Table of Contents

• Predictive Digital Twins: Where Dynamic Data-Driven Learning Meets Physics-Based ModelingMichael G. Kapteyn, Karen E. Willcox. 3-7 [doi]
• Dynamic Data-Driven Application Systems for NASA's Science Mission DirectorateMichael S. Seablom, Florence W. Tan, Jacqueline LeMoigne-Stewart. 8-11 [doi]
• Revisiting the Top Ten Ways that DDDAS Can Save the World with an Update in the BioInfoSciences Area and on the Energy BridgeShiyan Wang, Sangtae Kim. 12-17 [doi]
• Using Dynamic Data Driven Cyberinfrastructure for Next Generation Disaster IntelligenceIlkay Altintas. 18-21 [doi]
• Intelligent Contingency Management for Urban Air MobilityIrene M. Gregory, Newton H. Campbell, Natasha A. Neogi, Jon B. Holbrook, Jared A. Grauer, Barton J. Bacon, Patrick C. Murphy, Daniel D. Moerder, Benjamin M. Simmons, Michael J. Acheson, Thomas C. Britton, Jacob W. Cook. 22-26 [doi]
• A Dynamic Data Driven Applications Systems (DDDAS)-Based Digital Twin IoT FrameworkSarah Malik, Rakeen Rouf, Krzysztof Mazur, Antonios Kontsos. 29-36 [doi]
• A Hardware Testbed for Dynamic Data-Driven Aerospace Digital TwinsStefanie J. Salinger, Michael G. Kapteyn, Cory Kays, Jacob V. R. Pretorius, Karen E. Willcox. 37-45 [doi]
• A DDDAS Protocol for Real-Time Large-Scale UAS Flight CoordinationDavid Sacharny, Thomas C. Henderson, EJay Guo. 49-56 [doi]
• Data-Driven State Awareness for Fly-by-Feel Aerial Vehicles via Adaptive Time Series and Gaussian Process Regression ModelsShabbir Ahmed, Ahmad Amer, Carlos A. Varela, Fotis Kopsaftopoulos. 57-65 [doi]
• Integrated Planning, Decision-Making, and Weather Modeling for UAS Navigating Complex WeatherJohn J. Bird, Katherine Glasheen, Eric W. Frew. 66-73 [doi]
• Microgrid Operational Planning Using Deviation Clustering Within a DDDAS FrameworkJoshua Darville, Nurcin Celik. 77-84 [doi]
• Dynamic Data-Driven Self-healing Application for Phasor Measurement Unit NetworksYanfeng Qu, Xin Liu, Jiaqi Yan, Dong Jin. 85-92 [doi]
• Interpretable Deep Attention Model for Multivariate Time Series Prediction in Building Energy SystemsTryambak Gangopadhyay, Sin Yong Tan, Zhanhong Jiang, Soumik Sarkar. 93-101 [doi]
• Overcoming Stealthy Adversarial Attacks on Power Grid Load Predictions Through Dynamic Data RepairXingyu Zhou, Robert Canady, Yi Li, Xenofon D. Koutsoukos, Aniruddha Gokhale. 102-109 [doi]
• Uncertainty Analysis of Self-healed Composites with Machine Learning as Part of DDDASSameer B. Mulani, Samit Roy, Bodiuzzaman Jony. 113-120 [doi]
• Active Search Methods to Predict Material Failure Under Intermittent Loading in the Serebrinksy-Ortiz Fatigue ModelStephen Guth, Themistoklis Sapis. 121-131 [doi]
• Dynamic Data-Driven Distribution Tracking of Nanoparticle MorphologyChiwoo Park, Yu Ding 0002. 132-139 [doi]
• Machine Learning Algorithms for Improved Thermospheric Density ModelingHerbert Turner, Maggie Zhang, David Gondelach, Richard Linares. 143-151 [doi]
• Dynamic Transfer Learning from Physics-Based Simulated SAR Imagery for Automatic Target RecognitionAli Ahmadibeni, Branndon Jones, Damiyelle Smith, Amir Shirkhodaie. 152-159 [doi]
• Uncertainty Estimation for Semantic Segmentation of Hyperspectral ImageryAneesh Rangnekar, Emmett J. Ientilucci, Christopher Kanan, Matthew J. Hoffman. 163-170 [doi]
• Spectral Super Resolution with DCT Decomposition and Deep Residual LearningRaghunath Sai Puttagunta, Renlong Hang, Zhu Li 0001, Shuvra S. Bhattacharyya, George York. 171-178 [doi]
