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Animashree Anandkumar Uses AI to Connect Scientific Fields

Animashree Anandkumar
AAAS Member Animashree Anandkumar, Ph.D.

As emerging technology advances at an unprecedented rate, so too does the amount of data that are collected. Although analyzing extremely large data sets can have notable implications, from drug discoveries to climate change forecasts and beyond, making sense of the sheer volume of big data can be challenging and overwhelming for even the brightest scientists.

For AAAS Member Animashree (Anima) Anandkumar, the most powerful tool that can be harnessed to help understand giant data sets lies with artificial intelligence (AI). By automating and modeling data, AI can help analyze information with less labor and time, and even draw helpful insights and enable new discoveries. Anandkumar has become a leader in the field, dedicating her career to advancing the theoretical and practical aspects of machine learning.

Being a STEM pioneer runs in Anandkumar’s veins. Growing up in present day Mysuru, India, both of her parents, who are still to this day engineers, were some of the first people to introduce programmable manufacturing machines into the city. Anandkumar learned basic programming from them and was introduced to machines called computer numerically controlled systems (CNCS), where the system was programed to move tools that would manufacture automotive parts.

“Just seeing these big machines move through the power of programming, that just made it so much more physical and visual for me,” she says. “I could see that connection between programming and engineering, and also between math, science and engineering.”

An important turning point for Anandkumar happened in high school when she was introduced to probability. She could finally make sense of something that is not deterministic. “I was just awed by the structure of numbers,” she recalls. “That's what created this curiosity. There was always more to learn.”

That interest led Anandkumar to pursue electrical engineering at the Indian Institute of Technology in Madras, India. While there, she did an internship during the summer of her junior year “with such a great professor,” she recollects. This experience was her first introduction to AI and machine learning. “That was when I was like, I want to do this for the rest of my life,” Anandkumar says. She then went on to attain her doctorate from Cornell University and followed that by pursuing her postdoc at the Massachusetts Institute of Technology, all the while working on AI-related research.

Now as a Bren Professor of Computing at California Institute of Technology (Caltech) and senior director of AI research at the tech company NVIDIA, Anandkumar is excited about the real-world applications of AI. For example, she recently used AI to help model carbon capture and storage (CCS)—a complicated process to predict, but one that is integral for mitigating the effects of future climate change. She has helped experts better comprehend and predict carbon dioxide’s interaction with water underground over time, how much pressure builds up underground, how gas plumes expand over multiple decades, and other important insights. Her AI speeds up CCS by 700,000 times, which makes large-scale exploration and assessment of CCS possible. According to Anandkumar, she plans to work with companies to investigate and evaluate areas for CCS.

This work integrating AI with CCS is an example of the many interdisciplinary efforts that Anandkumar has been a part of. She worked with energy engineer Sally Benson, co-director of the Stanford Center for Carbon Storage and the Stanford Carbon Removal Initiative and now Deputy Director for Energy at the White House Office of Science and Technology Policy, on the project. “To me, it's all about being part of these teams … This could not be accomplished individually,” Anandkumar states. “AI is a great connector of these different fields.”

To foster even more collaborations between scientific disciplines, Anandkumar has helped found AI4Science @ Caltech, an initiative that connects AI researchers with specialists from other fields in an effort to advance AI tools for use in STEM. She also mentors for Caltech's WAVE Fellows program, which works to increase diversity in science and engineering graduate programs so that they can be more accessible to minorities. “Diversity and inclusion have been so close to heart,” she says. Many fellows that Anandkumar has worked with have gone on to pursue graduate school and Caltech and elsewhere.

With WAVE Fellows and other mentees, she makes sure they feel connected to the field and that they know when and where to ask for help. “I think that's something I tell everybody,” Anandkumar adds. “Asking for help is the most important thing for success and for some people, the hardest.”

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