The National Science Foundation (NSF) is investing $3 million over the next five years in the Artificial Intelligence (AI) Advancements and Convergence in Computational, Environmental, and Social Sciences (AI-ACCESS) program at Washington University in St. Louis. The grant is one of 22 new awards totaling nearly $63 million to create a new generation of talent in the STEM fields that reflects the diversity of the nation.
An NSF research traineeship (NRT) program, AI-ACCESS aims to build a cohort of new investigators trained at the intersection of AI, environmental science and social science to harness innovative computational tools to address global challenges including climate change.
William Yeoh, associate professor of computer science & engineering in the McKelvey School of Engineering, will lead AI-ACCESS with co-principal investigators Patrick Fowler, associate professor in the Brown School and director of the doctoral program in Public Health Sciences; Roman Garnett, associate professor of computer science & engineering, and Fangqiong Ling, assistant professor of energy, environmental & chemical engineering, both in McKelvey Engineering; and Claire Masteller, assistant professor of earth, environmental and planetary sciences in Arts & Sciences. AI-ACCESS is WashU’s second NSF research traineeship program, following the Linking Quantum Sensing Technologies across Disciplines (LinQ-STL) program awarded in 2022.
“We’re focused on how these three different disciplines — computational science, environmental science and social science — can converge to work on complex interdisciplinary problems,” Yeoh said. “WashU already has strengths in these areas and experience working across disciplinary boundaries, for example, in the Division of Computational & Data Sciences (DCDS), which focuses on applying data science methods to social science problems. By extending what we’re already doing into environmental science and engineering, our trainees will be poised at the cutting edge of using AI to solve complex climate-related problems and address their environmental and social impacts.”
WashU will recruit and retain a diverse group of 49 doctoral students, including 24 NSF-funded trainees and 25 trainees supported by WashU. Support pledged by the deans of Arts & Sciences, the Brown School and McKelvey Engineering at WashU ensures that international students, U.S. citizens and permanent residents can participate in the program and be funded throughout their training, from coursework to internships.
AI-ACCESS draws from a range of disciplines including computer science, environmental science and engineering, environmental justice, public health and social work. This holistic approach to education will provide students with a transdisciplinary perspective, ranging from foundational AI and machine learning to advanced topics in statistical and causal inference, while also fostering innovation and collaboration. Importantly, the program will emphasize the ethical dimensions of AI and data science, ensuring that future professionals are well-equipped to navigate complex ethical challenges.
“Students and faculty across campus will collaborate on projects investigating the environmental, policy and social responses to climate change through emerging data-driven methods,” said Fowler, who co-directs DCDS at WashU with Yeoh. “I look forward to learning at the intersections of environmental health, ethics and technology.”
AI-ACCESS will free students and faculty to think beyond departmental boundaries and open opportunities to conduct cutting-edge research in various disciplines. Graduate student trainees will matriculate into key constituent doctoral programs at WashU including computer science & engineering; earth, environmental and planetary sciences; political science; sociology; social work; and public health sciences. The program supports them throughout building transdisciplinary expertise and gaining professional experience through internships.
Ultimately, AI-ACCESS trainees are expected to emerge with a deep understanding of the convergence of AI and environmental social science to fill a growing need for organizations that aspire to develop data-driven policies and computational algorithms to address complex environmental and social challenges.
“Environmental systems are at the center of some of the most pressing challenges of our times, such as curbing climate change and adapting to its impacts, creating healthy and resilient cities, and designing a future without pollution,” said Ling, who studies microbial ecosystems to improve water supply safety and public health. “Many environmental systems are inherently complex; therefore, comprehending them demands the capacity to effectively collect and use multi-modal data.”
“Equally important is the skill to communicate the insights drawn from the data to the public and decision-makers,” Ling added. “All of these tasks necessitate a strong aptitude for working with data.”
Yeoh noted that interdisciplinary work gives researchers the opportunity to make broad impacts and engage students in new ways.
“By building on our interdisciplinary efforts at WashU and forming new collaborations to apply emerging AI and computational tools to social and environmental problems, we have the potential to bring about significant transformation of scientific practice and position our students as future leaders in these areas,” Yeoh said.
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