Naval Surface Warfare Center - Dahlgren Division(NSWCDD)

Laboratory Coordinator

Kyle Lackinger
17632 Dahlgren Road Suite 201
Dahlgren, VA 22448-5154
kyle.lackinger@navy.mil

The Naval Surface Warfare Center Dahlgren Division (NSWCDD)'s mission is to deliver warfare systems to protect our nation and defeat our adversaries.  Research, development, test and evaluation, analysis, systems engineering, integration and certification of complex naval warfare systems is performed by NSWCDD’s scientists and engineers.  NSWCDD conducts basic research in all systems-related areas.  Specific areas of emphasis include physics, mathematics, laser and computer technology, software, mechanical, electrical and systems engineering, human/systems integration, and system safety.  As a premier naval scientific and engineering institution, Dahlgren technology is critical to new design concepts for current ships and for systems integration and interoperability for the U.S. Navy.

With locations in Dahlgren and Dam Neck, Virginia, NSWCDD is the largest federal R&D employer in the state of Virginia. With over 5,000 federal employees – over 80% of whom execute technical projects – NSWCDD has created a tradition and culture of innovation.

The 2022 Summer Faculty Research Program has identified nine specific opportunities listed below for faculty to consider. When applying for a specific position, please include the name and email address for the POC related to the position.  

There may be additional opportunities available under the NSWCDD Technical Capabilities ** a URL is provided with the listing of current Technical Capabilities. Please contact Mr. Kyle Lackinger (kyle.lackinger@navy.mil) for more information.

Please Note: NSWCDD's Summer Faculty Research Program requires participants to be United States Citizens. Dual citizenship will be considered on a case by case basis.

Job Descriptions for SFRP 2022:

1: Title: Analysis of Large, High Dimensional, Complex Data Sets 
POC: Dr. Dave Marchette, david.marchette@navy.mil

Job Description: The analysis of large, high dimensional, complex data sets is important for a myriad of applications. One of the basic tools of analysis involves using graphs to encode local structure, then applying various techniques from linear algebra, geometry and topology to either embed the data into a lower dimensional space or to extract global information about the data.  Various mathematical techniques are relevant including, but not limited to, spectral graph embedding, multidimensional scaling, manifold learning, and topological data analysis. 

This work could go in several different directions depending on the interests of the candidate, including: methodologies aimed at specific types of inference such as classification, clustering or model selection; understanding the connection between the local structure of the graph, spectral embedding techniques and topological invariants; methods to utilize topological structure to determine the correct embedding space – which could mean the dimension of the embedding or the topology of the space into which one should embed; methods for embedding a point cloud into a given topological space and methods for performing inference in that space; utilizing local scale estimates to construct better graph filtrations (or to construct a single "best" graph) for defining the complex used in the topological calculations; more general theories for how to select the best spectral embedding techniques for a given inference task; efficient algorithms for computing homologies for large data sets or graphs. The above discussion provides some indication of the scope of our interest, but a summer project would likely only touch on one aspect of one of these areas. 

Place of performance is Naval Surface Warfare Center Dahlgren Division, Dahlgren, VA.
Number of Professors Desired:  1
Technical Department willing to fund accompanying student:  No
Number of students funded ($10K - $12K depending on educational level [Soph – Grad students]):  0

 

2: Title: Deep Neural Network (DNN) and related algorithm research 
POC: Dr. Dave Marchette, david.marchette@navy.mil

Task Description:  The desired research addresses the development of mathematical tools to better understand deep neural networks (DNN) and related algorithms. These networks are universal approximators with an extremely large set of parameters. Arguing from analogy with polynomial fits, one would expect that DNNs would suffer from overfitting and sever errors outside of the range of the training data, and yet there is considerable evidence that these algorithms are somewhat robust to these problems. With that said, there are also many examples of DNNs making extremely strange decisions on specially constructed examples. Thus we seek tools, derived from probability and statistics, linear algebra, linear and non-linear functional analysis, manifold discovery and learning, and other mathematical domains in order to analyze, predict and explain the behavior of deep neural networks. This project will focus on one such set of tools, as indicated by the area of expertise of the professor, and utilize these tools to provide insight into the family of models represented by deep neural networks.

