Pablo A. Moriano Salazar

Research Overview

Dr. Pablo Moriano is a computational scientist developing mathematical and data-driven methods for reliable, adaptive, and secure AI in complex scientific and cyber-physical systems. His research integrates machine learning, network science, anomaly detection, and cybersecurity to understand emerging failures and adversarial behavior, assess robustness under changing data and network structure, and support trustworthy autonomous decision-making. His methods have applications in connected-vehicle cybersecurity, scientific-computing telemetry, transportation safety, and software reliability.

Research Leadership and Projects

At ORNL, Dr. Moriano served as principal investigator of the three-year, $1.5 million Laboratory Directed Research and Development (LDRD) project Next-Generation Security for Interconnected Systems (2022–2025). The project developed adaptive anomaly-detection methods for interconnected cyber-physical systems.

He is a co-principal investigator of Sparsitute: A Mathematical Institute for Sparse Computations in Science and Engineering, a DOE Office of Science MMICC advancing sparse computation across scientific and engineering applications (2022–2027).

Selected Impact

Dr. Moriano has authored more than 40 peer-reviewed publications in cybersecurity, network science, and machine learning, including work published in IEEE Transactions on Information Forensics and Security, Physical Review Research, and IEEE Internet of Things Journal. His research has also produced U.S. patents and software copyrights in cybersecurity analytics and intrusion detection. His work has been recognized with ORNL Innovation Awards, best-paper awards, and the MGB–SIAM Early Career Fellowship.

Mentoring and Professional Service

Dr. Moriano mentors undergraduate, graduate, and postdoctoral researchers in data science, applied mathematics, cybersecurity, and engineering. His mentoring has supported research leading to publications, datasets, and software.

He contributes to the research community through professional service and scientific review, including the Mathematics in Computation Seminar Committee at ORNL, conference program committees, grant proposal review, and reviewing for journals in cybersecurity, machine learning, and network science.

Research Interests

• Artificial Intelligence and Machine Learning
• Anomaly Detection and Adversarial Learning
• Network and Data Science
• Cybersecurity for Cyber-Physical Systems
• Predictive Maintenance and Digital Twins

Publications

• Google Scholar profile

Laboratory and community service

• Member, Mathematics in Computation Seminar Committee, ORNL (2026–present)
• Member, CCSD Workforce Development Committee, ORNL (2024–2025)
• Organizer, SIAM Annual Meeting minisymposia (2024-2026)

Technical service

• Program committee member, ACM Workshop on Artificial Intelligence and Security (2024, 2025), and other selected conferences
• Reviewer for grant proposals for DOE/ASCR, LDRD, and the National Science Centre Poland

Professional Service

Reviewer for more than 40 journals across cybersecurity, machine learning, network science, and related fields. Selected journals include: ACM Computing Surveys; ACM Transactions on Cyber-Physical Systems; IEEE Transactions on Dependable and Secure Computing; IEEE Transactions on Information Forensics and Security; IEEE Transactions on Knowledge and Data Engineering; IEEE Transactions on Neural Networks and Learning Systems; IEEE Transactions on Network Science and Engineering; IEEE Transactions on Parallel and Distributed Systems; IEEE Transactions on Reliability; IEEE Transactions on Intelligent Transportation Systems; Computers & Security; Reliability Engineering & System Safety.