Publications

We present an approach for designing correct-by-construction neural networks (and other machine learning models) that are guaranteed to be consistent with a collection of input-output specifications before, during, and after algorithm training. Our method involves designing a constrained predictor for each set of compatible constraints, and combining them safely via...

The AI revolution is data driven. AI "data wrangling" is the process by which unusable data is transformed to support AI algorithm development (training) and deployment (inference). Significant time is devoted to translating diverse data representations supporting the many query and analysis steps found in an AI pipeline. Rigorous mathematical...

Spatial beamforming using distributed arrays of RF sensors is treated. Unlike the observations from traditional RF antenna arrays, the distributed array's data can be subjected to widely varying time and frequency shifts among sensors and signals. These shifts require compensation upon reception in order to perform spatial filtering. To perform...

Small Unmanned Aircraft Systems (sUAS) offer many potential benefits to society but also pose a dangerous mid-air collision hazard. Safely integrating into shared airspace will require sUAS to perform Collision Avoidance (CA), one of the primary components of Detect and Avoid (DAA) technologies. This paper performs a Monte Carlo simulation...

As unmanned aircraft systems (UASs) continue to integrate into the U.S. National Airspace System (NAS), there is a need to quantify the risk of airborne collisions between unmanned and manned aircraft to support regulation and standards development. Both regulators and standards developing organizations have made extensive use of Monte Carlo...

In this paper, we first show how general microgrid can be modeled as a negative feedback configuration comprising two subsystems. The first subsystem is the interconnected microgrid grid which is affected through negative feedback by the second subsystem consisting of all single-port components. This is modeled by transforming physical state...

This document represents the SRE19 AV submission by the team composed of JHU-CLSP, JHU-HLTCOE and MIT Lincoln Labs. All the developed systems for the audio and videoconditions consisted of Neural network embeddings with some flavor of PLDA/cosine back-end. Primary fusions obtained Actual DCF of 0.250 on SRE18 VAST eval, 0.183...

We propose a novel graph matching algorithm that uses ideas from graph signal processing to match vertices of graphs using alternative graph representations. Specifically, we consider a multi-scale heat diffusion on the graphs to create multiple weighted graph representations that incorporate both direct adjacencies as well as local structures induced...

When we are faced with challenging image classification tasks, we often explain our reasoning by dissecting the image, and pointing out prototypical aspects of one class or another. The mounting evidence for each of the classes helps us make our final decision. In this work, we introduce a deep network...

Identifying and profiling threat actors are high priority tasks for a number of governmental organizations. These threat actors may operate actively, using the Internet to promote propaganda, recruit new members, or exert command and control over their networks. Alternatively, threat actors may operate passively, demonstrating operational security awareness online while...