Place of performance is Naval Surface Warfare Center Dahlgren Division, Dahlgren, VA.
Number of Professors Desired:  1
Technical Department willing to fund accompanying student:  No
Number of students funded ($10K - $12K depending on educational level [Soph – Grad students]):  0

 

3: Title: Safety Assurance of AI Intensive Systems
POC:  Dr. Rani Kady, rani.kady@navy.mil

Task Description: Artificial intelligence (AI) is a transformative technology that holds promise for tremendous benefits. DoD interest in AI has recently increased due to military challenges that the US is facing and the advancement of AI in industry. One of the National Artificial Intelligence R&D Strategic Plan strategies calls for AI systems to operate safely and securely in a controlled, well-defined, and well-understood manner. Further progress in research is needed to address this challenge of creating reliable, dependable, and trustworthy AI systems.

Current analyses and techniques associated with software safety coupled with rapidly increasing DoD systems complexity have led to an engineering gap in the application of system safety in AI-based military systems.  In order to adequately evolve the system safety discipline in AI-based military applications, system safety practitioners seek dynamic, configurable and cost effective safety analyses and techniques for use in defining AI contribution to system risk and mitigating related risks of AI-based military systems.

The selected faculty member would be responsible for developing and demonstrating system safety analysis techniques to allow robust risk characterization of AI capabilities.  This should include dynamic, configurable, and cost effective verification and validation techniques for AI-based military systems that can be implemented to measure level of contribution to system risk.

Place of performance is Naval Surface Warfare Center Dahlgren Division, Dahlgren, VA.
Number of Professors Desired:  1
Technical Department willing to fund accompanying student:  No
Number of students funded ($10K - $12K depending on educational level [Soph – Grad students]):  0

 

4: Title: Summer Seminar Series in Data Analytics and Machine Learning
POC: Barry Stevens, barry.stevens@navy.mil

Job Description: Provide 10 weekly 90-minute seminars via Microsoft Teams (guest access provided) covering topics in simulations for readiness and training systems.  Envisioned topics include: Overview of Data Analytics and Machine Learning focusing on typical application (1-2 sessions), regression, classification methods, feature reduction, neural networks, supervised learning, unsupervised learning, real-time analytics, radiofrequency machine learning and others to be proposed.  Demonstration of functioning examples is desired.  Following the lecture will be an availability for individual or small group consultation for nominally 30 minutes.  Lecturer will provide a web location for attendee download of lecture material and other material as applicable and project consultation as time allows.

Place of performance is Naval Surface Warfare Center Dahlgren Division, Dam Neck, VA
Number of Professors Desired:  1
Technical Department willing to fund accompanying student:  No
Number of students funded ($10K - $12K depending on educational level [Soph – Grad students]):  0

 

5: Title: Summer Seminar Series in Cybersecurity
POC: Tammy Krum, tammy.krum@navy.mil

Job Description: Provide 10 weekly 90-minute seminars or via Microsoft Teams (guest access provided) covering topics in simulations for readiness and training systems.  Envisioned topics include: Zero Trust, Applying Cybersecurity to Industrial Control Systems and Weapon Systems, Cloud Security, Analyzing Vulnerabilities in context of System Architecture, Understanding various attack vectors, Building cyber resiliency and others to be proposed.  Following the lecture will be an availability for individual or small group consultation for nominally 30 minutes.  Lecturer will provide a web location for attendee download of lecture material and other material as applicable and project consultation as time allows. 

