Award Data

Deep Neural Networks have become ubiquitous in the modern analysis of voluminous datasets with geometric symmetries. In the field of Particle Physics, experiments such as DUNE require the detection of particle signatures interacting within the detector, with analyses of over a billion 3D event images per channel each year; with typical setups containing over 150,000 different channels.  In an ...

Software and hardware flaws can be exploited to make programs perform unintended computations or leak sensitive data. We propose to counter these threats by isolating libraries and other program units inside a single process. The developer will insert source-level annotations that i) map code and data units to compartments and ii) capture how each compartment is intended to interact with others, i ...

We propose to design, build and test genetic circuits and DNA constructs that will be expressed in human cells and that will ultimately have applications for the health of warfighters. The circuits will have physiological inputs representing, for example, (1) infection/sepsis, (2) altitude sickness or blood loss, and (3) radiation exposure; which will be mediated through signal transduction pathwa ...

Triton Systems, Inc. will work in collaboration with Professor Mark Yim of the University of Pennsylvania (UPenn) to design a viable, robust ground robot with novel, reconfigurable actuators. This robot can reconfigure from a wheeled state to a legged state, enabling it to overcome tall obstacles and rough terrain. This ground robot will also be of a modular nature, able to be combined with others ...

Metalenses, with their ability to arbitrarily control the amplitude and phase of light across a band of wavelengths, have the potential to disrupt imaging and communication systems which rely on traditional lenses to focus, collimate, and otherwise manipulate optical signals, and are under increasing pressure to operate with reduced size and weight. We propose to design, develop, and demonstrate a ...

Conventional methods for detecting pathogens, which are based on culturing the microorganism, are time-consuming and laborious. Machine learning provides an alternative path to identify pathogens using supervised learning algorithms. Most current computational tools utilize genomic or protein data to identify bacteria. These methods look for features in the whole genome that correlate to pathogeni ...

Stottler Henke proposes PaCT, leveraging our related past work in computer vision and machine learning. Drawing from techniques used in ExPATSS, a Phase II SBIR effort slated for transition to the Naval fleet, PaCT will perform bacterial characterization using features derived from the phenotype of the bacteria. PaCT will predict bacterial characteristics such as pathogenicity, antibiotic resistan ...

The goal of the research is to provide a solar-blind, deep-UV photo-detector array that can be used in instruments detecting chemical and biological agents, such as TAC-BIO II, using UV Raman and Fluorescence measurements. The overall approach is to develop a solid-state detector array that achieves the performance goals for QE (>70%), gain (>1E6), dark current (

StampPump is a postage-stamp-sized (27x27x6 mm), fully-self-contained, closed-loop insulin patch pump system that is filled at the factory with enough insulin to treat a person with T1- or trauma-induced hyperglycemia for a full week. The device is shelf stable for at least 90 days and so is compatible with critical-care or forward deployment use. We propose to augment this system with the ability ...

It is well established that hyperglycemia of critical illness, general glucose intolerance, and insulin resistance are common among critically ill patients, including those without a diagnosis of diabetes mellitus upon hospital admission. Such glycemic dysregulation has been linked to increased patient morbidity and mortality, and longer recovery times. Furthermore, tight glycemic control has been ...