Frances Campbell (Undergraduate, MECH 461) 
• Paul Riek (Undergraduate, MECH 461) 
• Ted Ecclestone (Undergraduate, Thesis) 
• Emily Bugeja (Undergraduate, Summer) 

• Design of infant feeding assistance that maintains the mother-baby dyad. Tasks include:
  • Co-develop a sensor and actuation system for infant supplementary feeding (ideally wearable)
  • Attend co-creation group meetings and consult medical professionals to determine functional/engineering requirements
  • Design and fabricate fluidic control, regulation, and sensing mechanisms, and combine into an integrated wearable system
  • Technically analyze and assess the integrated systems
  • Iterate and adapt designs/prototypes according to medical team experts and experimental results
• Design of a real-time measurement system for fall risk detection during walking across different terrain over long periods of time. Tasks include:
  • Development of a multi-sensor wearable measurement system that provides physiological information about the wearer’s gait and balance. The measurement system will be validated with in-lab motion capture systems to determine the accuracy and reliability of relevant measures.
  • Multi-season outdoor data collection to measure real walking conditions with the measurement system over a long period of time.
  • Development of a balance model that can be validated by the data, and leveraging the model to make a prediction of fall risk and corrective behaviors.
• Design of a trunk exoskeleton that can provide both haptic and active feedback for fall prevention. Tasks include:
  • Incorporating appropriate haptic cues to indicate behavior corrections are needed.
  • Designing a system that can move the trunk to physically correct behaviors that increase fall risk.
  • Leverage the results from the real-time measurement system to design an appropriate controller and correction mechanism.
  • Evaluate the efficacy of the two assistive modes (haptic vs active) with human studies.
  • Validate the trunk exoskeleton with human studies.
• Inclusive Design for Inclusive Futures: This interdisciplinary project between Queen’s (engineering) and York (sociology) seeks to design health and well-being technologies that take into account disciplinary differences across the social sciences and engineering. Applicants should have a technical background in mechatronics or robotics and have a strong interest in interdisciplinary work to understand and mitigate biases in AI, robotics, and healthcare systems. Tasks include:
  • Research trips to York to work with co-supervisors and collaborators
  • Contributing to empirical research that analyzes existing social robots, evaluates designer blind spots, and co-develops frameworks that centre lived experiences, ethical commitments, and real-world clinical needs.
  • Receiving rigorous interdisciplinary preparation, including qualitative research methods, participatory design, critical data studies, ethical assessment of robotic systems, and knowledge-mobilization strategies.
  • Co-authoring publications, presenting at national and international conferences, co-leading prototype development, and helping to design and host major research events.

If interested, please apply via email (amy.wu AT queensu.ca) with the particular project of interest, your CV and a statement that includes your interest and how your background makes you suitable for the project. Please note that due to the volume of emails received, only those selected for an interview will be contacted.

Queen's University invites applications from all qualified individuals. Queen’s is strongly committed to employment equity, diversity and inclusion in the workplace and encourages applications from Black, racialized/visible minority and Indigenous people, women, persons with disabilities, and 2SLGBTQ+ persons.