2025 Stanford Doerr Discovery Grants

Assessing our anthropogenic oceans

PI: Krish Seetah, Associate Professor of Environmental Social Sciences, of Oceans, and of Anthropology, and Senior Fellow at the Stanford Woods Institute for the Environment
UNESCO estimates that ~3 million shipwrecks are scattered across our oceans. Wrecks can be decades, centuries, or even millennia old; some vessels – oil liners, cruise ships – compare in size to a skyscraper. Shipwrecks are a potential ‘quiet tipping point’ and their cumulative effects could be having disastrous impacts on ocean ecosystems. Wrecks illustrate a profoundly negligent attitude towards ocean stewardship. Using shipwrecks as a starting point, this high-risk project aims for a reconceptualization of how we study ‘objects’ in our seas, aligning visual, acoustic, and ecological data for a radical new assessment of how anthropogenic structures impact the world’s oceans.

Fuel for survival: Plant energy reserves through time and turmoil

PI: C. Kevin Boyce, Professor of Earth & Planetary Sciences
Non-structural carbohydrates (NSCs) are a plant’s reserves and insurance policy, fueling recovery and regrowth after frosts, wildfires, and long winters. NSCs had a dramatic impact on different plant responses to the haze of recent fires in California. We will examine how NSC reserves vary and are managed across plant lineages, their role in surviving environmental disturbances now in the face of today’s growing climate challenges, and whether comparison with fossils might reveal past strategies that determined survival of extreme events of the geologic past like the meteorite that killed the dinosaurs and reshaped Earth’s forests 66 million years ago.

An active matter framework for collective animal behavior

PI: Nicholas Ouellette, Professor of Civil and Environmental Engineering
Groups of animals behaving collectively, such as bird flocks, are commonly held up as motivating examples by researchers studying active matter. However, surprisingly little work has been done to show that animal groups can actually be described as a form of “matter” as it is understood in physics or materials science. The goal of this project is to demonstrate that this analogy indeed holds for real animal groups, in that they have well-defined “material” properties and “thermodynamic” states. We will achieve our goals by analyzing empirical data for two canonical types of collective behavior: bird flocks and insect swarms.

The psychology of climate solutions: Effects of an immersive documentary

PIs: Madalina Vlasceanu, Assistant Professor of Environmental Social Sciences, and Sara Constantino, Assistant Professor of Environmental Social Sciences 
This project consists of a longitudinal experiment and field RCT to test the effects and mechanisms of an immersive Climate Literacy Intervention aimed at increasing a lay audience’s awareness and understanding of 1) climate change impacts and solutions, 2) the psychological tools necessary to engage in and sustain meaningful climate action, and 3) empirically informed strategies to engage others in climate action. This project pushes the boundaries of current research on the behavioral and psychological science of climate action, while also having the potential to make significant contributions to overcoming pervasive inaction on climate change.

A machine learning approach to seismic source classification

PI: Greg Beroza, Professor of Geophysics
Earthquakes occur in diverse tectonic and volcanic settings, and the waves they generate reflect those differences. Under this grant we will use multi-view machine learning to classify different types of earthquakes systematically to help understand the mechanics underlying their occurrence. Our application will be restless volcanoes for which the interaction of solid, fluid, and gas phases lead to strongly different earthquake types. The initial focus will be on Campi Flegrei, a volcanic system that poses a direct threat to the environs of Naples, Italy, but our approach will generalize to other volcanoes, and to earthquakes in all settings.

Building a computer vision tool to quantify the biomass of skeletal marine animals, algae, and protists across the past 600 million years

PI: Jonathan Payne, Professor of Earth & Planetary Sciences and Senior Fellow at the Stanford Woods Institute for the Environment
Changes in biodiversity across the ~600-million-year history of animal life are well understood, including both intervals of diversity increase and episodes of mass extinction. By contrast, variation in the total mass of living organisms (i.e., biomass) across evolutionary time remains essentially unknown. In this project, we aim to build a computer vision tool that can be used to recognize animal shells in marine limestone of various ages, enabling quantification of variation in skeletal abundance across time and environments. This tool would open a new window on the evolution of animal life and the connection between biodiversity and biomass.

All-solid-state lithium battery in diamond anvil cell – A cell within the cell

PI: Wendy Mao, Professor of Earth & Planetary Sciences and of Photon Science 
This project leverages diamond anvil cell technologies to study how pressure influences battery performance and electrochemical processes in situ, aiming to uncover key factors that control the behavior of solid-state materials such as ion transport, reaction kinetics, and phase stability. These fundamental insights could prove critical for developing all-solid-state lithium batteries which show great promise for next generation energy storage devices which are essential for sustainable energy systems. PI Mao will collaborate closely with SIMES staff scientist Yu Lin and SLAC-Stanford Battery Center Executive Director Jagjit Nanda and Scientist Yan-Kai Tzeng.

Real-time simulations via hybrid numerical-machine learning algorithms

PIs: Barbara Simpson, Assistant Professor of Civil and Environmental Engineering; Eric Darve, Professor of Mechanical Engineering; and Catherine Gorlé, Associate Professor of Civil and Environmental Engineering
Understanding multi-physics phenomena in engineering is essential for addressing global challenges. However, accurately modeling these systems is computationally prohibitive. Offshore wind turbines (OWTs), in particular, face challenges from coupled aero-hydro-structural forces, where mid-fidelity models miss key interactions, and high-fidelity models are too expensive for long-term analysis. The project objective is to develop a hybrid numerical–machine learning framework that creatively employs learned models, i.e., Graph Neural Networks, to represent fluid domains while modeling structure with efficient finite element models. This novel approach takes advantage of learned models to capture complex nonlinear interactions and numerical methods to ensure stability and efficiency.

The effectiveness and long-term impact of installing underwater barriers in front of vulnerable ice sheets

PI: Earle Wilson, Assistant Professor of Earth System Science
One proposed geoengineering strategy to protect vulnerable glaciers is installing submarine barriers to block warm seawater from reaching their margins. While proponents argue this is a cost-effective strategy to mitigate the impacts of sea level rise, the environmental consequences of altering the ocean circulation on this scale are unknown. We will conduct a process-based modeling study to assess the scientific feasibility of this approach and its long-term oceanic impacts. This study is a first step toward a more comprehensive environmental assessment of this geoengineering proposal.

Elucidating the community context of entomopathogens for more effective biological control

PI: Tadashi Fukami, Professor of Biology and of Earth System Science
This project aims to determine how multiple species of pathogens affect one another within the same host and how these interactions influence host survival. The specific focus is the bacteria, fungi, and nematodes that infect nut-infesting beetles and moths. This research will provide the ecological knowledge needed to reliably use entomopathogens for biological control as a more sustainable alternative to pesticides. Due to their complexity, interactions among these pathogens are rarely studied, which may explain the limited success thus far of biological control. Tadashi Fukami and Amaury Payelleville will conduct this research along with students mentored by them.

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