RiskEcon Lab @ Courant Institute NYU

The mission of RiskEcon® Lab @ 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 for distributed, embedded and autonomous systems.

David K.A. Mordecai was Invited to Present at the Courant Center for Atmosphere Ocean Science

David K.A. Mordecai was Invited to Present at the Courant Center for Atmosphere Ocean Science

Dr. David K.A. Mordecai was invited to present at the Courant Institute for Mathematical Sciences NYU Center for Atmosphere Ocean Science (CAOS) at the Atmosphere Ocean Science Colloquium on October 27, 2021.

The presentation by Dr. David Mordecai was entitled Multi-resolution Remote-Sensing and Data Fusion for Multi-Modal Estimation of Mesoscale Terrestrial Atmospheric Scattering Fields: Statistical Models and Applications to Risk Domains.

Synopsis
Although severe convective storms (SCSs) have been customarily classified as “secondary perils” by the insurance sector, it is particularly noteworthy that during the previous 10 years, SCSs have contributed more than half of global insured losses from secondary perils, and during 2020, such secondary perils account for more than 70% of the natural catastrophe insured losses (resulting mostly from SCSs and wildfire occurrences). Reliably modeling region-specific hazards of mesoscale climate risks related to SCSs at relevant temporal and spatial scales – among other industrial and municipal exposures to such climate-driven conditions (e.g., air quality, urban wind fields, flash flooding, drought, wildfire propagation), including impairment to energy grid stability and transportation networks – is inherently a joint-hypothesis problem. At mesoscales, e.g., within ranges greater than 5 km up to 200km and less than 1000km (Fujita 1981), predominant atmospheric instabilities (thermal, symmetric, barotropic, Kelvin-Helmholtz, etc.) contributing to storm propensities are highly state-dependent.

Given these geospatial complexities, the propensity and propagation of mesoscale severe convective storms are subject to prevailing localized spatial and temporal conditions. In the absence of robust statistical sampling, reliable estimation and classification of such storm occurrences at these temporal and spatial scales cannot be viably numerically simulated. Remote statistical measurements at relevant temporal and spatial mesoscales involve 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. However, the physics and geometric properties of these signals (e.g., RayleighMie and Bragg scattering) across a range of respective emission wavelengths tend to covary relative to composite atmospheric particle size and shape distributions.

David K.A. Mordecai was Invited to Present at the Courant Center for Atmosphere Ocean Science

Dr. Mordecai is President and Co-Founder of Risk Economics, and Visiting Scholar at Courant Institute of Mathematical Sciences NYU, advising research activities at RiskEcon® Lab for Decision Metrics @ Courant Institute.

About Center for Atmosphere Ocean Science
The Center for Atmosphere Ocean Science is a unit of the Department of Mathematics, within the Courant Institute of Mathematical Sciences NYU. Their mission is to advance the understanding of and ability to predict the coupled atmosphere, ocean and ice system through the use of mathematical and computational tools and analysis of observations; and to train the next generation of leading theoretical and computational climate scientists to face one of the most consequential problems of the 21st century. For more information, visit: https://caos.cims.nyu.edu/.

About Risk Economics
Risk Economics provides advisory services at the intersection of commercial business-process engineering and risk engineering with a particular focus on coupling commercial reinsurance and financial technology, through the rigorous application of agent-based, demographic, and statistical methodologies to microeconomic and macroeconomic analytics.

David K.A. Mordecai was Invited to Present at the Courant Center for Atmosphere Ocean Science Read More »

David K.A. Mordecai was Invited to Speak at the Joint Quantum Symposium

David K.A. Mordecai was Invited to Speak at the Joint Quantum Symposium

David K.A. Mordecai, President of Risk Economics and Adjunct Professor at New York University (NYU), was invited to speak at the Joint Quantum Symposium held at NYU on April 5-6, 2018.

David Mordecai participated on a panel entitled Future of Quantum Information, where he highlighted and discussed prospective domain-specific RiskTech use-case applications for quantum devices and related nanotechnologies within Artificial Intelligence (AI), autonomous systems control, industrial Internet of Things (IoT) and remote sensing.

The panel was introduced by Paul Horn, Senior Vice Provost for Research at NYU and Senior Vice Dean for Strategic Initiatives and Entrepreneurship at the NYU Tandon School of Engineering.

The other speakers on the panel were the following:

Quantum

About Risk Economics
Risk Economics is a New York based advisory firm founded in 1999, providing advisory services at the intersection of commercial business-process engineering and risk engineering with a particular focus on coupling commercial reinsurance and financial technology, through the rigorous application of agent-based, demographic, and statistical methodologies to microeconomic and macroeconomic analytics.

About RiskEcon® Lab for Decision Metrics
The mission of RiskEcon® Lab @ 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.

David K.A. Mordecai was Invited to Speak at the Joint Quantum Symposium Read More »

David K.A. Mordecai Presented an Applied Mathematics Seminar at Courant Institute of Mathematical Sciences NYU

David K.A. Mordecai Presented an Applied Mathematics Seminar at Courant Institute of Mathematical Sciences NYU

David K.A. Mordecai presented an Applied Mathematics Seminar at Courant Institute of Mathematical Sciences NYU entitled (Not So) Distant Cousins: Some Common Statistical Relations Underlying Models Across Disparate Social Processes.

Dr. Mordecai’s presentation at Courant Institute compared and contrasted specific models within political science, mathematical and economic sociology, economics, and finance in order to highlight and discuss the intuition underlying certain common statistical properties that describe information dissemination and aggregation, as well as structural innovation and behavioral propagation (e.g. cultural evolution, strategic response, imitation and technical adoption) across agent-based systems. The intent was to motivate and suggest areas for future interdisciplinary research.

David K.A. Mordecai Presented an Applied Mathematics Seminar at Courant Institute of Mathematical Sciences NYU

David K.A. Mordecai Presented an Applied Mathematics Seminar at Courant Institute of Mathematical Sciences NYU Read More »

RiskEcon® Lab for Decision Metrics has been Established at Courant Institute of Mathematical Sciences NYU

RiskEcon® Lab for Decision Metrics has been Established at Courant Institute of Mathematical Sciences NYU

RiskEcon® Lab for Decision Metrics (RiskEcon® Lab) has been established at Courant Institute of Mathematical Sciences NYU, in order to apply a range of computational methods to researching geopolitical and socioeconomic issues, such as aging and health trends, immigration, and consumer behavior.

The primary focus of RiskEcon® Lab will be to cultivate NYU’s competency in computational statistics and to fund, foster, promote, and direct research that applies tools and methods from machine learning, data-mining, and text-mining to large scale real world geopolitical and socioeconomic problems related to demographics and macroeconomics. These include financial, labor, housing, consumption, and trade effects of consumer behavior as well as global population, immigration, environmental, epidemiological, aging, and health trends. In addition to promoting research, other activities of the RiskEcon® Lab will involve advancing development of the field via interdisciplinary postgraduate graduate research and education.

RiskEcon® Lab will be housed within the newly established Center for Computational Economics and Algorithmic Data Analytics (CEcADA) at Courant Institute.

RiskEcon® Lab for Decision Metrics has been Established at Courant Institute of Mathematical Sciences NYU

For additional information, see the following:

RiskEcon® Lab for Decision Metrics has been Established at Courant Institute of Mathematical Sciences NYU Read More »