Maryland Engineering Enters Into Five Year, $78.2M Agreement with the U.S. Army

Maryland Engineering Enters Into Five Year, $78.2M Agreement with the U.S. Army

Ask Don Woodbury, director of innovation and partnerships at the University of Maryland’s A. James Clark School of Engineering, about the school’s leadership in the U.S. Army DEVCOM Army Research Laboratory’s (ARL) Data Driven Engineering Research (DataDrivER) program, and he’ll sum it up succinctly: “We’re keeping engineering on the cutting edge.”

Earlier this year, ARL awarded Maryland Engineering a $78.2 million cooperative agreement over five years to spearhead an effort integrating data science and engineering. The Clark School–ARL partnership aims to devise better methods for performing data-intensive research, and accelerate the development of research outcomes for defense, AI/ML, and more. Examples include:

• Hardware and software that engage with and extract knowledge from massive data sets to improve decisions made by humans and autonomous systems.

• Advanced AI and ML algorithms and related analytics, giving people new tools to efficiently identify and extract key information.

• Visualization techniques that help people better absorb and interact with data, and the conclusions it suggests.

“Engineering and data science are merging. DataDrivER gives us a chance to make that merger happen more quickly,” Woodbury said.

Year one: microelectronics, big data and more

Six projects are planned for DataDrivER’s first year:

• Living Microelectronics – A Smart Nose: develop the first device that facilitates direct information transfer between biological sensors and a microelectronic interface to identify chemicals, biologicals, and/or pathogens.

• Multimodal Neural Dynamics Platform: design, build, and harness the unique capabilities of a living neural network to engineer hybrid AI architectures that share the efficiency, adaptability, and resilience of biological systems.   

• Classification and Information Retrieval in Massively Large Databases: investigate ultra-fast reservoir computing to parse very large datasets in real time to provide fingerprinting of radio frequency emitters. 

• Integrated Data-Driven and Model-Based Systems Engineering: add large data sets to a modeling environment to assess performance and cost impacts of alternative technologies like sensor suites or autonomy algorithms for an autonomous ground vehicle and design strategies on complex systems.

• Mobility Analytics and Sandbox: advance real-time fusion and visualization of data for anything that can move (vehicles, aircraft, equipment, medical supplies, etc.) and analytics that support improved decision and the more efficient movement of people, equipment, and supplies on complex, multi-modal networks. 

• Cyber-physical Systems Data Analytics and Sandbox: create tools that collect and assess large data streams from complex systems like connected and autonomous vehicles, robotics platforms, and UAVs, to identify and mitigate potential cyber threats. 

Innovation in the approach

In addition to its novel outcomes, the manner in which DataDivER operates is also novel: projects have an accelerated 18- to 24-month window to a laboratory prototype demonstration and are resourced to support this accelerated schedule.

“We have a fantastic foundation of fundamental research discoveries and a workforce that is at the leading edge of key emerging technologies. We can leverage our technology and workforce to efficiently deliver compelling research outcomes to our partners and sponsors in a timeframe that is not typical for university research,” Woodbury said, drawing a comparison to the pharmaceutical companies that leveraged past research inventions to speed up development of a COVID-19 vaccine.

UMD’s close proximity to ARL provides unique opportunities for collaborations that will leverage the personnel, instrumentation, and facilities of each organization to achieve their common research objectives.

“We seek impactful innovations and discovery with our research, exploring new possibilities and multidisciplinary solutions in every engineering discipline—from industrial AI to autonomous systems that better serve our service members. DataDrivER has that kind of ambitious aim,” Clark School Dean Samuel Graham, Jr. said. “We hope our ARL partnership serves as inspiration for other collaborations inside and outside our university, and look forward to jointly creating new solutions that merge big data and classical engineering.”

May 25, 2023