Publications
Toward distributed control for reconfigurable robust microgrids
Summary
Summary
Microgrids have been seen as a good solution to providing power to forward-deployed military forces. However, compatibility, robustness and stability of current solutions are often questionable. To overcome some of these problems, we first propose a theoretically-sound modeling method which defines common microgrid component interfaces using power and rate of...
Image processing pipeline for liver fibrosis classification using ultrasound shear wave elastography
Summary
Summary
The purpose of this study was to develop an automated method for classifying liver fibrosis stage >=F2 based on ultrasound shear wave elastography (SWE) and to assess the system's performance in comparison with a reference manual approach. The reference approach consists of manually selecting a region of interest from each...
Weather radar network benefit model for nontornadic thunderstorm wind casualty cost reduction
Summary
Summary
An econometric geospatial benefit model for nontornadic thunderstorm wind casualty reduction is developed for meteorological radar network planning. Regression analyses on 22 years (1998–2019) of storm event and warning data show, likely for the first time, a clear dependence of nontornadic severe thunderstorm warning performance on radar coverage. Furthermore, nontornadic...
A multi-task LSTM framework for improved early sepsis prediction
Summary
Summary
Early detection for sepsis, a high-mortality clinical condition, is important for improving patient outcomes. The performance of conventional deep learning methods degrades quickly as predictions are made several hours prior to the clinical definition. We adopt recurrent neural networks (RNNs) to improve early prediction of the onset of sepsis using...
GraphChallenge.org triangle counting performance [e-print]
Summary
Summary
The rise of graph analytic systems has created a need for new ways to measure and compare the capabilities of graph processing systems. The MIT/Amazon/IEEE Graph Challenge has been developed to provide a well-defined community venue for stimulating research and highlighting innovations in graph analysis software, hardware, algorithms, and systems...
GraphChallenge.org sparse deep neural network performance [e-print]
Summary
Summary
The MIT/IEEE/Amazon GraphChallenge.org encourages community approaches to developing new solutions for analyzing graphs and sparse data. Sparse AI analytics present unique scalability difficulties. The Sparse Deep Neural Network (DNN) Challenge draws upon prior challenges from machine learning, high performance computing, and visual analytics to create a challenge that is reflective...
Hardware foundation for secure computing
Summary
Summary
Software security solutions are often considered to be more adaptable than their hardware counterparts. However, software has to work within the limitations of the system hardware platform, of which the selection is often dictated by functionality rather than security. Performance issues of security solutions without proper hardware support are easy...
Leveraging linear algebra to count and enumerate simple subgraphs
Summary
Summary
Even though subgraph counting and subgraph matching are well-known NP-Hard problems, they are foundational building blocks for many scientific and commercial applications. In order to analyze graphs that contain millions to billions of edges, distributed systems can provide computational scalability through search parallelization. One recent approach for exposing graph algorithm...
Towards a distributed framework for multi-agent reinforcement learning research
Summary
Summary
Some of the most important publications in deep reinforcement learning over the last few years have been fueled by access to massive amounts of computation through large scale distributed systems. The success of these approaches in achieving human-expert level performance on several complex video-game environments has motivated further exploration into...
A hardware root-of-trust design for low-power SoC edge devices
Summary
Summary
In this work, we introduce a hardware root-of-trust architecture for low-power edge devices. An accelerator-based SoC design that includes the hardware root-of-trust architecture is developed. An example application for the device is presented. We examine attacks based on physical access given the significant threat they pose to unattended edge systems...