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CENSAI aims to tackle the AI ‘grand challenge’ of accelerating science

UNIVERSITY PARK, Pa. — Bringing together researchers from across various disciplines at Penn State and beyond, the Center for Artificial Intelligence Foundations and Scientific Applications (CENSAI) has its sights set on advancing AI to dramatically transform science, according to Vasant Honavar, CENSAI founding director said in a recent interview with EdgeDiscovery. 

CENSAI is the result of grassroots faculty efforts over many years, Honavar said. 

Ten years ago, there was a lot of excitement around big data — using large data sets and high-performance computing (HPC) to solve complex, longstanding problems in science.  

“Getting data is only the first step,” Honavar said. “You analyze data, you generate hypotheses, you run experiments, you modify your hypotheses… all of these steps are part of the scientific process. Accelerating science requires accelerating all of the steps in teh scientific process.” 

The primary focus of the Penn State Institute for Computational and Data Sciences (ICDS) at the time in which Honavar started as a co-hire, was on computing infrastructure, primarily HPC infrastructure for science. Over time, ICDS expanded its focus to include the development and applications of new methods and tools for computation-enabled, data-intensive scientific discovery. 

Given the role of ICDS in helping advance and support different scientific domains at Penn State, Honavar and other faculty with similar interests came together around a shared vision around AI for scientific discovery and proposed the establishment of CENSAI. The center was approved in 2021. 

CENSAI tackles two interrelated goals: pursuing foundational research in AI that is aimed at tackling the AI grand challenge of accelerating and transforming the practice of science and leveraging the advances in AI to accelerate science. 

Together, CENSAI leadership, ICDS Research Innovations with Scientists and Engineers (RISE) team and other researchers with deep expertise in specific scientific domains will collaborate to pursue research challenges none of them could tackle on their own.  

Working groups are organized within CENSAI around life, health, materials and social sciences. 

CENSAI hopes to foster interdisciplinary collaborations around AI-enabled science across Penn State. 

“These [research focuses] represent areas in which Penn State has significant strengths and offers opportunities for major advances in the foreseeable future where Penn State also has a reasonable chance of success,” Honavar said.  

CENSAI also seeks to develop multi-institutional collaborations that bring together researchers with complementary expertise and interests to go after ambitious research projects.  

In a recent interview with EdgeDiscovery, Honavar said, “The formation of teams with the right combination of expertise and interests is crucial for successfully advancing AI and enabling scientific discoveries in different domains using the power of AI.” 

“The other unifying idea is that even though scientific disciplines can be quite different, they often share common needs in terms of methodological advances in AI,” Honavar said. 

While the past decade has seen major advances in machine learning, and hence predictive modeling from large data sets, the current state-of-the-art in AI methods for generating hypothesis, optimizing the design of experiments, integrating information from multiple disciplines and structuring human-machine collaborations in science, remain unanswered,” Honavar said.  

“Scientific discovery provides a grant challenge for AI,” Honavar said. “Making progress on AI methods for science would yield fundamental advances across multiple areas of AI. It would also transform the practice of science and dramatically accelerate scientific discovery.” 

The work of CENSAI has the potential for broad societal impact as well. 

“If we can use AI to accelerate science, then we can have a positive impact on all of the field that those sciences are impacting,” Honavar said. “If you can use AI to figure out how to better predict the risk of heart disease, then you would help reduce the burden of the disease. That’s what excites me about CENSAI… advancing AI not just in the abstract, but in ways that tackle major scientific and societal challenges.” 

One of the CENSAI working groups focused on material science has been working with the National Institutes of Standards and Technology (NIST) and researchers from Wisconsin, the University of Maryland, Carnegie Mellon University, Northwestern University and several other partners around the country on a proposal for an AI institute for materials discovery, design and synthesis. 

This institute is organized around a vision of AI for closed-loop human-AI collaboration in science, using materials science as a test case.  

A second CENSAI working group, led by Ed O’Brien, ICDS co-hire and professor of chemistry, recently secured a $20 million grant for the U.S. National Science Foundation (NSF) National Synthesis Center for Emergence in the Molecular and Cellular Sciences (NCEMS). The funding was granted by NSF.  

The focus of NCEMS is to integrate and analyze existing data sets to answer open questions in molecular and cellular sciences.  

“The center is not about a single project, instead it is about enabling and supporting many projects covering a broad spectrum of research questions in the life sciences identified by the larger scientific community and executed using the resources provided by the center that NSF funded,” Honavar said. 

Researchers within a working group at CENSAI are focused on biomedical and health sciences. This group is contributing the informatics, data science and expertise to the Penn State Clinical and Translational Science Institute (CTSI), which is funded by the National Institutes of Health (NIH). 

Some CENSAI researchers are part of groups focused on AI-enabled cyber security and data and computational infrastructure for collaborative data-driven science. 

“I’m always excited about pushing the frontiers of what AI can do,” Honavar said. “Bridging the gap between AI research and scientific applications has many dimensions including AI education for researchers in various areas of science, what AI is and what it can and can’t do, as well as how to start thinking about projects in one’s own area of expertise that could benefit from AI. The other is infrastructure; you’ll need funding, collaborators and access to local or national infrastructure to do the work you want to do.” 

CENSAI works to ensure ICDS infrastructure offers Penn State researchers an on-ramp to connect to national resources. 

CENSAI continues to be an open community for researchers who are interested in AI, science and human machine collaboration. Researchers can participate in projects that suit their interests. Look out for events, workshops and idea labs organized by CENSAI and calls for seed grant proposals from ICDS on topics related to CENSAI.  

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