2018 CITRIS Seed Funding Awards announced

We are delighted to announce the CITRIS Seed Funding Program awards for 2018. This year, 50 highly competitive teams from the four CITRIS campuses at UC Berkeley, Davis, Merced, and Santa Cruz submitted proposals for early-stage collaborative research projects.

Ten teams will receive a one-time award, averaging $60,000 each, for interdisciplinary work that can lead to larger research programs and extramural grant proposals. Winning proposals incorporate machine learning, data analytics and visualization, mapping, and sensors to advance smart energy and infrastructure, cultural preservation, patient care and screening, traffic management, and other timely applications in healthcare, sustainability, robotics, and democracy. Of the successful proposals, 90% of lead investigators are receiving their first Seed award and 100% are first-time lead PIs, and 80% of the projects include pre-tenured faculty members.

CITRIS has awarded annual seed grants to spur multi-campus, multidisciplinary collaborations among four University of California campuses since 2008. Numerous companies and centers have resulted from the program, including Cellscope, an imaging device that transforms ordinary cell phones into otoscopes for ear exams in the field; and the Center for Autonomous and Interactive Systems at UC Merced, which focuses on robotics, virtual characters, cognitive science, and human-computer interfaces.

Congratulations to faculty leaders of the 2018 CITRIS Seed Funding awards below.

Visualizing ancient Egyptian landscapes and material culture: Cultural contexts for immersive visualization and VR

Principal investigators: Rita Lucarelli (UC Berkeley), Elaine Sullivan (UC Santa Cruz)
Initiative: Connected Communities

Researchers will build 3D and 4D models of ancient Egyptian artifacts and landscapes so they can be navigated in their ancient contexts.

Mapping spatial inequality: Immigrants in poverty and community services

Principal investigators: Irene Bloemraad (UC Berkeley) and Veronica Terriquez (UC Santa Cruz)
Initiative: Connected Communities

Researchers will build a web app that shows the spatial mismatch between where immigrants live and where community immigrant organizations are.

Cloud-based anytime computation of reachable tubes for provably safe unmanned aerial systems traffic management

Principal Investigators: Abhishek Halder and Ricardo Sanfelice (UC Santa Cruz), Mark Mueller and Claire Tomlin (UC Berkeley)
Initiative: People and Robots

This project aims to develop a framework and associated tools for fast computation of the space-time reachable sets for multiple networked agents under uncertainty.

A sensor system for robotic monitoring and mapping of plant root and shoot health

Principal Investigators: Reza Ehsani (UC Merced), Alireza Pourreza (UC Davis)
Initiative: People and Robots

Researchers will build an unmanned ground robot to non-destructively monitor plant root size and density using X-ray technology.

WeCare: WiFi-enabled device-free activity monitoring platform for elderly healthcare and smart home automation

Principal Investigators: Han Zou and Ming Jin (UC Berkeley), Zhou Yu (UC Davis)
Initiative: Health

Researchers will develop a human-activity monitoring platform that infers users’ daily activities based on how human bodies intersect with ubiquitous WiFi signals.

Automation and deep learning for diabetic retinopathy screening

Principal Investigators: Glenn Yiu (UC Davis Medical Center), Stella Yu (UC Berkeley)
Initiative: Health

This project will develop a program for automated diabetic retinopathy screening at UC Davis Health (UCDH) using deep learning algorithms developed at UC Berkeley.

Predicting venous thromboembolism episodes using routine patient care data and machine learning techniques

Principal Investigators: Ted Wun (UC Davis Medical Center), Prabhu Shankar and Chen-Nee Chuah (UC Davis)
Initiative: Health

Using data collected during routine patient care and applying machine learning techniques, researchers will develop predictive models to identify patients with cancer who are at high risk to develop venous thromboembolism (VTE).

Persistent autonomous monitoring for early detection and prediction of wildfires

Principal Investigators: Katia Obraczka (UC Santa Cruz), Stefano Carpin (UC Merced), Scott Stephens (UC Berkeley)
Initiative: Sustainable Infrastructures

Researchers will design, deploy, test, and evaluate under real-world scenarios a novel IoT system to enable accurate, timely, and scalable wildfire detection and prediction.

Smart road corridors by meso-scale in-pavement distributed infrastructure sensing

Principal Investigators: Kenichi Soga (UC Berkeley), John Harvey (UC Davis)
Initiative: Sustainable Infrastructures

This project will use a dynamic distributed fiber-optic sensor technology as a novel system for vehicle detection and behavior analysis for complex road junctions and busy road corridors.

Using smart city and building-specific air quality data for improved indoor air quality and energy efficiency

Principal Investigators: Jovan Pantelic (UC Berkeley), Mark Modera (UC Davis), Wolfgang Rogge (UC Merced)
Initiative: Sustainable Infrastructures

Sensors providing building-specific air quality data will be used to improve natural ventilation efficiency and better optimize building control systems to ensure safe indoor air quality and improve energy efficiency.