Publications

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 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...

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...

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.

Superstorm Sandy illustrated the economic and human impact that severe weather can have on urban areas such as New York City. While flooding and wind damaged or destroyed some of the energy infrastructure, all installed microgrids in the New York City region remained operational during Sandy, including those at Princeton...

The conversion of electrical to mechanical power on a sub-centimeter scale is a key technology in many microsystems and energy harvesting devices. In this paper, we present a type of a capacitive energy conversion device that uses capillary pressure and electrowetting to reversibly convert electrical power to hydraulic power. These...

This technical report summarizes the operational observations recorded by MIT Lincoln Laboratory (MIT LL) aviation subject matter experts during the period 13 April to 31 October 2015. Three separate field observations were conducted over four convective weather days across the eastern National Airspace System (NAS) with visits to five separate...