Publications

This paper describes a feature-rich model of data relevance, designed to aid first responder retrieval of useful information from social media sources during disasters or emergencies. The approach is meant to address the failure of traditional keyword-based methods to sufficiently suppress clutter during retrieval. The model iteratively incorporates relevance feedback...

Direct-write printing allows the fabrication of centimeter-wave radio devices. Most polymer dielectric polymer materials become lossy at frequencies above 10 GHz. Presented here is a printable dielectric material with low loss in the K a band (26.5–40 GHz). This process allows the fabrication of resonator filter devices and a radio...

We describe a novel key-centric processor architecture in which each piece of data or code can be protected by encryption while at rest, in transit, and in use. Using embedded key management for cryptographic key handling, our processor permits mutually distrusting software written by different entities to work closely together...

The ability to collect and analyze large amounts of data is a growing problem within the scientific community. The growing gap between data and user calls for innovative tools that address the challenges faced by big data volume, velocity, and verity. While there has been great progress in the world...

Spectroscopic ellipsometry is demonstrated to be an effective technique for assessing the quality of plasmonic resonances within aluminum nanostructures deposited with multiple techniques. The resonance quality of nanoplasmonic aluminum arrays is shown to be strongly dependent on the method of aluminum deposition. Three-layer metal-dielectric-metal nanopillar arrays were fabricated in a...

This chapter focuses on state-of-the-art provably secure cryptographic techniques for protecting big data applications. We do not focus on more established, and commonly available cryptographic solutions. The goal is to inform practitioners of new techniques to consider as they develop new big data solutions rather than to summarize the current...

In this paper, we present a pipeline for named entity extraction and linking that is designed specifically for noisy, grammatically inconsistent domains where traditional named entity techniques perform poorly. Our approach leverages a large knowledge base to improve entity recognition, while maintaining the use of traditional NER to identify mentions...

In this paper, we explore the problem of recognizing named entities in microposts, a genre with notoriously little context surrounding each named entity and inconsistent use of grammar, punctuation, capitalization, and spelling conventions by authors. In spite of the challenges associated with information extraction from microposts, it remains an increasingly...

We propose a novel RF signal classification method based on sparse coding, an unsupervised learning method popular in computer vision. In particular, we employ a convolutional sparse coder that can extract high-level features by computing the maximal similarity between an unknown received signal against an overcomplete dictionary of matched filter...

This article reviews MIT Lincoln Laboratory's work over the past 20 years to develop photon-sensitive image sensors based on arrays of silicon Geiger-mode avalanche photodiodes. Integration of these detectors to all-digital CMOS readout circuits enable exquisitely sensitive solid-state imagers for lidar, wavefront sensing, and passive imaging.