NSF-IEEE Workshop: Toward Explainable, Reliable, and Sustainable Machine Learning in Signal & Data Science

The fast-growing areas of artificial intelligence (AI) and machine learning (ML), especially in the area of deep models, are bringing new ways and tools of solving problems beyond the traditional paradigms.  They offer new perspectives as well as prompt challenges in the areas of signal processing and data science.  This workshop aims at bringing together experts from academia, industry, government agencies, and professional societies to discuss research challenges, opportunities, and potential pathways forward and collaborative efforts needed toward explainable, reliable, and sustainable machine learning for signal and data science.  The workshop is envisioned to be an initial step of a series of efforts to foster convergence research in AI/ML that brings together intellectually diverse researchers to develop effective ways of communicating and collaborating across disciplines. 

Acknowledgment:  funding and in-kind support from the National Science Foundation, the IEEE Signal Processing Society, and the University of Maryland.