[Opensim-announcement] Participate in a Virtual Workshop and OpenSim Challenge

[Jennifer Hicks]

*Apply for the Next Virtual Workshop for Advanced OpenSim Users*
*Deadline to Apply: September 17, 2018*
*Workshop Dates: October 22-26, 2018*
We are pleased to announce a Virtual workshop will take place over the
course of one week in October. The goal of the workshop is to accelerate
the research projects of OpenSim community members. Participants will work
on their projects, with support and advice from the Stanford OpenSim team
and each other. The event will span one week, including several video
conference meetings, along with a daily forum and chat support. It is
expected that participants have already begun to use OpenSim for their
project. Small teams (2-3) of applicants, working on the same project, are
particularly encouraged. Read more and apply
<http://opensim.stanford.edu/support/event_details.php?id=204&title=Virtual-Workshop-for-Advanced-OpenSim-Users>
.

*Participate in a Machine Learning Challenge with OpenSim*

*Entries Due: September 15, 2018*Łukasz Kidziński, a Postdoctoral Fellow at
Stanford University, has organized a challenge to use reinforcement
learning approaches to develop a controller that enables a human model with
a prosthetic leg to walk and run. Based on the OpenSim platform, this
challenge is one of eight selected to be part of the Neural Information
Processing Systems (NIPS) 2018 Competition Track.

Participants are provided with a physiologically based human
musculoskeletal model, the OpenSim simulation environment, and datasets of
normal gait kinematics. The goal is to match the requested velocity vector,
which changes in real time. Round 1 of the challenge ends on September 15.

Details on how to participate, including information on free resources to
get started, are available at the NIPS 2018: AI for Prosthetics Challenge
<https://www.crowdai.org/challenges/nips-2018-ai-for-prosthetics-challenge>
website.
You can learn more about reinforcement learning and the challenge in our
recent webinar, Robust Control Strategies for Musculoskeletal Models Using
Deep Reinforcement Learning <https://www.youtube.com/watch?v=M2D5xSSxshE>.

-- 
*Jennifer Hicks, Ph.D.*
Director of Data Science | Mobilize Center <http://mobilize.stanford.edu>
Associate Director | NCSRR
<http://www.stanford.edu/group/opensim/about/index.html>
R&D Manager | OpenSim <http://opensim.stanford.edu/>
Stanford University
650-498-4403 | jenhicks at stanford.edu
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