The CITRIS Core Seed Funding program supports nascent ideas in information technology led by University of California researchers. This year’s awarded projects include smart clothing for anxiety, augmented reality for visual impairment, and digital mentorship for underrepresented minorities in STEM, among others.
We are excited to announce the CITRIS Core Seed Funding program awards for 2020. Competitive teams from the campuses of CITRIS and the Banatao Institute at UC Berkeley, Santa Cruz, Merced, Davis, and Davis Health submitted 68 proposals for innovative, early-stage collaborative projects. Seven teams each received a one-time award of up to $60,000 for interdisciplinary work that can lead to larger research programs and extramural grant proposals. Projects are designed to show results within a year.
The following projects were awarded seed funding:
Title: Data-Driven Fall Prevention and Intervention for Older Adults
PIs: JoAnn Seibles (UC Davis Health), Wan Du (UC Merced), Shijia Pan (UC Merced)
Preventing falls among older adults is an important issue for these individuals, as well as their families and caregivers. Although organizations have started offering fall-prevention programs, participation remains low. For example, over the last 10 years, participation in the Healthy Aging Association’s (HAA) Young-At-Heart (YAH) balance training in Stanislaus County, CA, has increased at a lower rate than the increase of its senior population. This project will design, implement, and test a system using Internet of Things (IoT) technology that can assess the fall risk of older adults by passively measuring a set of fall risk factors. The performance of the system will be validated in HAA YAH classes. The research findings are important for improving the well-being of older adults and reduce the social cost of fall treatments.
Title: Therapeutic Touch: Reactive Smart Clothing for Anxiety
PIs: Gozde Goncu-Berk (UC Davis), Philippe Raymond Goldin (UC Davis Health), Tingrui Pan (UC Davis)
Tactile sensory stimulation has been demonstrated to help calm people with anxiety disorders. Smart clothing and textiles have the potential to sense and collect physiological data about the wearer, and can also have embedded actuation capabilities such as promoting mechanical, electrical, and thermal tactile stimuli. This project aims to develop and test novel smart clothing with embedded textile-based actuating capabilities that deliver tactile stimulation in response to changes in the emotional state of a person with acute and long-term anxiety. The outcome will offer novel ways of complementing care for people with anxiety disorders.
Title: Enhancing Obstacle Visibility using a Head-Mounted Vision Aid for People with Low Vision
PIs: Emily Cooper (UC Berkeley), Roberto Manduchi (UC Santa Cruz)
Today, an estimated 5.7 million adults in the United States have a visual impairment with the vast majority of them having low vision. Since conditions that result in vision loss become more common with age, the number of people with low vision is expected to almost double by 2050. Despite a range of existing assistive tools, low vision adversely affects one’s ability to read, socialize, and walk safely and independently. This project will draw from previous work to address the challenge of obstacle avoidance during mobility for people with reduced peripheral vision. The team will design an enhancement system that uses emerging augmented reality (AR) technology to create minimally-obtrusive cues to help people with reduced peripheral vision detect and avoid obstacles in their path.
People and Robots
Title: Integrating Theory of Mind in AI Models: Strategy Discovery from Human Behavioral Data
PIs: Magy Seif El-Nasr (UC Santa Cruz), Kosa Goucher-Lambert (UC Berkeley)
As AI becomes integrated into systems used in our everyday life, new models integrating humanistic abilities become important. This project aims to develop a clear way to represent behavioral data in computational models. The overarching research goal is to develop a novel human-in-the-loop approach that integrates qualitative and quantitative inputs from humans into the computational process of modeling intent, strategies, and tactics as a graphical probabilistic model. CITRIS Seed Funding will support the first step: developing a novel language for representing complex dynamic behaviors, allowing experts to systematically and reliably model and update such behaviors based on human inputs.
Title: General Charger Feed Specification
PIs: Gil Tal (UC Davis), Timothy Lipman (UC Berkeley)
Lack of availability of charger data is a key challenge for electric vehicle (EV) users. Currently, charger data is kept in multiple formats by individual companies with little motivation to share data. This project will take initial steps for developing a feed specification for electric vehicle supply infrastructure (EVSE). It will include elements of computer science and data processing to guide the development of a lightweight and useful framework. Primary project elements include: 1) EV user survey; 2) assessment of available data; 3) development of system specifications; 4) review of best practices for data feed specifications; 5) development and implementation of a pilot specification and test, and 6) partnership with infrastructure funders to explore the potential of adding data sharing requirements to funding.
Future of Work
Title: Platforms and the Future of Work in Digitized Agriculture
PIs: Martin Kenney (UC Davis), M. Anne Visser (UC Davis), John Zysman (UC Berkeley), Catherine Keske (UC Merced)
As intelligent tools and systems are adopted in agriculture, California agriculturalists and workers will need to adapt and adjust. Data sharing can be used to create value by increasing transparency, traceability, and productivity. These benefits are predicated upon platform adoption. The conundrum is that, as the intermediary, the platform owner acquires significant power. This research examines five forms of platform organization and their benefits and drawbacks for actors in the agri-food system, farmers in particular. The types discussed are 1) startups, 2) agro-food industry firms, 3) agricultural cooperatives, 4) specially formed consortia of agri-food system actors, and 5) internet companies such as Google. The project will analyze the business models for each, assess likelihood of adoption, and effect on farmers and their practices.
Women in Tech
Title: The Impact of Shared Values and Power on Successful Mentoring for Under-Represented Minorities in STEM
PIs: Sarah McCullough (UC Davis), Erin Hestir (UC Merced), Anita Balaraman (UC Berkeley)
A chasm often lies between what is taught in the classroom and what students need to be successful. Mentorship provides a vehicle for raising greater expectations by students and gauging whether a student is prepared to be successful in post-graduate academic endeavors or in the world of work. Unfortunately, mentorship remains a hidden pedagogy in undergraduate and graduate education, and beyond. This project aims to study the characteristics of mentoring programs that benefit historically underrepresented minorities in STEM and increase their retention and continuation in STEM fields. The program will study the impact of a digital mentorship program, enabling mentees to gain professional development skills and garner career advice during COVID-19 given social distancing requirements and across geographic barriers.
Through this competitive seed funding program, CITRIS and the Banatao Institute have catalyzed promising new technology projects. Since 2008, CITRIS Core Seed Funding has supported 168 projects and over 380 researchers from all CITRIS campuses, resulting in extramural funding up to four times the initial investment within four years of completion.
The Center for Information Technology Research in the Interest of Society (CITRIS) and the Banatao Institute drive interdisciplinary innovation for social good with faculty researchers and students from four University of California campuses – Berkeley, Davis, Merced, and Santa Cruz – along with public and private partners.
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