Scholars Selected for Oral Presentations

at 2018 ARCS Symposium on May 7

To register for this year’s May 7th symposium, click here

University of California, Berkeley

“AlterWear: BatteryFree Wearable Displays for Opportunistic Interactions”

Stanford University

“Quantification of Heterogeneity in Geomaterials Using Multiscale Imaging”

  • Shabnam Semnani
  • PI: Ronaldo I. Borja / Civil and Environmental Engineering
  • Read Abstract →

San Francisco State University

“Ecological effects of active revegetation in a San Francisco Bay salt marsh restoration site”

  • Margot Buchbinder
  • PI: Katharyn Boyer / Biology – Estuary and Ocean Science
  • Read Abstract →

University of California, San Francisco

“Propagating Individual Electronic Medical Records Through A Knowledge Network To Generate Deep Patient Stratification And Accelerate Precision Medicine”

  • Charlotte Nelson
  • PI: Sergio Baranzini & Atul Butte / Biology – Informatics
  • Read Abstract →

University of California, Davis

“Jumping Genes in Maize”

University of California, Santa Cruz

“Understanding Plankton Morphology with Computational Fluid Dynamics”

As the landscape of wearable devices continues to expand, power remains a major issue for adoption, usability, and miniaturization. Users are faced with an increasing number of personal devices to manage, charge, and care for. In this work, we argue that power constraints limit the design space of wearable devices. We present AlterWear: an architecture for new wearable devices that implement a battery-less design using electromagnetic induction via NFC and bi-stable ink displays. Although these displays are active only when in proximity to an NFC-enabled device, this unique combination of hardware enables both quick, dynamic and long-term interactions with persistent visual displays. We demonstrate new wearables enabled through AlterWear with dynamic, fashionforward, and expressive displays across several form factors, and evaluate them in a user study. By forgoing the need for onboard power, AlterWear expands the ecosystem of functional and fashionable wearable technologies.

To promote environmental and energy sustainability, it is crucial to reduce environmental impacts due to applications such as hydrocarbon recovery, unconventional energy resources and underground waste storage, along with enhancement of technologies such as carbon sequestration and geothermal energy. These applications require an understanding of the behavior of the involved geomaterials (i.e. soils and rocks) at multiple scales, and the ability to predict their behavior under various conditions. Geomaterials often consist of various phases that form complex structures persisting at multiple scales. Microstructural morphology of these materials has a great impact on their overall behavior such as deformation, failure and transport properties, and needs to be incorporated into the computational modeling efforts. In this work, we show how imaging techniques across different scales can be combined to determine microstructural morphology of geomaterials.

With the predicted acceleration of sea level rise, salt marsh restoration efforts are faced with the challenge of building and maintaining sufficient sediment to support vegetation. We planted earthen mounds at the Sears Point restoration site on the north San Pablo Bay using native Pacific cordgrass, Spartina foliosa. We hypothesized that S. foliosa would stabilize sediments, reducing erosion and promoting sediment accretion, and that changes to soil due to vegetation would foster development of soil invertebrate communities valuable to marsh functions. We discuss the implications of our results for salt marsh restoration in the San Francisco Bay and other estuaries.

With recent technological advances, medical providers are being flooded with data from basic science research from multiple disciplines. Our ability to transform this data into usable medical knowledge is being held back by the lack of connections between the different data sources. In order to address this issue, several efforts to integrate these data sources in a single platform are ongoing. One of the most promising approaches makes use of heterogeneous networks. Heterogeneous networks are ensembles of connected entities with multiple types of nodes and edges. One such network, SPOKE (Scalable PrecisiOn Medicine Knowledge Engine), contains over five decades of biomedical research. Using Electronic Health Records (EHRs), we propagated patients’ connections through SPOKE and generated a network profile for each patient. These patient profiles are being used to stratify patients into a disease landscape. The ultimate goal of this disease landscape is for it to be used as a tool for uncovering novel biological level information, diagnosing patients, predicting patient trajectories, and designing tailored treatments.

Jumping genes were discovered in corn in the 1940’s when genetic crosses using different plants as parents yielded kernels with unexpected purple speckles. Today, we know these jumping genes are present across the tree of life, and generate mutations in plants and animals including humans. In the maize genome, jumping genes make up over 85% of all DNA, and I am studying how this abundance of jumping genes make mutations. Mutations are usually bad, but sometimes they make changes that are beneficial, particularly in response to agriculturally stressful environments like drought. I use DNA sequences from thousands of corn plants to find these mutations and their consequences.

The tintinnid (a species of zooplankton) has evolved an interesting way of getting its food: it waves cilia around its mouth in such a way that prey are simply funneled in and captured. In this study, I use computational fluid dynamics to simulate how this very special type of plankton feeds, and give insights on how the plankton's shape has evolved to optimize the effectiveness of this fascinating feeding mechanism.