DDDAS2022 Main-Track Plenary Presentations -- Aerospace I -- Generalized multifidelity active learning for Gaussian-process-based reliability analysis -- Essential Properties of a Multimodal Hypersonic Object Detection and Tracking System -- Aerospace II -- Dynamic Airspace Control via Spatial Network Morphing -- Towards the formal verification of data-driven flight awareness: Leveraging the Cramér-Rao lower bound of stochastic functional time series models -- Coupled Sensor Configuration and Path-Planning in a Multimodal Threat Field -- Space Systems -- Probabilistic Admissible Region Based Track Initialization -- Radar cross-section modeling of space debris -- High Resolution Imaging Satellite Constellation -- Network Systems -- Reachability Analysis to Track Non-cooperative Satellite in Cislunar Regime -- Physics-Aware Machine Learning for Dynamic, Data-Driven Radar Target Recognition -- DDDAS for Optimized Design and Management of Wireless Cellular Networks -- Systems Support Methods -- DDDAS-based Learning for Edge Computing at 5G and Beyond 5G -- Monitoring and Secure Communications for Small Modular Reactors -- Data Augmentation of High-Rate Dynamic Testing via a Physics-Informed GAN Approach -- Unsupervised Wave Physics-Informed Representation Learning for Guided Wavefield Reconstruction -- Passive Radio Frequency-based 3D Indoor Positioning System via Ensemble Learning -- Deep Learning - I -- Deep Learning Approach for Data and Computing Efficient Situational Assessment and Awareness in Human Assistance and Disaster Response and Damage Assessment Applications -- SpecAL: Towards Active Learning for Semantic Segmentation of Hyperspectral Imagery -- Multimodal IR and RF based sensor system for real-time human target detection, identification, and Geolocation -- Deep Learning - II -- Learning Interacting Dynamic Systems with Neural Ordinary Differential Equations -- Relational Active Feature Elicitation for DDDAS -- Explainable Human-in-the-loop Dynamic Data-Driven Digital Twins -- Tracking -- Transmission Censoring and Information Fusion for Communication-Efficient Distributed Nonlinear Filtering -- Distributed Estimation of the Pelagic Scattering Layer using a Buoyancy Controlled Robotic System -- Towards a data-driven bilinear Koopman operator for controlled nonlinear systems and sensitivity analysis -- Security -- Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach -- Dynamic Data-Driven Digital Twins for Blockchain Systems -- Adversarial Forecasting through Adversarial Risk Analysis within a DDDAS Framework -- Distributed Systems -- Power Grid Resilience: Data Gaps for Data-Driven Disruption Analysis -- Attack-resilient Cyber-physical System State Estimation for Smart Grid Digital Twin Design -- Applying DDDAS Principles for Realizing Optimized and Robust Deep Learning Models at the Edge -- Keynotes -- Keynotes Overview -- DDDAS for Systems Analytics in Applied Mechanics -- Computing for Emerging Aerospace Autonomous Vehicles -- From genomics to therapeutics: Single-cell dissection and manipulation of disease circuitry -- Data Augmentation to Improve Adversarial Robustness of AI-Based Network Security Monitoring -- Improving Predictive Models for Environmental Monitoring using Distributed Spacecraft Autonomy -- Towards Continual Unsupervised Data Driven Adaptive Learning -- DDDAS2022 Main-Track: Wildfires Panel -- Wildfires Panel Overview -- Using Dynamic Data Driven Cyberinfrastructure for Next Generation Disaster Intelligence -- Simulating large wildland & WUI fires with a physics-based weather-fire behavior model: Understanding, prediction, and data-shaped products -- Autonomous Unmanned Aerial Vehicle systems in Wildfire Detection and Management-Challenges and Opportunities -- Role of Autonomous Unmanned Aerial Systems in Prescribed Burn Projects -- Towards a Dynamic Data Driven Wildfire Digital Twin (WDT): Impact on Deforestation, Air Quality and Cardiopulmonary Disease -- Earth System Digital Twin for Air Quality -- Dynamic Data Driven Applications for Atmospheric Monitoring and Tracking -- Workshop on Climate, Life, Earth, Planets -- Dynamic Data-Driven Downscaling to Quantify Extreme Rainfall and Flood Loss Risk -- DDDAS 2022 Conference Agenda -- Agenda, DDDAS 2022, October 6-10. -- .

This book constitutes the refereed proceedings of the 4th International Conference on Dynamic Data Driven Applications Systems, DDDAS 2022, which took place in Cambridge, MA, USA, during October 6-10, 2022. The 31 regular papers in the main track and 5 regular papers from the Wildfires panel, as well as one workshop paper, were carefully reviewed and selected for inclusion in the book. They were organized in following topical sections: DDAS2022 Main-Track Plenary Presentations; Keynotes; DDDAS2022 Main-Track: Wildfires Panel; Workshop on Climate, Life, Earth, Planets.