Posted: 02-06-2024

Location: U.S. Army Combat Capabilities Development Command – Aberdeen Proving Ground, MD

Level: Graduate student 

General Topic: Computer Science

Description of Research: Distributed ML analytic applications leverage multiple devices to optimize analytic performance at the expense of greater network and compute resource usage. However, compared to single device analytics, distributed analytic applications are more susceptible to dynamics in resource-constrained, dynamic environments because of the increased number of devices and network links involved. This project will explore methods to mitigate the impacts of degraded resources in ML analytic applications. Specifically, the participant(s) will work with DEVCOM ARL scientists to investigate, develop, and analyze adaptive ML analytic algorithms in resource-constrained, dynamic environments The participant(s) will have exposure and hands on experience with software development using Python, ML packages (PyTorch,Tensorflow) and data science packages (numpy, pandas), as well as analysis using visualization tools including Grafana, seaborn, and matplotlib.

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