Bérénice Mettler, Ph.D.

Founder & CEO

Bérénice Mettler has a lifelong fascination with human movement skills and their reproduction with technology, particularly the contrasts between how movement is controlled and learned in humans and machines. This duality has influenced her career path starting with work on flight control and guidance of agile unmanned vehicles, analyzing human pilot skills, and more recently, understanding and modeling human movement skills to build technologies that augment learning and performance.

Born in Geneva, Switzerland, Bérénice earned a degree in mechanical engineering from the Swiss Federal Institute of Technology (ETH), followed by a PhD from Carnegie Mellon University and postdoctoral work at Massachusetts Institute of Technology (MIT).

From 2006 to 2016, Bérénice was an assistant and then associate professor at the University of Minnesota (UMN), where she founded and led the Interactive Guidance and Control Lab (IGCL). While on sabbatical in 2015, she founded iCueMotion with the mission of building technology to augment human movement learning, transforming how humans train and rehabilitate movement.

Her philosophy is to build tools that leverage movement measurements and feedback and work in harmony with natural human sensory-motor and learning processes to create long-term physical and mental benefits for users and society. Her work with the iCueMotion team leverages her academic experience in modeling, guidance and control, robotics, human factors, and cognitive neurosciences.

Bérénice's research has been recognized with several best paper awards. She has authored close to 100 peer-reviewed papers, including several highly cited publications in the field of unmanned aerial vehicles. She is the recipient of a 2012 NSF Career Award, and in January 2017, she was honored by President Obama and the White House Office of Science and Technology with the Presidential Award for Early Career in Science and Engineering (PECASE).

Research Career Details

While earning her PhD at Carnegie Mellon University, Bérénice performed the first rigorous investigation of small-scale helicopter flight dynamics using system identification tools with the goal of enhancing flight control performance for agile maneuvering. She received a University Award for her contributions to Carnegie Mellon's victory at the 1997 International Aerial Robotics Competition.

As a postdoc and then researcher at MIT from 2001 to 2005, she conducted her own independent research through a NASA grant, which led to contributions on spatial guidance for autonomous flight. These contributions included real-time trajectory planning using spatial value function which encodes behavior as a spatial time-to-go function and enables real-time trajectory optimization in complex environments. Simultaneously, while building on her PhD thesis on helicopter system identification, modeling, and flight control, Bérénice assisted with mentoring Professor Eric Feron's PhD and Masters candidates. This project culminated in the first fully automatic unmanned acrobatic flight.

In 2006, she joined the department of Aerospace Engineering and Mechanics at UMN. Her goal, in the context of founding the Interactive Guidance and Control Lab (IGCL), was to investigate artificial and human spatial guidance and control skills. During her tenure at UMN, she supervised seven PhD students and obtained support for her research from the National Science Foundation (NSF), Army Flight Dynamics Directorate (AFDD), Office of Naval Research (ONR), National Aeronautics and Space Administration (NASA), and the Jet Propulsion Lab.

Bérénice's work at her UMN lab (IGCL) provided her with the opportunity to deepen her understanding of the principles exploited by the human brain to achieve agile performance in complex environments. By applying the concept of spatial value function, she created a mathematical framework for investigating principles that underlie the structure and organization of spatial behavior that can be leveraged for more efficient learning and computing.

Working closely with her students, she applied this framework to both autonomous and human guidance skills in complex spatial environments. Some of the key results include the formalization of the concept of subgoals, their role in abstraction and learning, and how this behavioral structure helps elucidate a system-wide control architecture.

At iCueMotion Bérénice continues to research spatial movement skills, with an emphasis on so-called open motor skills such as tennis or skiing, which involve dynamic interactions with the task or activity environment. She and her team have built a data-driven framework for modeling, assessing, and training movement skills across different domains. This framework combines individual users' data with population-wide data, enabling systemic modeling of the skill acquisition process including the influence of individual factors. Ultimately, these insights can be leveraged for data-driven training.

Bérénice's Google Scholar Profile