Sabrina González-Pasterski, an American physicist with Cuban heritage, is rethinking how artificial intelligence might help tackle some of physics’ toughest questions. Her work on gravitational memory and celestial holography is drawing attention from researchers around the world.
When Sabrina González-Pasterski’s research on gravitational memory was cited by Stephen Hawking, it was a milestone for a young scientist already known for building her own airplane at 14. Now 33, she works at the Perimeter Institute in Canada, focusing on celestial holography and how artificial intelligence might change the way physicists approach their field. González-Pasterski is not only a researcher at the Perimeter Institute but also leads the Celestial Holography Initiative, a project aimed at advancing this new direction in theoretical physics.
Her approach stands out. Rather than treating AI as a tool for quick answers, she wants to use it to map the structure of physical knowledge itself—finding links between theories and surfacing questions that haven’t been asked yet. This idea comes from her own background, moving between engineering and physics, and now shapes her research. As described in materials about her career, her AI work is a research goal: using artificial intelligence to explore the space of physical theories and their relationships, not just to automate solutions.
Sabrina González-Pasterski completed her doctorate at Harvard in 2019, marking a clear transition from her early engineering achievements to a formal academic trajectory in physics.
Her early interest in pushing boundaries took her to MIT, where she was among the first women to graduate in physics with the highest possible score. But González-Pasterski draws a line between building something that works and understanding why it works. “As a physicist, you want to know why it works, not just that it does,” she says. This way of thinking now drives her efforts to bridge quantum theory and Einstein’s relativity—two foundations of modern physics that still don’t fit together.
Her research on gravitational memory and the spin memory effect has opened new ways to think about how gravitational waves leave lasting marks on space-time. These effects, seen after events like black hole mergers, offer clues about the universe’s underlying symmetries. According to summaries of her work, gravitational memory and the spin memory effect are central to her research, not just side projects. Her findings suggest these traces could help physicists spot universal mathematical patterns—a step toward the long-sought quantum theory of gravity.
She’s realistic about the limits. Spin memory alone won’t solve the puzzle. It’s part of a larger effort to see if gravity can be described holographically—in other words, if information about our three-dimensional universe can be encoded on a two-dimensional surface, like the celestial sphere. This idea, called celestial holography, is at the heart of her current work. But González-Pasterski warns against taking the “universe as a hologram” metaphor too literally. For her, it’s a mathematical tool, not a literal picture of reality.
Recent independent publications highlight that the intersection of artificial intelligence and fundamental physics is rapidly gaining traction as a research topic. However, most applications remain experimental, with AI being used to explore possible connections between physical theories rather than to provide definitive answers.
There are still major hurdles. Theoretical physicists have yet to build a complete version of holography for flat space-time—the kind that best matches our universe. The real test, González-Pasterski says, is whether these ideas can actually describe what we see. She’s now working with experts in artificial intelligence and mathematics to create the tools needed to explore which physical theories are possible and how they connect.
Her path—shaped by her family’s Cuban roots, early engineering projects, and a willingness to try new things—has become an advantage in a field where tools like AI are changing the landscape. González-Pasterski cautions that if research becomes just about automated answers, physics could lose its core purpose: understanding, not just application. She argues that even if quantum gravity never leads to new technology, the search for knowledge is still worth it.
Labels like “the new Einstein” or “the Einstein Latina” once made her uneasy. Now, she’s willing to use the attention to bring more scientists into developing new tools. “Let them call me what they want,” she says, focusing instead on the need for the scientific community to engage with these changes.
The intersection of science and technology isn’t new. As reported earlier, shifts in scientific thinking often reflect broader changes in society and culture. González-Pasterski’s story shows that the future of physics may depend as much on new ways of thinking as on new discoveries. Her work points to a shift in how fundamental questions are tackled, with artificial intelligence likely to play a bigger role in the next era of research.
