Publications
Large-format Geiger-mode avalanche photodiode arrays and readout circuits
Summary
Summary
Over the past 20 years, we have developed arrays of custom-fabricated silicon and InP Geiger-mode avalanche photodiode arrays, CMOS readout circuits to digitally count or time stamp single-photon detection events, and techniques to integrate these two components to make back-illuminated solid-state image sensors for lidar, optical communications, and passive imaging...
Machine learning for medical ultrasound: status, methods, and future opportunities
Summary
Summary
Ultrasound (US) imaging is the most commonly performed cross-sectional diagnostic imaging modality in the practice of medicine. It is low-cost, non-ionizing, portable, and capable of real-time image acquisition and display. US is a rapidly evolving technology with significant challenges and opportunities. Challenges include high inter- and intra-operator variability and limited...
Trust and performance in human-AI systems for multi-domain command and control
Summary
Summary
Command and Control is one of the core tenants of joint military operations, however, the nature of modern security threats, the democratization of technology globally, and the speed and scope of information flows are stressing traditional operational paradigms, necessitating a fundamental shift to better concurrently integrate and operate across multiple...
XLab: early indications & warning from open source data with application to biological threat
Summary
Summary
XLab is an early warning system that addresses a broad range of national security threats using a flexible, rapidly reconfigurable architecture. XLab enables intelligence analysts to visualize, explore, and query a knowledge base constructed from multiple data sources, guided by subject matter expertise codified in threat model graphs. This paper...
Improving security at the system-call boundary in a type-safe operating system
Summary
Summary
Historically, most approaches to operating sytems security aim to either protect the kernel (e.g., the MMU) or protect user applications (e.g., W exclusive or X). However, little study has been done into protecting the boundary between these layers. We describe a vulnerability in Tock, a type-safe operating system, at the...
Classifier performance estimation with unbalanced, partially labeled data
Summary
Summary
Class imbalance and lack of ground truth are two significant problems in modern machine learning research. These problems are especially pressing in operational contexts where the total number of data points is extremely large and the cost of obtaining labels is very high. In the face of these issues, accurate...
Key Challenges and Prospects for Optical Standoff Trace Detection of Explosives
Summary
Summary
Sophisticated improvised explosive devices (IEDs) challenge the capabilities of current sensors, particularly in areas away from static checkpoints. This security gap could be filled by standoff chemical sensors that detect IEDs based on external trace explosive residues. Unfortunately, previous efforts have not led to widely deployed capabilities. Crucially, the physical...
Potential impacts of climate warming and increased summer heat stress on the electric grid: a case study for a large power transformer (LPT) in the Northeast United States
Summary
Summary
Large power transformers (LPTs) are critical yet vulnerable components of the power grid. More frequent and intense heat waves or high temperatures can degrade their operational lifetime and increase the risk of premature failure. Without adequate preparedness, a widespread situation could ultimately lead to prolonged grid disruption and incur excessive...
Detecting pathogen exposure during the non-symptomatic incubation period using physiological data
Summary
Summary
Early pathogen exposure detection allows better patient care and faster implementation of public health measures (patient isolation, contact tracing). Existing exposure detection most frequently relies on overt clinical symptoms, namely fever, during the infectious prodromal period. We have developed a robust machine learning based method to better detect asymptomatic states...
Peregrine: 3-D network localization and navigation
Summary
Summary
Location-aware devices will create new services and applications in emerging fields such as autonomous driving, smart cities, and the Internet of Things. Many existing localization systems rely on anchors such as satellites at known positions which broadcast radio signals. However, such signals may be blocked by obstacles, corrupted by multipath...