Mission Statement

Our History

The NKD-Group is dedicated to the design, manufacture and distribution of analytical software to support quantitative decision makers.  We focus primarily on providing support to the academic teaching community. As financial modeling becomes more quantitatively demanding, The NKD-Group  has produced WinORS that excels in user-friendliness and educational user support.  Our goal is to make it straightforward for you, the application engineer, to use the WinORS product to investigate, apply, and interpret solutions to complex decision models in finance, financial engineering, and operations research.

The history of our commitment to software development dates back to the early 1980s under the DOS operating system.  Today we embrace  agile development principles in our consulting and software development .  The NKD-Group now specializes in developing business models in finance that integrate multivariate statistics, machine learning algorithms, artificial neural networks, data mining, and more to “big data.”

Nina Kajiji is a 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” and “AI and Data Science in Applied Security and Investment Management.”
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.
When not actively working, her personal interests center on container gardening and volunteering with non-profit organizations. She is the co-chair of the European Working Group on Operational Research for Development. 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.

Personal Website: www.ninakajiji.net

Dr. Gordon H. Dash joined the faculty of the College of Business (COB) in 1974. As a Full Professor, he holds appointments in Finance & Decision Sciences and the Interdisciplinary Neuroscience Program. He completed his undergraduate degree in business administration at Coe College (1968). He earned a master’s and two-field Doctorate in Finance and Operational Research from the University of Colorado at Boulder (1978).
 Dr. Dash has ongoing research projects that link traditional optimization algorithms to neural network algorithms for classification and prediction. His research emphasizes the development of algorithmic extensions in combinatorial optimization and radial basis function neural networks. Using newly developed algorithms, Dr. Dash has produced a current research strain that spans topics such as the neuroeconomics of SMART cities, ethical AI and the determinants of chronic disease states (neuroethics), and sustainability in multiobjective behavioral portfolio optimization. Dr. Dash’s research is published in journals that target portfolio optimization and management, multiobjective optimization, complex decision analytics, energy management, and more. Research service includes serving as an associate editor for the International Journal of Applied Optimization Studies and co-chair of the European Working Group for Operational Research on Development (EWG-ORD). Since 2018 the annual EWG-ORD international meeting format has promoted the dissemination of recent research findings on the integration of operational research and the United Nation’s seventeen sustainable development goals. Dr. Dash’s research has been presented globally in over thirty countries spanning the continents of Europe, Africa, and Asia.
Besides contributing several book chapters to books in financial engineering, Professor Dash is the co-author of two e-books. His book on derivatives market valuation is titled “Applied Risk Management: Valuation of Derivatives under AI and Data Science Technologies”. The twenty-two-chapter text features valuation applications that draw upon his state-of-the-art algorithmic tools. His investment and portfolio management textbook is titled “AI and Data Science in Applied Security and Investment Management.”  The textbook includes new valuation analytics to incorporate the latest in portfolio optimization and the use of neural networks to model key prediction targets such as corporate earnings.
Dr. Dash is a member RiskGroupAuth (Greece), an interdisciplinary research group (think-tank) specializing in developing risk assessment and management tools for modern energy systems. He remains a member in good standing of several honorary societies, including Beta Gamma Sigma, Phi Kappa Phi, and Delta Sigma Pi.

Personal website: www.ghdash.net