Place of performance is Naval Surface Warfare Center Dahlgren Division, Dam Neck, VA
Number of Professors Desired:  1
Technical Department willing to fund accompanying student:  No
Number of students funded ($10K - $12K depending on educational level [Soph – Grad students]):  0

 

6: Title: Radiofrequency (RF) Engineering 

POC: Mike O’Brien, michael.w.obrien@navy.mil

Job Description: Investigation of the application of wireless communication technologies, such as Software Defined Radios (SDR). The applied research will be used to optimize the performance and further enhance current and future SDR applications, such as spectrum monitoring applications, data communication capabilities, and cybersecurity applications. The various Navy applications that use RF technologies to accomplish critical missions need to continue to be updated with emerging wireless technologies that are current being explored on SDR platforms, such as cognitive radio systems, dynamically adapt transmitted waveforms, beamforming, and Multiple Input Multiple Output (MIMO) transceiver architectures. 

Place of performance is Naval Surface Warfare Center Dahlgren Division, Dam Neck, VA
Number of Professors Desired:  2
Technical Department willing to fund accompanying student:  No
Number of students funded ($10K - $12K depending on educational level [Soph – Grad students]):  0

 

7: Title: Systems Safety Engineering Curriculum Development and Integration
POC: Tiffany Johnson, tiffany.a.johnson1@navy.mil

Job Description: The selected professor will assist in reviewing and improving current in-house workforce development curriculum and content as well as evaluating them for transition to academic courses that could be incorporated into an undergraduate and/or graduate level systems engineering program.  As no undergraduate degree, concentration, or certificate program exists for system safety engineering as practiced by the Department of Defense, organizations such as NSWCDD are challenged with long-lead times of employee development in a high demand environment. The NSWCDD Systems Safety Engineering Division (R40) has developed a complete Workforce Development curriculum of approximately 16 courses that teaches employees systems safety engineering principles, methods, and MIL-STD-882E analyses. 

Place of performance is Naval Surface Warfare Center Dahlgren Division, Dahlgren, VA
Number of Professors Desired:  1
Technical Department willing to fund accompanying student:  Yes
Number of students funded ($10K - $12K depending on educational level [Soph – Grad students]):  1

 

8: Title: Intelligent Automation for Mission Assurance
POC: Kathleen Young, Kathleen.Young@navy.mil

Job Description: The Mission and Assurance Decision Support System (MADSS) provides an integrated Command, Control and Communications (C3) operational and critical infrastructure relationships understanding by correlating data from different data sources, using micro services, secure network and automated data transformation services. MADSS provides improved responsiveness and predictive capability, rapid event analysis, and Warfighter analysis of alternatives development for network and critical infrastructure outages.

The selected faculty will conduct applied research to bring intelligent automation techniques (Intersection of artificial intelligence, machine learning and automation) to enhance the data processing, transformation, and analytics required for object and object-object relationship pattern recognition. 

Place of performance is Naval Surface Warfare Center Dahlgren Division, Dahlgren, VA
Number of Professors Desired:  1
Technical Department willing to fund accompanying student:  No
Number of students funded ($10K - $12K depending on educational level [Soph – Grad students]):  0

 

9: Title: Human System Integration Technology Convergence
POC: Dr. Elizabet Haro, elizabet.haro@navy.mil

Job Description: The Intelligent Automation group provides a holistic approach for digital transformation through collaborative convergence of technologies for rapid delivery to the Fleet. The selected faculty will conduct applied research and development for Human System Integration, including data analytics with virtual reality interface designs. Innovation in human factors, gestural interfaces, biomechanics, system safety, health hazards, personnel survivability, manpower, training, and habitability and enhanced affordability. Additionally, innovation in explainable Artificial Intelligence, specifically, capturing human important features into deep learning algorithms, and surrogate modeling. 

Place of performance is Naval Surface Warfare Center Dahlgren Division, Dahlgren, VA
Number of Professors Desired:  1
Technical Department willing to fund accompanying student:  No
Number of students funded ($10K - $12K depending on educational level [Soph – Grad students]):  0

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Additional opportunities may exist that align with NSWCDD Technical Capabilities and these can be found here: 

https://www.navsea.navy.mil/Home/Warfare-Centers/NSWC-Dahlgren/What-We-D...