Research Improving Trustworthiness of Deep Learning Models Validation techniques and interpretability frameworks for reliable, accountable deep learning. Space Signal Propagation Optimization Deep learning methods for optimizing transmission efficiency in space signal propagation. Hate Speech Detection Machine learning approaches for detecting hate speech in online text. Galaxy Morphological Classification Vision models for classifying galaxy morphology from astronomical imagery. Integrating Symbolic and Sub-Symbolic Algorithms Combining symbolic reasoning with sub-symbolic (neural) learning methods. Artificial Intelligence for Computer Security Applying AI techniques to computer security problems. Explaining Deep Learning with Background Knowledge (XBack) Using structured background knowledge to explain deep learning model behavior. Combining Symbolic and Sub-Symbolic Artificial Intelligence Broader research program on hybrid neuro-symbolic AI methods. Explainable Machine Reasoning through the Application of Linked Data (EMERALD) DoD/Air Force-funded research on explainable machine reasoning with linked data. Recovering the Sources of Individual Differences Unduly-named Errors (ReSIDUE) DARPA-funded research on individual differences in human performance data. Deep Learning Execution Time Improvement Improving deep learning model execution time at Intel Corporation. Human Centered Big Data (HCBD) Ohio Federal Research Network project on human-centered big data analytics. Explaining AI Decisions Industry research on explaining AI model decisions at Accenture Technology Labs. Advancing Software Tools for Ontology Development NSF-funded development of software tools for ontology engineering. Software ECII Knowledge-graph-based concept induction software; pivotal to $1M in DARPA/AFRL funding. OWLAx A Protégé plugin for visual ontology development through diagramming. ROWLTab A Protégé plugin that converts SWRL rules to OWL axioms.