Applied Risk Management:
Valuation of Derivatives under AI and Data Science Technologies

Gordon H Dash and Nina Kajiji

Nina Kajiji, MBA, MS, PhD, pstat
Chief Data Scientist & Principal , The NKD Group, Inc.
Adjunct Professor, Computer Science & Statistics, Univ. of Rhode Island

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Dr. Nina Kajiji holds a B.Com. (1980) from Bombay University, India; an MBA (1982), a M.S. in Statistics (1991), and a Ph.D. Applied Mathematics (2001), from the University of Rhode Island, USA.  She is the Principal of The NKD Group, Inc. She is also an adjunct associate professor in the Computer Science and Statistics Department at the University of Rhode Island.  She has been conferred the title Accredited Professional Statistician™ from the American Statistical Association.

Her principal research interests are in applied optimization, volatility modeling, and artificial intelligence (AI). Application fields include: socially responsible investing, modeling risk, neuroscience-based modeling for the development of smart cities, ‘big data’ analysis of intra-day municipal bond yield curves, and obtaining complex educational assessment elasticity metrics. Her research continues to expand to include ‘big data’ analytics featuring visualization, high-performance computing, and explainable AI (XAI) to assist in complex data mining. Dr. Kajiji’s academic research has been published in several operational research journals, finance journals, and, most recently, in the journal Neuroscience. Besides contributing several book chapters, Nina is currently co-authoring two e-Books titled “Applied Risk Management: Valuation of Derivatives under AI and Data Science Technologies” (www.ARMDAT.com) and “AI and Data Science in Applied Security and Investment Management” (www.aisimbook.online).

Nina is the co-architect of the cloud-based computing platform, WinORSe-AI 2021. The computing platform is geared towards solving problems using techniques commonly used in financial engineering, statistics, operations research, and economics. Research models using WinORSe-AI have been presented to capital market professionals in Italy, India, Thailand, South Africa, Lithuania, Turkey, and the UK. Some specialized techniques incorporated in WinORSe-AI 2021 are combinatorial non-linear goal programming, Bayesian enhanced regularized univariate and multivariate radial basis neural network, Explainable AI (XAI) using SHAP, and more.

Nina has taught courses in Statistics, Time Series Analysis, Operations Research, and Finance at various Universities in the U.S. and internationally. She is a member of the Greek-based RiskGroupAuth, an interdisciplinary research group (think-tank) specializing in developing risk assessment and management tools for modern energy systems. She has also given keynote addresses at international research meetings.

When not actively working, her personal interests center on container gardening and volunteering with non-profit organizations that promote girl education across the K-12 population. For her volunteer work, Nina has been awarded The President’s Volunteer Service Award (Gold Level) from the President’s Council on Service and Civic Participation.  Nina was also honored with the 2013-14 Woman of the Year Award from National Association of Professional Women. She currently serves as the co-Chair of the European Working Group on Operational Research for Development (EWG-ORD)Personal Website: www.ninakajiji.net

 

Updated: 31-Aug-2024

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