[hpc-announce] CFP: [AI4S] The 3rd Workshop on Artificial Intelligence and Machine Learning for Scientific Applications at SC'22

Murali Emani m.k.eemani at gmail.com
Tue Jun 28 10:01:49 CDT 2022

[AI4S]: The 3rd Workshop on Artificial Intelligence and Machine Learning
for Scientific Applications

                                         To be held in conjunction with SC22
                              Monday, 14 November 2022, 1:30pm - 5pm CST
                      Kay Bailey Hutchison Convention Center, Dallas, TX,

                                         Website: https://ai4s.github.io/

The purpose of this workshop is to bring together computer scientists and
domain scientists from academia, government, and industry to share recent
advances in the use of AI/ML to various scientific applications, introduce
new scientific application problems to the broader community, and stimulate
tools and infrastructures to support the application of AI/ML in scientific
applications.The workshop will be organized as a series of plenary talks
based on peer-reviewed paper submissions accompanied by keynotes from
distinguished researchers in the area and a panel discussion. We encourage
participation and submissions from universities, industry, and DOE National

Artificial intelligence (AI)/machine learning (ML) is a game-changing
technology that has shown tremendous advantages and improvements in
algorithms, implementation, and applications. We have seen many successful
stories of applying AI/ML to scientific applications, such as predicting
extreme weather events, identifying exoplanets in trillions of sky pixels,
and accelerating numerical solvers in fluid simulation. However, there are
a number of problems remaining to be studied to enhance the usability of
AI/ML to scientific applications. For example, how to systematically and
automatically apply AI/ML to scientific applications? How to incorporate
domain knowledge (e.g., conservation laws, invariants, causality and
symmetries) into AI/ML models? How to make the models interpretable and
robust for HPC? How to make AI/ML more approachable to the HPC community?
Addressing the above problems will bridge the gap between AI/ML and
scientific applications and enable wider employment of AI/ML in HPC.

Call for Papers
We solicit research papers in the following topic areas, but not be limited
- Innovative AI/ML models to analyze, accelerate, or improve performance of
scientific applications in terms of execution time and simulation accuracy;
- Innovative methods to incorporate complex constraints imposed by physical
principles to scientific applications;
- Innovative methods to completely or partially replace first-order
computation with efficient AI/ML models;
- Tools and infrastructure to improve the usability of AI/ML to scientific
- Performance characterization and study on the possibility of using AI/ML
to specific scientific applications;
- Workflow of applying AI/ML to scientific applications;
- Innovative methods to make AI models interpretable and robust for
scientific applications.

Authors are invited to submit manuscripts in English structured as
technical papers up to 6 pages, letter size (8.5in x 11in) and including
figures, tables, and references. Submissions not conforming to these
guidelines may be returned without review. Your paper should be formatted
using IEEE conference format which can be found from

All manuscripts will be peer-reviewed and judged on correctness,
originality, technical strength, and significance, quality of presentation,
and interest and relevance to the workshop attendees. Submitted papers must
represent original unpublished research that is not currently under review
for any other conference or journal. Papers not following these guidelines
will be rejected without review and further action may be taken, including
(but not limited to) notifications sent to the heads of the institutions of
the authors and sponsors of the conference. Submissions received after the
due date, exceeding length limit, or not appropriately structured may also
not be considered. At least one author of an accepted paper must register
for and attend the workshop. Authors may contact the workshop organizers
for more information.

Papers should be submitted electronically at:
https://submissions.supercomputing.org, SC22 Workshop: AI4S'22: Workshop on
Artificial Intelligence and Machine Learning for Scientific Applications".

The final papers are planned to be published through IEEE. Published
proceedings will be included in the IEEE Xplore digital library.

Important Dates:
Submission Deadline: August 2, 2022 (AoE)
Notification of acceptance: September 8, 2022
Camera Ready: September 23, 2022
Workshop: November 14, 2022

Gokcen Kestor, Pacific Northwest National Laboratory
Dong Li, University of California, Merced
Murali Krishna Emani, Argonne National Laboratory

Program Committee
Debbie Bard, Lawrence Berkeley National Laboratory
Kevin Barker, Pacific Northwest National Laboratory
Aparna Chandramowlishwaran, University of California, Irvine
Wenqian Dong, University of California, Merced
Yao Fehlis, AMD Research
Olexandr Isayev, Carnegie Mellon University
Jiawen Liu, Facebook
Brian C Van Essen, Lawrence Livermore National Laboratory
Natalia Vassilieva, Cerebras
Venkatram Vishwanath, Argonne National Laboratory
Laurent White, AMD Research

Best Regards,

More information about the hpc-announce mailing list