Dimitris Giovanis is an assistant research professor in the Department of Civil and Systems Engineering. He is a fellow of the Hopkins Extreme Materials Institute, and member of the Center on Artificial Intelligence for Materials in Extreme Environments, the Institute for Data Intensive Engineering and Science, and the Mathematical Institute for Data Science.
His research focuses on developing mathematical methodologies and computational tools and algorithms to accelerate and optimize simulation and analysis for scientific discovery and data-informed design, optimization, and decision making in science and engineering. His work integrates modern tools from scientific machine learning, data science, numerical analysis, and high-performance computing with uncertainty quantification to advance risk-informed predictive modeling.
Giovanis’ current projects range from materials science (amorphous solids, energetics, carbon-based composites, additive manufacturing) and natural hazards (performance-based earthquake/wind engineering, regional hazards, post-wildfire debris) to health (traumatic brain injury, digital twins of the human heart, epidemics) and aerospace (structural/aeroelastic).
Giovanis earned his five-year diploma in civil engineering, master’s degree in computational mechanics, and PhD—focused on stochastic finite element methods—from the National Technical University of Athens in Greece. Giovanis is a member of the NHERI Simulation Center, the American Society of Civil Engineer’s Engineering Mechanics Institute Probabilistic Methods Committee, the ASCE/EMI Machine Learning Group, the Society for Industrial and Applied Mathematics Uncertainty Quantification group, and the Greek Association of Computational Mechanics. He is a licensed Professional Civil Engineer in Greece and is also an assistant coach of the men’s water polo team at Johns Hopkins University.