Master of Business Analytics and Intelligence Faculty

Big-data analytics is about examining large sets of data to uncover hidden patterns, unknown correlations and other useful information that can be used to make better business decisions. Kabirian's primary research and teaching interest in business analytics lies in data mining and statistical tools for big-data sets. He will teach Statistics Foundation and Data Mining & Visualization.

Supply chain logistics, the movement of goods from raw materials to finished products, plays a crucial role in business operations. Kamlesh Mathur's research is focused on the distribution aspects of the supply chain, providing management tools in two key areas. In the first, Mathur's studies look at how efficient routing and scheduling of delivery vehicles used to distribute products can result in substantial savings for companies. His second topic revolves around the question of where to locate claim and service centers for the greatest efficiency and effectiveness. Mathur serves as one of the co-directors in the Master of Business Analytics and Intelligence program and plans to teach the Operations Analytics: Stochastic course.

In the digital age, marketers collect and use a lot of data to understand customer behavior and formulate appropriate strategies. Rakesh Niraj's research deals with both analytical and empirical modeling of marketing strategy in such areas as information sharing, price targeting and customer relationship management (CRM). His recently published research, together with Jagdip Singh, looks at textual data generated by users in the context of reviews provided by peers and compares their impact to reviews provided by experts. He is teaching courses on measuring marketing performance, CRM and marketing metrics at Weatherhead. He is one of the co-directors of the Master of Business Analytics and Intelligence program and expects to teach the advanced marketing models class in the spring semester of the program.

Jagdip Singh's research involves designing and delivering human and technological interfaces that connect organizations and customers, with a focus on the service industry. Frontline interfaces are central to promoting, facilitating, and enabling the exchange of valued resources between an organization and its customers. Digital data generated during frontline interactions often hold a key for continuous innovation of interfaces for value exchange and long-term customer relationships. Singh works with frontline digital data to mine for insights and to build dynamic predictive models that inform intelligent, evidence based management decision making. He is one of the co-directors of the Master of Business Analytics and Intelligence program and will teach the Marketing Models and Digital Analytics courses.

Daniel Solow pursues several streams of research. The first area is "complex systems," which are systems made up of a number of factors that interact in complex ways. He’s developed mathematical models that provide insight on how much interaction among employees and managers is good for performance and the role and value of leadership. Related research identifies when, how and how much central control benefits a complex system. Solow's second research area involves developing computer programs for solving decision problems in business, engineering, economics, mathematics and computer science. His third focus is in developing systematic teaching methods to help college and graduate students learn advanced mathematics. Solow will teach the Operations Analytics: Deterministic course in the Master of Business Analytics and Intelligence program.