2026 TomKat Graduate Fellowships awarded across six departments
Navigating challenges
Six doctoral students have won graduate fellowships to propel their proof-of-concept research toward real-world deployment, tackling challenges that span aviation emissions, power electronics, agriculture, bioenergy, wildfire protection, and tribal energy policy. Starting this fall, the 2026 cohort will receive two years of support through the TomKat Center's Graduate Fellowships for Translational Research, which provide tuition, stipends, and additional research funding while immersing fellows in a community built around translating early-stage science into deployable solutions.
Since the program's founding in 2020, TomKat fellowships have supported Stanford doctoral students in their third year or beyond as they move discoveries out of the lab and toward licensing, spinouts, field trials, and partnerships. The fellowship can also serve as a launchpad into other Stanford Doerr School for Sustainability programs, including the Sustainability Accelerator, Ecopreneurship fellowships, and TomKat's own Innovation Transfer Program.
Tracking down impact
The TomKat graduate fellows are addressing urgent problems in energy and the environment.
Atmospheric water vapor is one of the least-observed variables in weather and climate science, measured today only sparsely by twice-daily weather balloon launches and coarse satellite passes. That gap also makes it difficult to predict whether a flight will cross into a thin region of ice-supersaturated air that produces persistent contrails, which are a source of radiative forcing that rivals aviation's direct CO2 emissions. Gibson Clark, a PhD candidate in the Department of Mechanical Engineering, is developing IRISS, the In-flight Real-time Infrared Spectroscopic Sensor, an onboard instrument that would add humidity to the suite of variables commercial aircraft already measure. The fellowship will support sensor development and validation, along with a real-time contrail-probability dashboard to deliver flight-level humidity data to airlines through the World Meteorological Organization's Aircraft Meteorological Data Relay network. The same measurements would improve precipitation forecasting worldwide.
Power converters underpin nearly every electrified system, from EVs and drones to data centers and medical devices. Their mass, volume, and waste heat trade directly against range, payload, and compute density. As a PhD candidate in Electrical Engineering, Clarissa Daniel’s research targets the magnetic components that typically bottleneck converter miniaturization, replacing them with piezoelectric resonators that store energy mechanically instead. These planar, chip-integrable devices stay efficient at frequencies far beyond what magnetics can reach and generate so little heat that converters built around them can operate with reduced thermal management and therefore not require bulky heat sinks. The fellowship will build on prior work from the SUPER Lab by characterizing how resonators behave and fail under real high-power operation, exploring new materials and resonator geometries. Daniel will also develop the packaging, thermal management, and control systems needed to integrate piezoelectric converters into power electronics.
Genetically engineered crop traits typically run "always on," active in every tissue at every growth stage regardless of need, which imposes yield and metabolic costs and limits how sophisticated a trait can be. Isabel Goldaracena-Aguirre, a Bioengineering PhD candidate, is building a programmable toolkit that lets plants express a gene only under precise conditions, using genetic "AND gates" that require multiple biological signals. These gates can reserve expression until optimal cell type, developmental stage, and environmental cues align before the traits switch on. The approach could reduce reliance on pesticides and fertilizers by letting crops express protective or nutrient-related traits precisely when and where they are needed, cutting the volume of agricultural chemicals and the energy used to produce them. The TomKat fellowship will support advancing this platform toward real-world use, including licensing pathways that could eventually bring programmable trait control to agriculture.
Scaling biofuel crops to meet the demands of hard-to-electrify sectors like aviation, shipping, and trucking runs headlong into a land-use problem: biofuel production competes with the arable land needed for food. That tension could be resolved if biofuel crops could thrive on marginal land. To do this, we require knowledge, from DNA sequence alone, of which genetic variants will improve a plant's stress tolerance. Kristy Mualim, a PhD candidate in Biology, is training deep learning models on multi-species regulatory genomics data to decode the sequence rules governing stress-induced gene expression in bioenergy crops. This will enable precise redesign of stress-tolerant gene promoters without the off-target effects of broad genetic interventions. Starting from species in the Brassicaceae family, this framework is designed to extend to any flowering plant, since the stress-signaling pathway is broadly conserved. She intends to release the trained model as a free, open tool for the research community, to help plant breeders and engineers unlock an estimated 900 million hectares of underused marginal land for fuel crops without competing with food production.
As more homes are built in fire-prone regions, the tools available to protect them remain expensive, environmentally harmful, or impractical to deploy at scale. As Athena Kolli pursues her PhD in Materials Science and Engineering, she is developing a new class of wildfire retardants that can be applied proactively to homes and critical infrastructure before fire season begins, offering durable protection when and where it is needed most. Unlike approaches that require application immediately before or during a wildfire threat, these materials are designed to withstand extended outdoor exposure while retaining their fire-retardant performance. Her fellowship research will focus on formulating retardant materials that balance long-term durability, fire-retardant performance, and environmental compatibility, while optimizing adhesion, weathering resistance, and sprayability. Just as importantly, these retardants will be designed to work with existing application equipment and scalable manufacturing processes, reducing barriers to adoption. By validating performance and environmental impact and collaborating with fire management partners on field deployment, this work will help move next-generation wildfire retardants from laboratory development toward practical, large-scale use.
The Navajo Nation, one of the largest tribal nations in the United States, has depended on nonrenewable energy extraction since the 1920s for royalties, leases, employment, and tax revenue. The shift toward renewable energy will inevitably reshape their tribal land and economic base. As a PhD candidate in Earth System Science, Raven Alcott's research centers tribal self-determination in that transition, using two forms of knowledge co-production to close the gap between energy-decision tools and the communities they affect. Working directly with the Navajo Nation and tribal citizens, the TomKat fellowship will allow Alcott to co-develop future-oriented energy scenarios and operationalize them through energy transition modeling and analysis, addressing sustainability challenges linked to a historical lack of consultation, collaboration, and consent in decisions about the Nation's energy future.
About the fellowship: Established in 2020, the TomKat Center's Graduate Fellowships for Translational Research support Stanford doctoral students in their third year or beyond as they move applied research from proof-of-concept toward impactful, real-world solutions. Fellows receive two years of tuition and stipend support plus additional research funding, along with mentorship and a peer community focused on translational research.
