Join us in person, or online for a talk by Prof. Eiichi Yoshida from Tokyo University of Science. 

Link to Talk

Abstract: Recent advent of artificial intelligence and the rapid progress on motion capacity of humanoid robots are bringing a strong attention expecting industrial and social applications. Despite their highly dynamic motion ability, humanoid robots need further improvements in motions involving contact with their body. We humans generate such contact-rich motions with ease while solving the complex problem of combined discrete contact sequence and continuous dynamic motions is extremely hard. In this talk, I will present ongoing research to address the following challenges: collecting whole-body contact motion data from humans, learning behaviors from those data and synthesizing multi-contact humanoid motions. 

Biography: Prof. Eiichi Yoshida is a Professor at the Tokyo University of Science since 2022. He received PhD. degree from the Graduate School of Engineering, the University of Tokyo in 1996. He then joined the National Institute of Advanced Industrial Science and Technology (AIST), Japan, and served as Co-Director of AIST-CNRS Joint Robotics Laboratory from 2004 to 2021, at LAAS-CNRS, Toulouse, France and AIST, Japan. He is a Fellow of IEEE and received awards including Best Paper Award in Advanced Robotics Journal, and the honor of a national medal from the French Government. His research interests include humanoid robotics, human modeling, and task and motion planning for robots. 

Title:
Physical AI and Intelligent Systems: Research Infrastructure and Collaborative Opportunities at the ACIS Laboratory

Abstract:
Artificial Intelligence has rapidly evolved in the digital world, yet its integration into the physical world, for example to robustly execute robots and autonomous systems, demands advanced scientific and technological insights into complex, real-world systems. This presentation highlights the capabilities and collaborative potential of the Advanced Control and Intelligent Systems (ACIS) laboratory at the University of Victoria.

ACIS@UVic operates across three specialized divisions:
•    Robotics and Autonomous Systems: Driving innovations in autonomous mobility, unmanned aerial systems (UAS), and complex field robotics.
•    Physical AI: Bridging the gap between machine learning and physical dynamics, focusing on hardware-in-the-loop validation, human-centric settings such as XR and HRC technologies.
•    Intelligent Systems: Delivering data-driven and AI-powered solutions for diagnosis and prognosis tools, operations research, and complex scheduling problems.

In this talk, Dr. Najjaran will demonstrate the core strengths in training HQP, experimental facilities, and mastering the process of building, curating, and structuring high-fidelity datasets specifically for physical AI applications. By showcasing the lab's current portfolio of AI-driven research, this session aims to identify strategic, high-impact research synergies and foster collaborative partnerships.
 

Bio:
Dr. Homayoun Najjaran is a Professor in the Faculty of Engineering and Computer Science at the University of Victoria, where he serves as the Principal Investigator (PI) of the Advanced Control and Intelligent Systems (ACIS) laboratory. His research and teaching focus on the analysis and design of mechatronics, control systems, and applied artificial intelligence, with broad applications in industrial automation, robotics, and autonomous systems. Together with his students, he has published over 200 articles dedicated to ensuring the safe and robust operation of autonomous systems in industrial settings. Dr. Najjaran is a registered Professional Engineer (P.Eng.), a Fellow of the CSME, and the CEO of Cognia AI, a company providing AI-powered solutions and services to industry.

Title:
From Arctic Defence to the Golf Course: Human Technology Teaming to Improve Performance

Abstract:
This presentation examines how human–technology teaming can be optimized to improve performance by comparing work across both highstakes and everyday domains. Within maritime and arctic defence, it highlights key challenges in human–automation interaction, including trust, reliance, workload, and maintaining the human “in-the-loop,” and demonstrates how design choices influence these factors. Extending these principles to golf, the work illustrates how technology use shapes confidence and training practices..

Bio:
Dr. Heather Neyedli is the PI of the Cognitive and Motor Performance Lab at the School of Health and Human Performance, Dalhousie University. Her work spans the areas of Kinesiology, Psychology/Neuroscience, and Engineering. Her research in human–technology interaction centers on improving how people interact with AI, automated systems, and other technology, with a focus on the use of technology in military and sport settings. She also has a research stream that focuses on how humans make decisions and plan actions. This includes understanding how humans process information, adapt their movements, and respond to feedback when interacting with their environment.

Join us in person (McGill Engine Room, Montreal, QC), or online for a talk by Dr. Amy LaViers, Director of the Robotics, Automation, and Dance (RAD) Lab. 

Virtual Meeting

Amy LaViers, Director, The RAD Lab (she/ her)

Amy LaViers works at the intersection of robotics and dance and is a pioneer in the field she named: choreobotics. Her writing, choreography, and machine designs have been presented internationally in both engineering and arts venues, including Nature, Robotics and Autonomous Systems, the Oxford Handbook of Improvisation in Dance, MIT Press, Merce Cunningham's studios, Joe's Pub at the Public Theater, and the Performance Arcade. Her teaching has been recognized on the University of Illinois at Urbana-Champaign's List of Teachers Ranked as Excellent by Their Students with Outstanding distinction, and she is a recipient of DARPA's Young Faculty Award and Director's Fellowship. Her work has been featured in media outlets like The New York Times, Wired, and Dance Magazine. She lives in Philadelphia where she directs the Robotics, Automation, and Dance (RAD) Lab, a non-profit for artmaking, education, and research. 

Choreobotics, Movemes, and a Periodic Table for Choreography

Can a human imitate an octopus? Can a bee mimic a centipede? Can a quadruped mirror a biped? When do two bodies in motion do the same thins? Moving robots out of factories requires that we consider the ability of a body's movement to communicate, express, or otherwise encode meaning. This new context poignantly demonstrates how dance is an essential body of knowledge for robotic research: chemists create compounds, aided by a systematic organization of molecules; musicians make instruments like a cello and glute perform similar actions, bolstered by shared notation. Likewise, dancers take disparate bodies, people with differing bone structures and musculatures, and create coordinated group action in a novel motion style that serves a single expressive goal. Artist-engineer teams in the RAD Lab use movement notation (with the idea of "movemes" as the basic unit) as a basis for projects in robotics, AI and artmaking. The talk presents several projects while grappling with the impossibility of dancing in unison and positing this phenomenon as a fundamental act that forms the basis of embodied communication.