Dynamics AI: Data-Driven Science & Engineering Seminar Series

University of Washington

Join us for our ongoing Data-Driven Science & Engineering Seminar Series organized by the AI Institute in Dynamic Systems. Visit our website to sign up for the seminar mailing list to receive future announcements and to view recordings from past events!

ICICLE Seminar Series featuring Professor Laura Schmidt and Dr. Amarnath Gupta

Zoom webinar

The ICICLE Seminar Series is happy to announce the next set of speakers for June 13th, 2024: Professor Laura Schmidt from UCSF and Dr. Amarnath Gupta from the San Diego Supercomputer Center will be joining us to talk about NSF Convergence  Accelerator Track J Award entitled NOURISH, the Network Of User-Engaged Researchers building Interdisciplinary Scientific Continue reading "ICICLE Seminar Series featuring Professor Laura Schmidt and Dr. Amarnath Gupta"

Workshop | Machine Learning for Science & Engineering

University of Washington

Physics-informed Machine Learning (ML) continues to emerge as a leading paradigm integrating artificial intelligence (AI) with engineering dynamic systems. This approach provides new capabilities in real-time sensing, learning, decision-making, and predictions that are ethical, efficient, reliable, safe, and imbued with uncertainty quantification. The foundations of physics-informed ML are rooted in four key disciplines: (i) controlContinue reading "Workshop | Machine Learning for Science & Engineering"

AI for Agriculture Summit: A Visioning Conference

Washington, D.C.

Envision How AI Can Tackle Critical Global Challenges in Ag There is a pressing need for agricultural innovation to meet the demands of a growing global population amidst challenging environmental conditions. Attendees at the AI for Agriculture Summit will help develop a long-term technical vision and implementation strategy for leveraging agricultural AI advancements, starting withContinue reading "AI for Agriculture Summit: A Visioning Conference"

Workshop on Knowledge-Guided ML (KGML2024)

McNamara Alumni Center, University of Minnesota Twin Cities 200 Oak Street SE, Minneapolis, MN, United States

A Framework for Accelerating Scientific Discovery Explore the depth and diversity of research methodologies being explored in knowledge-guided machine learning (KGML) for a wide range of scientific applications, as well as the gaps in the current state of KGML research providing novel opportunities to advance AI foundations while accelerating discoveries in problems of high societal relevance.

ICICLE & OSU CSE Distinguished Seminar featuring Dr. Dan Stanzione

We invite you to join us for a joint ICICLE & OSU CSE Distinguished Seminar Series on Thursday, August 22 at 11AM EST featuring Dr. Dan Stanzione, Associate Vice President for Research at The University of Texas at Austin and Executive Director of the Texas Advanced Computing Center (TACC). He will provide an overview ofContinue reading "ICICLE & OSU CSE Distinguished Seminar featuring Dr. Dan Stanzione"

Machine Learning for Cyber-Agricultural Systems (MLCAS 2024) Workshop

Nebraska Innovation Campus 2021 Transformation Dr., Lincoln, NE, United States

During this workshop, awards for the MLCAS Corn Yield Prediction Using Satellite Data competition will be announced. The challenge for MLCAS 2024 focuses on the use of satellite imagery datasets from the U.S. Midwest to predict genotype-specific plot-level yield for the 2023 multi-state maize hybrid trials.  

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