Stanford University backs five AI research teams with follow-on Hoffman-Yee funding
Stanford University has awarded additional Hoffman-Yee grant funding to five interdisciplinary AI research teams, extending projects that span biology, generative AI, policing, and neuroscience, with implications for how human-centered AI research feeds into education, industry, and public policy.
Professor Jennifer Eberhardt of Stanford University presents findings from her team’s AI and policing research at the Hoffman-Yee Symposium
Photo credit: Stanford University
Stanford University has awarded up to two million dollars each in follow-on funding to five interdisciplinary research teams as part of its Hoffman-Yee Research Grant program, extending work focused on human-centered artificial intelligence across science, health, and society.
The funding, administered by Stanford Human-Centered Artificial Intelligence (HAI) and supported by a philanthropic gift from Reid Hoffman and Michelle Yee, builds on initial 2024 awards of five hundred thousand dollars per team. In total, the Hoffman-Yee program has now distributed 27.6 million dollars to date, reinforcing Stanford’s role as a hub for applied AI research with downstream relevance for education, skills, and real-world systems.
Extended funding for human-centered AI research
Stanford HAI selected the five teams from its 2024 cohort following a competitive review process that included public presentations at the Hoffman-Yee Symposium and private interviews with a selection committee.
James Landay, co-director of Stanford HAI, says the program is designed to support ambitious work with long-term impact. “Hoffman-Yee Research Grants are given to teams that show boldness, ingenuity, and potential for transformative impact in human-centered AI,” he says. “We believe these projects will play a significant role in defining future work in AI, from academia to industry, government, and civil society.”
The five teams will continue research across areas including generative AI and creativity, biological modeling, public safety, neuroscience, and genomics. Several projects also emphasize open-source tools and interdisciplinary collaboration, reinforcing connections between academic research and workforce development.
From virtual cells to policing and creativity
One funded team is advancing work on a human-centered AI virtual cell, combining large-scale biological data with multimodal AI models. Emma Lundberg, associate professor of bioengineering and pathology at Stanford, says the funding supports a long-term research vision. “This additional Hoffman-Yee funding enables us to pursue our bold vision of building virtual cell models to advance our understanding of drug response,” she says.
Another team is applying AI to analyze body-worn camera footage, integrating insights into law enforcement training and evaluation. Jennifer Eberhardt, professor of psychology at Stanford and project lead, says the scale of the data enables new forms of analysis. “Our initial findings demonstrate the potential of our approach: combining massive datasets, advanced AI tools, and interdisciplinary expertise to evaluate policy effectiveness and identify practices that reduce escalation and build trust,” she says.
Research into generative AI and creativity is also being extended, with teams exploring how humans and AI systems establish shared conceptual grounding when creating visual and immersive content. Early work has already informed product development and contributed to new interdisciplinary communities at Stanford.
Several projects intersect directly with education and skills development, particularly through the creation of AI assistants, open-source tools, and new research communities that span disciplines.
Ehsan Adeli, assistant professor of psychiatry and behavioral sciences at Stanford, says Hoffman-Yee funding has enabled cross-disciplinary work that would otherwise be difficult to sustain. “This support has created a level of cross-disciplinary collaboration that would not have been possible otherwise,” he says, pointing to the challenge of building large-scale foundation models of the human brain.
The Evo genomics project also continues under the extended funding, with Brian Hie, assistant professor of chemical engineering at Stanford, noting the role of early support. “Our work would not be possible without this support,” he says.
