The world of the 21st century is increasingly complex and fraught with risk. Disruptions related to geopolitical activity, national security, artificial intelligence, data security, financial crises, climate change, biological threats, environmental deterioration, and natural and man-made disasters, among other catalysts, are seemingly daily occurrences, with potential impacts across every commercial sector. As a result, decision making in the face of such uncertainty can be paralyzing to individuals and corporations alike.
At Atlas Research Innovations, we partner with an experienced team of global leaders across a variety of disciplines to take an alternative data-driven and science-based approach towards complexity and risk. We attempt to change the conversation from one of risk and ruin to one of clarity and opportunity.
Dr. Michael Ferrari is the Managing Partner at Atlas Research Innovations and a Senior Fellow at the Wharton School at the University of Pennsylvania. He provides clients with basic and applied bespoke research services towards a variety of scientific, technical and economic domains. Most of this work falls at the food-water-energy-infrastructure nexus, and encompasses Data Science & Analytics, Spatial Informatics, AI/Machine Learning, Financial & Physical Risk, GeoEconomics, Sensor Networks, Environmental System Science and Engineering, Smart City & Earth Observation Technologies, and Information Theory.
Michael has spent his career as a scientist, engineer and economist in the following industrial sectors: energy and agriculture; FinTech, chemicals, water & natural resources, commodities & supply chain, and informatics.
Dr. Ferrari earned his PhD from Rutgers (Dept. of Env. Sciences & Engineering: programs in Geophysical Fluid Dynamics and Environmental Biophysical Modeling) where his research focused on better understanding the Industrial/Environmental interface and the Earth/Space/Biosphere complex from both an information systems and an evolutionary perspective. His doctoral work in numerical modeling & applied mathematics was supported by the NASA Goddard Institute for Space Studies.