• Active Scene Classification via Dynamically Learning Prototypical ViewsZachary A. Daniels, Dimitris N. Metaxas. 179-187 [doi]
• Informative Ensemble Kalman Learning for Neural StructureMargaret Trautner, Gabriel Margolis, Sai Ravela. 191-199 [doi]
• Reachability Analysis Based Tracking: Applications to Non-cooperative Space Object TrackingZach Hall, Puneet Singla. 200-207 [doi]
• Sparse Regression and Adaptive Feature Generation for the Discovery of Dynamical SystemsChinmay S. Kulkarni, Abhinav Gupta, Pierre F. J. Lermusiaux. 208-216 [doi]
• Improving Prediction Confidence in Learning-Enabled Autonomous SystemsDimitrios Boursinos, Xenofon D. Koutsoukos. 217-224 [doi]
• Physics-Based SAR Modeling and Simulation for Large-Scale Data Generation of Multi-platform Vehicles for Deep Learning-Based ATRBranndon Jones, Ali Ahmadibeni, Maxine Beard, Amir Shirkhodaie. 227-235 [doi]
• Towards Provably Correct Probabilistic Flight SystemsElkin Cruz-Camacho, Saswata Paul, Fotis Kopsaftopoulos, Carlos A. Varela. 236-244 [doi]
• Dynamic Data-Driven Formal Progress Envelopes for Distributed AlgorithmsSaswata Paul, Fotis Kopsaftopoulos, Stacy Patterson, Carlos A. Varela. 245-252 [doi]
• Dynamic Sensor Processing for Securing Unmanned VehiclesRaul Quinonez, Luis E. Salazar, Jairo Giraldo, Alvaro A. Cárdenas. 253-261 [doi]
• A Scalable Mixture Model Based Defense Against Data Poisoning Attacks on ClassifiersXi Li, David J. Miller 0001, Zhen Xiang, George Kesidis. 262-273 [doi]
• Resilient Machine Learning (rML) Ensemble Against Adversarial Machine Learning AttacksLikai Yao, Cihan Tunc, Pratik Satam, Salim Hariri. 274-282 [doi]
• Data-Based Defense-in-Depth of Critical SystemsStyliani Pantopoulou, Pola Lydia Lagari, Clive H. Townsend, Lefteri H. Tsoukalas. 283-290 [doi]
• Physics-Driven Machine Learning for Time-Optimal Path Planning in Stochastic Dynamic FlowsRohit Chowdhury, Deepak N. Subramani. 293-301 [doi]
• Discovering Laws from Observations: A Data-Driven ApproachChenzhong Yin, Gaurav Gupta, Paul Bogdan. 302-310 [doi]
• An On-Demand Weather Avoidance System for Small Aircraft Flight Path RoutingEric Lyons, David Westbrook, Andrew Grote, George Papadimitriou, Komal Thareja, Cong Wang 0014, Michael Zink, Ewa Deelman, Anirban Mandal, Paul Ruth. 311-319 [doi]
• Dynamic, Data-Driven Hyperspectral Image Classification on Resource-Constrained PlatformsLei Pan, Rijun Liao, Zhu Li 0001, Shuvra S. Bhattacharyya. 320-327 [doi]
• Semi-supervised Visual Tracking Based on Variational Siamese NetworkLiang Xu, Ruixin Niu. 328-336 [doi]
• Occlusion Detection for Dynamic AdaptationZachary Mulhollan, Aneesh Rangnekar, Anthony Vodacek, Matthew J. Hoffman. 337-344 [doi]
• PNEUMON: A DDDAS Framework to Detect Fatigue and Dyspnea in COPDVarun Kanal, Andrew Miller, Diego Vester, Jackson Liller, Maria Kyrarini, Glenn Wylie, Michael J. Falvo, Fillia Makedon. 345-352 [doi]
• Impact of DDDAS/InfoSymbiotics in the Industrial SectorDaniel Abramovitch, Sandeep Gogineni, Cory Kays, Chung-Sheng Li, Jose Moreira, Chitra Sivanandam, Nurali Virani. 355 [doi]
• AI/ML Applications for Aerospace and DefenseKishore K. Reddy, Amit Surana, Paul Kodzwa, Shane Zable, Richard LaRowe, Eric Brewer, Steven Burd. 356 [doi]
• Future Direction of DDDAS/InfoSymbiotics and Collaborations with Related InitiativesErik Blasch, Robert Bohn, Jahla Gato, Edward L. McLarney, Jasmin Ratchford, Sonia Sachs. 357 [doi]