Nina Kajiji


Nina’s 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” ( and “AI and Data Science in Applied Security and Investment Management” (


B.Com University of Bombay, India (1980)
MBA University of Rhode Island (1982)
M.S. in Statistics, University of Rhode Island (1991)
Ph.D. Applied Mathematics, University of Rhode Island (2001)
pstat® Accredited Professional StatisticianTM (2013-2018)

Selected Publications

  • Journal Articles

    Dash Jr., Gordon H., and Kajiji N. On Multiobjective Combinatorial Optimization and Dynamic Interim Hedging of Efficient Portfolios. International Transactions in Operational Research, Forthcoming, 2014.

  • Kajiji, Nina and Dash, Jr., Gordon H. On the Behavioral Specification and Multivariate Neural Network Estimation of Cognitive Scale Economies. Journal of Applied Operational Research, Vol 5(1) 2013.
  • Dash Jr., Gordon H., and Kajiji N. Efficient Multivariate Modeling of Cross Border Effects in the European Bond Volatility Spillover: A Multiple Objective Artificial Neural Network Approach. Lecture Notes in Management Science, Vol 4. July 2012.


Edited Works and Book Chapters


  • Kajiji, Nina and Dash, Jr. Gordon H. Computational Practice: Multivariate Parametric or Nonparametric Modeling of European Bond Volatility Spillover? Recent Advances in Computational Finance, Edited by: N. Thomaidis, and G. Dash. Nova Science Publishers, Inc. 2013
  • Kajiji, Nina and Forman, John. Production of Efficient Wealth Maximization Using Neuroeconomic Behavioral Drivers and Continuous Automated Trading, Recent Advances in Computational Finance, Edited by: N. Thomaidis, and G. Dash. Nova Science Publishers, Inc. 2013.
  • Dash Jr., Gordon H., and Kajiji, Nina. Engineering a Generalized Neural Network Mapping of Volatility Spillovers in European Government Bond Markets, Handbook of Financial Engineering, Series: Springer Optimization and Its Applications, Vol. 18, Edited By: C. Zopounidis, M. Doumpos, and P. Pardalos, Springer, 2008.