The Yale School of Engineering & Applied Science has awarded seed research grants to support new, ambitious, and speculative research in artificial intelligence. These grants, a strategic initiative aligned with Yale Engineering’s commitment to AI as a research priority, will empower researchers to pursue pioneering projects across a range of critical areas, from foundational AI research to practical applications that intersect with fields such as materials science, environmental sustainability, and healthcare.
This year’s awardees include interdisciplinary teams exploring innovative ways to harness AI’s potential, with projects designed to achieve impact through technological breakthroughs, community engagement, and industry partnerships. Funded projects were selected based on their potential to drive advancements that support Yale Engineering’s strategic vision and to position Yale researchers for future external funding opportunities.
“AI is a powerful and rapidly-evolving tool, and while much of the public excitement tends to focus on its natural-language applications and realistic mimicry, its potential uses are much broader and more profound than that,” said Yale Engineering Dean Jeffrey Brock. “These projects demonstrate just a few of the ways that our faculty are taking a strategic approach to advancing AI, from tackling the problem of ‘hallucinations’ to devising new brain-inspired approaches to computer memory systems.”
Awarded projects and workshops span Yale Engineering’s strategic focus areas in AI, including the technological aspects of AI, its applications, and its impact on people and society. Projects include the development of interpretable AI models for complex scientific reasoning, applications exploring the integration of AI in sustainable materials and medical diagnostics, and enhancing storytelling in science and engineering. Workshops funded under this initiative will explore AI’s potential in transforming engineered wood for sustainable construction and foster interdisciplinary dialogue on multimodal deep learning.
Supported by Yale Engineering and the Office of the Provost, the competitive seed funding program is designed to provide Yale Engineering faculty and their collaborators from across the university with resources to generate preliminary results, strengthen their research portfolios, and enhance competitiveness for external funding. Awarded projects are eligible for additional support in the form of cloud credits from Amazon and Google, further amplifying their capacity to leverage cutting-edge resources in pursuit of pioneering research.
Exploring Photo-Electro-Chemical Neural Network for Energy-Efficient AI Computing
Awardees: Shu Hu (Chemical & Environmental Engineering) & Fengnian Xia (Electrical & Computer Engineering)
In this interdisciplinary project, Shu Hu and Fengnian Xia are pioneering an ambitious project to address another pressing challenge of AI: the high energy demands of digital AI computing. Their goal is to design a new type of AI hardware that mimics the brain’s energy efficiency. As AI workloads grow, particularly with the rise of large language models, energy-efficient computing has become a top priority. Traditional AI infrastructure struggles to balance performance with energy costs, underscoring the need for innovative hardware solutions.
The research team’s approach uses photo-electro-chemical processes to create a 3D, reconfigurable neural network. This design leverages the brain’s adaptability, enabling neural networks to change their structure and connectivity based on specific needs. By creating an all-analogue, brain-inspired computing model, they hope to achieve higher energy efficiency without sacrificing performance, opening doors for sustainable AI hardware.