Algorithm Performance Evaluation with Low Sample Size ($49,995), NGA, 2021-2022, PI
• Redesign and Implementation of USDS-Proxy Language – Phase II+Option ($53,091/$509,997), ARiA, 2021-2023, Co-PI (PI: Charles Wallace)
• Continuation: Machine Learning and Artificial Intelligence Using Acoustic Sensors in Connected Vehicles and Roadside Units ($150,000), Ford Motor Company, 2021-2022
• SCC-CIVIC-PG Track B: Helping Rural Counties to Enhance Flooding and Coastal Disaster Resilience and Adaptation ($4,080/$49,999), NSF, 2021, Co-PI (PI: Thomas Oommen)
• Redesign and Implementation of USDS-Proxy Language ($17,231/$76,610), ARiA, 2020, Co-PI (PI: Charles Wallace)
• Modeling and Algorithm Development for Adaptive Adversarial AI for Complex Autonomy ($428,707), US Army ERDC, 2020-2022, PI
• DURIP: Acoustic Sensing System and High-Throughput Computing for Environment and Threat Monitoring in Naval Environments Using Machine Learning ($243,169), Office of Naval Research, 2020-2021, PI
• Machine Learning and Artificial Intelligence Using Acoustic Sensors in Connected Vehicles and Roadside Units ($149,518), Ford Motor Company, 2020-2021, PI
• Defending the Nation’s Digital Frontier: Cybersecurity Training for Tomorrow’s Officers ($66,377/$248,517), Office of Naval Research, 2020-2021, Co-PI (PI: Andrew Barnard)
• Duty Cycle Aggregation, Warranty Mitigation, and Fleet Prognostics using Customer Usage Data (Part II) ($199,847), Ford Motor Company, 2020-2022, PI
• Algorithms for Look-Down Infrared Target Exploitation – Phase II ($399,994), NGA, 2020-2022, PI
• Machine Learning for Human-Based Visual Detection Metrics ($120,000), Signature Research Inc., 2020-2021, PI
• Localization, Tracking, and Classification of On-Ice and Underwater Noise Sources Using Machine Learning ($299,533), Naval Undersea Warfare Center, 2019-2022, PI
• Duty Cycle Aggregation and Warranty Mitigation using Customer Usage Data ($50,000), Ford Motor Company, 2019, PI
• Algorithms for Look-Down Infrared Target Exploitation ($99,998), NGA, 2018-19, PI
• Distributed Array Processing for Aperture Level STAR ($50,000), MIT Lincoln Laboratory, 2017-18, PI
• Self-Interference Modeling in Active Phased Arrays ($15,000), MIT Lincoln Laboratory, 2017, PI
• Multistatic GPR Phase II ($100,000), Akela, Inc. / US Army SBIR, 2017-19, PI
• Multisensor Analysis and Algorithm Development for Detection and Classification of Buried and Obscured Targets ($99,779), Army Research Office, 2016-2019, PI
• Implementation of Unmanned Aerial Vehicles (UAVs) for Assessment of Transportation Infrastructure ($87,620/$598,526), Michigan DOT, 2016-2019, Co-PI (PI: Colin Brooks)
• Multistatic GPR for Explosive Hazards Detection ($49,987), Akela, Inc. / US Army SBIR, 2016-2017, PI
• Heterogeneous Multisensor Buried Target Detection Using Spatiotemporal Feature Learning ($381,200), Army Research Office, 2015-2018, PI
Explainable deep fusion, ISR-2 Seminar Series: Advancing Toward Modern Detection and Estimation Theory, Los Alamos National Laboratory (July, 2020)
Introduction to Deep Learning, GSG Programming Seminar Series, Michigan Tech Graduate Student Government (July, 2020)
Introduction to Machine Learning with Python, GSG Programming Seminar Series, Michigan Tech Graduate Student Government (July, 2020)
Explainable deep fusion, Technological University of Eindhoven (May, 2019)
Interpretable deep fusion using non-linear deep learning architectures, Ford M.C. (March, 2019)
Making sense of deep fusion using explainable AI, NGA (January, 2019)
Agile simultaneous transmit and receive phased arrays, AFRL (November, 2018)
How to win on trivia night: sensor fusion beyond the weighted average, AFIT (November, 2018)
How to win on trivia night: sensor fusion beyond the weighted average, MIT LL (July, 2018)
How to win on trivia night: sensor fusion beyond the weighted average, CCC (May, 2018)
How to win on trivia night: sensor fusion beyond the weighted average, U. Mich. (March, 2018)
Sensor fusion and radar signal processing, Argo AI (February, 2018)
