Anima Anandkumar, the Bren Professor of Computing and Mathematical Sciences at California Institute of Technology (Caltech) figures in the 2026 TIME100 AI list, which ranks the 100 most influential people in artificial intelligence.
The wide-ranging list is broken up into leaders, innovators, shapers, and thinkers. The accompanying piece on Mysore, India-born professor cites her pioneering work in “AI-powered techniques to model physical processes with lightning-fast speed.”
Her “work may not control the weather, but it can predict it. The Caltech professor helped pioneer AI-powered techniques to model physical processes with lightning-fast speed—in some cases, more than a million times faster than prior methods,” it says.
“Her algorithms have since been used to forecast weather phenomena thousands of times faster than traditional methods, design novel medical devices and components for quantum computers, optimize a key step in computer chip manufacturing, conduct sustainable nuclear fusion simulations to one day safely harness their energy source, and much more,” notes Time.
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In March, Anandkumar joined the United Nations Secretary-General’s Scientific Advisory Board, helping to shape the U.N.’s scientific agenda and advising its leaders on AI. Her focus is on bringing balance and scientific grounding to conversations on how AI can benefit people across the world, particularly in the Global South, at a time when misinformation around the technology is rife.
She points, for example, to concerns that data centers will be used only for surveillance. “Yes, that is one possible future,” she told Time. “But if democracy is alive, we want to ensure they’re used for other applications, like weather, climate, scientific discovery.”
In 2020, she introduced the concept of neural operators, AI models that work with continuous mathematical functions rather than discrete data points. These neural operators are well suited for making scientific predictions that are grounded in the continuous, physical world.
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Anandkumar has worked to apply neural operators in a variety of scientific contexts such as weather forecasting and the optimization of computer chip manufacturing.
Anandkumar co-founded Accelerated Understanding, a company scaling such methods into a universal AI model for physical simulation and engineering, and recently announced reaching a milestone of five trillion context length to accommodate large spatiotemporal data.
She received her B Tech from the Indian Institute of Technology Madras and her PhD from Cornell University and did her postdoctoral research at MIT. She was previously principal scientist at Amazon Web Services and senior director of AI research at NVIDIA.