Publications
Colorization of H&E stained tissue using deep learning
Summary
Summary
Histopathology is a critical tool in the diagnosis and stratification of cancer. Digital Pathology involves the scanning of stained and fixed tissue samples to produce high-resolution images that can be used for computer-aided diagnosis and research. A common challenge in digital pathology related to the quality and characteristics of staining...
Mission assurance: beyond secure processing
Summary
Summary
The processor of a drone runs essential functions of sensing, communications, coordination, and control. This is the conventional view. But in today's cyber environment, the processor must also provide security to assure mission completion. We have been developing a secure processing architecture for mission assurance. A study on state-of-the-art secure...
Curator: provenance management for modern distributed systems
Summary
Summary
Data provenance is a valuable tool for protecting and troubleshooting distributed systems. Careful design of the provenance components reduces the impact on the design, implementation, and operation of the distributed system. In this paper, we present Curator, a provenance management toolkit that can be easily integrated with microservice-based systems and...
A secure cloud with minimal provider trust
Summary
Summary
Bolted is a new architecture for a bare metal cloud with the goal of providing security-sensitive customers of a cloud the same level of security and control that they can obtain in their own private data centers. It allows tenants to elastically allocate secure resources within a cloud while being...
Lessons learned from a decade of providing interactive, on-demand high performance computing to scientists and engineers
Summary
Summary
For decades, the use of HPC systems was limited to those in the physical sciences who had mastered their domain in conjunction with a deep understanding of HPC architectures and algorithms. During these same decades, consumer computing device advances produced tablets and smartphones that allow millions of children to interactively...
On large-scale graph generation with validation of diverse triangle statistics at edges and vertices
Summary
Summary
Researchers developing implementations of distributed graph analytic algorithms require graph generators that yield graphs sharing the challenging characteristics of real-world graphs (small-world, scale-free, heavy-tailed degree distribution) with efficiently calculable ground-truth solutions to the desired output. Reproducibility for current generators used in benchmarking are somewhat lacking in this respect due to...
Next-generation embedded processors: an update
Summary
Summary
For mission assurance, Department of Defense (DoD) embedded systems should be designed to mitigate various aspects of cyber risks, while maintaining performance (size, weight, power, cost, and schedule). This paper reports our latest research effort in the development of a next-generation System-on-Chip (SoC) for DoD applications, which we first presented...
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...
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...
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...