[asme-dtm] Workshop on Machine Learning for Computational Design at the International Conference on Machine Learning (ICML) 2022

  • From: Paul Grogan <pgrogan@xxxxxxxxxxx>
  • To: "asme-dtm@xxxxxxxxxxxxx" <asme-dtm@xxxxxxxxxxxxx>
  • Date: Thu, 12 May 2022 21:24:02 +0000

Dear Community Members,

Please see the note below, courtesy of Dr. Mark Fuge, regarding the ICML 2022 
Workshop on Machine Learning for Computational Design .

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Dear Colleagues,


We invite you to participate in the ICML 2022 Workshop on Machine Learning for 
Computational Design (https://mlcompdesign.github.io/). This workshop seeks to 
unify discussions in learning-based methods for computational design across 
disciplines with an emphasis on design for function.  The workshop will be 
highly interactive and should build bridges between academia, industry, and 
practitioners from all backgrounds.


We are soliciting calls for three types of presentations: a) Research poster 
presentations, to be accompanied by brief oral presentations; b) Software 
demos; c) Design demos.  Please indicate for which track you are submitting in 
the title of the submission.


Those interested in presenting in the Research track should submit a 1-4 page 
short paper on their research in the intersection of machine learning and 
computational design.  Research can be in any domain; examples include (and are 
not limited to) mechanical design, web design, biology, materials, molecular 
design, robotics, architecture.  The research can be on any aspect of the 
computational design problem - algorithms for design, design analysis, 
representation learning, model learning, etc. - as long as it is focused on 
learning-based methods.  The submitted paper can be on recently published and 
to-be-published work or ongoing/late-breaking work with preliminary results.


Those interested in presenting in the Software Demos will present software in 
dedicated demo booths at the workshop.  This should be research- or 
industrial-grade software developed by the submitters, that uses machine 
learning algorithms for design.  Submissions should include a 1-2 page 
technical description of their software, including the problem the software 
addresses, a high-level description of the underlying algorithms that power it, 
and a brief video or online demo of the software being used.  We are excited to 
see contributions from any domain!


Those interested in presenting in the Design Demos will present physical or 
virtual artifacts of items designed using machine learning.  If the designed 
object is not suitable to be presented (e.g. if it is a large building or a 
biological specimen), a virtual representation can be presented.  We are 
excited to see designs that span the gamut of art, design, and engineering.  
Interested participants should submit a 1-page description of the item and how 
it was made, along with photos or other visual documentation.


Please take note of the following timeline and deadlines:


June 4th - Submission deadline, to be presented as fast-forwards and posters

June 6th - Notification of acceptance

June 17th - Poster slides and fast-forward talk video uploads due for accepted 
submission (for poster track)

July 22nd/23rd - Date of the workshop


Applicants should submit their paper on 
https://cmt3.research.microsoft.com/MLCD2022/

We look forward to reading your papers and seeing you at ICML 2022 in Baltimore!


Sincerely, The Organizers

Lydia Chilton (Columbia University)

Rafael Gomez-Bombarelli (MIT)

Wengong Jin (Broad Institute)

Vladimir Kim (Adobe)

Caitlin Mueller (MIT)

Daniel Ritchie (Brown University)

Andrew Spielberg (Harvard University)


Mark Fuge
Associate Professor of Mechanical Engineering
Affiliate Faculty, Institute for Systems Research
Member, Maryland Robotics Center
Member, Human-Computer Interaction Lab
University of Maryland
2172 Glenn L. Martin Hall, College Park, MD 20742
(301) 405-2558 | http://ideal.umd.edu
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--
Paul T. Grogan, Ph.D.

Assistant Professor
School of Systems and Enterprises
Stevens Institute of Technology

Secretary, ASME Design Theory and Methodology (DTM)
Secretary, Council of Engineering Systems Universities (CESUN)

https://www.name-coach.com/paul-grogan

E: pgrogan@xxxxxxxxxxx<mailto:pgrogan@xxxxxxxxxxx> | O: (201) 216-5378 (Babbio 
Center 517) | W: code-lab.org<https://www.code-lab.org/>

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