The Center for Information Technology Research in the Interest of Society and the Banatao Institute (CITRIS) at the University of California (UC) is proud to announce the recipients of the 2025 CITRIS Seed Awards. Four multicampus teams from UC Berkeley, UC Davis (including the UC Davis Health medical campus), UC Merced and UC Santa Cruz will receive up to $60,000 to propel their early-stage, proof-of-concept research into full-fledged information technology solutions to some of society’s most pressing challenges.
The CITRIS Seed Funding Program prepares awardees to make long-term, beneficial contributions to their fields through projects designed to show results within one year and to garner significant follow-on funding. This year’s winners, each exemplifying an innovative, interdisciplinary problem-solving approach, will join a community of more than 410 researchers across 250-plus projects supported by the program since its launch in 2008.
“The selected proposals show great potential to be truly transformative,” said Alexandre Bayen, director of CITRIS and the Banatao Institute, Liao-Cho Innovation Endowed Chair and professor of electrical engineering and computer sciences at UC Berkeley, and associate provost for the Berkeley Space Center. “We are pleased to support UC researchers who will shape the futures of their fields while also making a tangible positive impact on society.”
More than 65 proposals were submitted this year in four critical research areas: aerospace and aviation; artificial intelligence (AI), autonomy and robotics; digital health; and sustainability and climate resilience. Common themes among this year’s submissions included harnessing data for more energy-efficient processes and improving the accessibility of burgeoning technologies to broader populations.
The following projects received 2025 awards:
AERO-SENSE: Autonomous environmental robotics for onboard sensing and estimation of near-surface environments
Principal investigators: Javier González-Rocha (lead PI, UC Santa Cruz), Camli Badrya (UC Davis)
Accurate wind measurements in the lowest layer of the atmosphere are crucial for forecasting weather, monitoring air quality, ensuring safe flights and managing wildfire risk. Current tools suffer from significant technical restraints: Observations from satellites and crewed aircraft are coarse and infrequent, while ground-based towers are limited by height and terrain. This project seeks to transform multirotor uncrewed aerial vehicles, also known as UAVs or drones, into real-time mobile wind sensors, using just their onboard motion and control data. The research team will employ a combination of wind tunnel experiments, real-world flight testing and model-based estimation to develop a scalable, energy-efficient monitoring system that reinforces safe drone practices. Beyond enhancing the quality of environmental monitoring, this proposal will also expand access to air quality data across underserved communities and contribute to long-term drone workforce development.
Maximizing grid infrastructure capacity for electrification
Principal investigators: Duncan Callaway (lead PI, UC Berkeley), Alan Jenn (UC Davis)
Electrifying transportation systems is a key step toward reducing carbon emissions, but a large-scale transition to electric vehicles (EVs) will require extensive, expensive upgrades to power distribution infrastructure. This project aims to introduce robust, scalable algorithms to EV chargers at the factory level to strategically allocate electricity based on usage trends. Researchers will explore two approaches: a pricing model based on grid data and customer behavior, and a voltage monitoring system that will enable chargers to reduce energy consumption in response to voltage drops that signify high grid usage. The team will validate their results with simulations and deploy field pilots in collaboration with utilities to examine performance under real-world conditions. By incorporating customer behavior into a decentralized and data-focused approach, this work presents a cost-effective solution to power infrastructure upgrades, advancing climate goals while supporting utilities and customers alike.
Point-of-care cardiovascular assessment for earlier detection of preeclampsia and heart failure in at-risk pregnant patients
Principal investigators: Lihong Mo (lead PI, UC Davis Health), Dongyu Liu (UC Davis)
Cardiovascular disease (CVD) is the leading cause of illness and death for pregnant people, but early detection methods are often costly and hard to access. Electrocardiogram (ECG) testing, while common, can be ineffective in pregnant patients, even when they suffer from CVD symptoms such as shortness of breath and palpitations. This project seeks to design machine learning algorithms that can distinguish between pregnant and nonpregnant individuals based on multiple ECG parameters and detect preeclampsia and heart failure at an early stage. The team will rely on joint learning models that combine broad statistical features with individual patterns in ECG signals, allowing researchers to examine both overall trends and detailed, short-term changes. They will also develop an interactive visualization system to help researchers and clinicians understand the data. By grounding the diagnosis process in transparent, easily understood signals, this solution will improve health outcomes for pregnant patients.
Restoring speech perception in older adults using biosignals, machine learning and augmented reality
Principal investigators: Lee Miller (lead PI, UC Davis), Ahmed Arif (UC Merced)
Understanding speech in noisy backgrounds is the greatest daily challenge for half a billion people with hearing loss, most of them older adults. This struggle to communicate can introduce a cascade of health problems, from social isolation and depression to cognitive impairment and dementia. While hearing aids boost volume, they fail to make speech more distinguishable in precisely the loud, dynamic situations where they are needed most. This project will develop an augmented reality (AR) system that incorporates the eyes, ears and brain to substantially enhance speech comprehension for listeners with hearing loss. The team’s wearable device will leverage selective attention and auditory-visual integration, creating an “acoustic spotlight” to boost sound in the direction of a user’s gaze. Combined with real-time captioning and AR to emphasize facial information, the technology has the potential to restore communication and quality of life to millions.