Dynamic Data Driven Applications Systems

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 Cram©r-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