Publications

Patent litigation is an expensive and time-consuming process. To minimize its impact on the participants in the patent lifecycle, automatic determination of litigation potential is a compelling machine learning application. In this paper, we consider preliminary methods for the prediction of a patent being involved in litigation using metadata, content...

Today's infrastructure as a service (IaaS) cloud environments rely upon full trust in the provider to secure applications and data. Cloud providers do not offer the ability to create hardware-rooted cryptographic identities for IaaS cloud resources or sufficient information to verify the integrity of systems. Trusted computing protocols and hardware...

Automatic extraction of intelligent and useful information from data is one of the main goals in data science. Traditional approaches have focused on learning from structured features, i.e., information in a relational database. However, most of the data encountered in practice are unstructured (i.e., social media posts, forums, emails and...

A new DARPA program called Data Driven Discovery of Models (D3M) aims to develop automated model discovery systems that can be used by researchers with specific subject matter expertise to create empirical models of real, complex processes. Two major goals of this program are to allow experts to create empirical...

Machine learning methods in Human Language Technology have reached a stage of maturity where widespread use is both possible and desirable. The MIT Lincoln Laboratory LLTools software suite provides a step towards this goal by providing a set of easily accessible frameworks for incorporating speech, text, and entity resolution components...

Unlike current chemical trace detection technology, dogs actively sniff to acquire an odor sample. Flow visualization experiments with an anatomically-similar 3D printed dog's nose revealed the external aerodynamics during canine sniffing, where ventral-laterally expired air jets entrain odorant-laden air toward the nose, thereby extending the "aerodynamic reach" for inspiration of...

This work monetizes the environmental benefits of Terminal Flight Data Manager (TFDM) capabilities which reduce fuel burn and gaseous emissions, and in turn reduce climate change and air quality effects. A methodology is created which takes TFDM "engines-on" taxi time savings and converts them to fuel and carbon dioxide (CO2)...

Experimentalists seeking to improve the coherent lifetimes of quantum bits have generally focused on mitigating decoherence mechanisms through, for example, improvements to qubit designs and materials, and system isolation from environmental perturbations. In the case of the phase degree of freedom in a quantum superposition, however, the coherence that must...

Vector sensor imaging presents a challenging problem in covariance estimation when allowing arbitrarily polarized sources. We propose a Stokes parameter representation of the source covariance matrix which is both qualitatively and computationally convenient. Using this formulation, we adapt the proximal gradient and expectation maximization (EM) algorithms and apply them in...

Building secure systems used to mean ensuring a secure perimeter, but that is no longer the case. Today's systems are ill-equipped to deal with attackers that are able to pierce perimeter defenses. Data provenance is a critical technology in building resilient systems that will allow systems to recover from attackers...