David K.A. Mordecai presented at the Verification, Validation and Uncertainty Quantification Group

David K.A. Mordecai, Chief Scientist and Co-Managing Member of Numerati^® Partners presented at the Verification, Validation and Uncertainty Quantification (VVUQ) Group lunch convened on March 28, 2025.

The first part of his two-part invited presentation Weather Volatility, Transition Risk Exposure, and Credit Capacity addressed practical application of compound real options analysis and numerical optimization of temporal and spatial models from industrial economics for storage and transmission in the context of binding technical constraints related to comparative conversion rate efficiencies in the scalable deployment of low-carbon stochastic production.

The second part of his invited presentation Multi-resolution Remote-Sensing and Data Fusion for Multi-Modal Estimation of Mesoscale Terrestrial Atmospheric Scattering Fields: Statistical Models and Applications to Risk Domains discussed state estimation of the propensity and propagation of mesoscale severe convective storms, subject to prevailing localized spatial and temporal conditions at temporal and spatial scales which cannot be numerically simulated, as well as the role of remote statistical measurements at relevant temporal and spatial mesoscales. He highlighted the applicability and utility of sampling and assimilation of signals characterizing atmospheric composition based upon reflectivity, propagation, attenuation and doppler signatures of complementary acoustic, optical and radar-based emissions across a range of spectral bands, and under corresponding conditions of temperature, pressure and humidity.

David Mordecai is an Adjunct Professor of Econometrics and Statistics at the University of Chicago Booth School of Business and has been recently appointed as Adjunct Professor of Law teaching quantitative methods at NYU Law School. He also advises research activities at RiskEcon^® Lab @ Courant Institute of Mathematical Sciences NYU.

Jet Propulsion Laboratory (JPL) is the research and development lab federally funded by NASA and managed by Caltech.

The mission of RiskEcon^® Lab for Decision Metrics @ Courant Institute of Mathematical Sciences NYU is the development of experimental testbeds and analytics that employ high-dimensional datasets from innovative sources by applying a range of computational and analytical methods to commercial and industrial sensor networks and edge computing embedded systems, focusing primarily on research and development (R&D) of remote- and compressed- sensing, anomaly detection, forensic analytics and statistical process control. By employing applied computational statistics within the context of robust and scalable data analytic solutions, the goal is robust and reliable integration of machine learning with signal processing for measurement and control, in order to conduct research fundamental to large-scale, real-world questions in risk and liability management in the public interest. RiskEcon^® Lab for Decision Metrics was established in 2011 at Courant Institute of Mathematical Sciences, an independent division of New York University (NYU). Courant is considered to be one of the world’s leading mathematics educational and scientific research centers, and has been ranked first in research in applied mathematics. RiskEcon^® Lab is the cornerstone of the Computational Economics and Algorithmic Data Analytics (CEcADA) cooperative at New York University, established concurrently in 2011.