Dr. Daniel Arnold

Biography

Daniel Arnold is an Adjunct Professor specializing in Civil Environmental Engineering at the University of California, Berkeley. His research concentrates on control strategies for managing distributed energy resources and improving the stability and security of electric power distribution systems utilizing advanced data science tools. Arnold applies machine learning techniques to analyze high-resolution data from Phasor Measurement Units (PMUs). He is recognized as an emerging leader in integrating artificial intelligence and control strategies into energy systems. Alongside his academic responsibilities, Arnold leads a research group at the Lawrence Berkeley National Laboratory, where he engages in peer reviewing for leading journals and participates in workshops that translate research into actionable insights. Arnold possesses a strong grounding in optimizing cyber-physical systems and addressing vulnerabilities within energy infrastructures, including developing control algorithms that utilize non-compromised system components to enhance resilience against unintended outages. His ongoing work seeks to extend the application of adaptive control methods to broad-scale energy systems to prevent incidents like blackouts.

Research Interests