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GW to Co-Lead a New $20 million NSF AI Institute
The George Washington University is co-leading a multi-institutional effort supported by the National Science Foundation (NSF) that will develop new artificial intelligence (AI) technologies designed to promote trust and mitigate risks, while simultaneously empowering and educating the public. The NSF Institute for Trustworthy AI in Law & Society (TRAILS) unites specialists in AI and machine learning with systems engineers, social scientists, legal scholars, educators, and public policy experts. The multidisciplinary team will work with impacted communities, private industry, and the federal government to determine how to evaluate trust in AI, how to develop technical solutions and processes for AI that can be trusted, and which policy models best create and sustain trust. David Broniatowski, an associate professor of engineering management and systems engineering at GW, is the lead principal investigator of TRAILS at GW.
The new institute is expected to transform the practice of AI by encouraging new innovations that foreground ethics, human rights, and input and feedback from communities whose voices have previously been marginalized. The NSF, in collaboration with government agencies and private sector leaders, has now invested close to half a billion dollars in the AI institutes ecosystem—an investment that expands a collaborative AI research network into almost every U.S. state.
October's Local Hero: Jessica Palermo
October 18, 2023
Each month we will highlight one of the members of the GW Engineering staff in our Local Hero editorial feature. Take the time to meet October's Local Hero, Jessica Palermo!
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ECE Professors Suresh Subramaniam and Tian Lan helped coordinate MobiHoc 2023 being held in the University Student Center and Science & Engineering Hall from October 23 through 26, 2023.
Using Machine Learning to Optimize Cold Plasma Applications
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A pioneer in cold plasma research, Professor Michael Keidar has received a $100,000 grant from the Department of Energy to overcome the challenge of optimizing plasma chemistry for specific targets.
