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Announcing the NSF-DARE Conference on Computational Modeling for Neurorehabilitation
March 3-4, 2022 @ University of Southern California
Los Angeles, CA, USA
Plus 3 Pre-Conference Zoom Seminars
https://dare2023.usc.edu/
March 3-4, 2022 @ University of Southern California
Los Angeles, CA, USA
Plus 3 Pre-Conference Zoom Seminars
https://dare2023.usc.edu/
Join us the first week in March for a conference focused on the intersection of computational modeling and neurorehabilitation. Hosted by the University of Southern California and the University of Washington with support from the NSF, this conference has been designed to critically discuss two questions:
1. What can computational modeling do for neurorehabilitation?
2. How can computational modeling improve neurorehabilitation?
How can you participate?
Scientific contribution:
Submit a brief abstract (to be considered for both oral or poster sessions)- See instructions here https://sites.usc.edu/dare2023/abstract-submission/.
Due Date January 15th.
Since attendance at the workshop is limited, individuals who are selected for a 10-minute podium or poster presentation will be given priority for registration.
Apply to be a DARE2023 Fellow
A main goal of the conference is to catalyze a diverse community of Fellows that come together addressing the two key questions above. They will receive travel assistance and be invited to co-write a Position Paper.
Please see instructions here https://sites.usc.edu/dare2023/abstract-submission/.
Want to learn more?
This conference will bring together experts and trainees from around the world to discuss critical questions, challenges, and opportunities at the intersection of computational modeling and neurorehabilitation. Our mission is to identify the gaps and opportunities for using computational modeling and device design to understand, optimize, and improve neurorehabilitation. We will focus on four areas of impact, as described in https://dare2023.usc.edu/:
| 1. Modeling adaptation and plasticity: How do we leverage modeling to understand neuroplasticity? How can the integration of novel imaging technologies, machine learning, and physiology-based models be used to predict and understand the complex processes underlying beneficial neuroplasticity and adaptation that support learning and recovery? 2. Modeling for personalization: A central challenge in rehabilitation is that each individual’s de- velopmental, injury, treatment response, and long-term recovery trajectory is unique. However, it is necessary to first determine the degree of personalization required to optimize and support development and recovery in practice. How can we leverage large, diverse, and real-time datasets to support an appropriate and effective level of personalization to optimize outcomes? 3. Modeling human-device interactions: Interconnected human-centered technology has become a critical part of function and rehabilitation – including development, acute care, training, and activities of daily living. However, neurorehabilitation requires new engineering approaches to support the design, interaction, integration and control of devices to support development and recovery. How can modeling inform and accelerate this development? 4. Modeling in the wild: Rehabilitation does not end at the clinic’s door – it extends into and is meant to serve our daily lives and practices. How can modeling support rehabilitation in unstructured human environments to offer actionable insights to support and promote recovery? How can modeling identify and dismantle environmental and societal barriers that cause disability to support and enhance activities of daily living? |
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