AAAI 2024 Spring Symposium Series will be hosted at Stanford University on March 25-27, 2024 as part of the Association for the Advancement of Artificial Intelligence (AAAI) conference. The conference will include the following eight symposia:  Bi-directionality in Human-AI Collaborative Systems Clinical Foundation Models Symposium Empowering Machine Learning and Large Language Models with Domain andContinue reading "AAAI 2024 Spring Symposium Series"

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!

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"

Join this Zoom webinar to hear from senior leadership in the U.S. Department of Education about their newly released document, "Designing for Education with Artificial Intelligence: An Essential Guide for Developers."

Featuring Imme Ebert-Uphoff (CSU/CIRA), this one-hour talk focuses on Measuring Sharpness of AI-Generated Meteorological Imagery.

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"

Join us via Zoom for a talk to introduce the main issues and themes pertaining to the ethics of AI, featuring Clayton Peterson, Associate Professor of Philosophy, Université du Québec à Trois-Rivières. Analyzing what the ethics of AI are by reflecting on our understanding of both ethics and AI, the aim of this session isContinue reading "INVITEd Talk: Understanding Ethics of AI"

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.