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Publications in VIVO

Vossen, Thomas

Associate Professor


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courses taught

  • BUSM 3021 - Business and Financial Analytics II
    Primary Instructor - Spring 2021 / Fall 2021 / Spring 2022 / Fall 2022 / Spring 2023
    Focuses of quantitative tools to interpret and solve important problems in business and finance. Makes use of spreadsheet modeling, analysis and mini cases to present material. Ideal for those interested in quantitative methods and modeling. Degree credit not granted for this course and BUSM 3002.
  • MBAC 6080 - Decision Modeling and Applications
    Primary Instructor - Summer 2018 / Summer 2019 / Summer 2020
    Integrates topics from decision analysis and operations management as they relate to modeling management decisions. Field projects involve the university, local companies, and/or government agencies.
  • MGMT 4820 - Decision Analytics
    Primary Instructor - Spring 2021 / Spring 2022 / Spring 2023
    This course prepares students to thrive in analytics-driven organizations. Students will explore the capabilities and challenges of data-driven business decision making. The course will introduce a set of common analytics tools. Students will have opportunities to apply the analytics tools to business problems based on practical data sets from various companies. Excel spreadsheet and several other software packages will be used extensively in the course. The class will be conducted with a combination of lectures, case discussions, lab sessions, and student presentations. Grading will be based on several problem sets, exams, case reports, and a final project.
  • OPIM 8820 - Large-Scale Optimization
    Primary Instructor - Spring 2020
    Covers computational techniques for solving optimization problems with a large number of variables and/or constraints. The techniques will have many business and engineering applications. With the emphasis on integer programming, we will study Branch-and-Cut, Lagrangian relaxation, column generation and Bender's decomposition, from both a theoretical and practical perspective. Students will learn to formulate and solve large-scale problems and learn how to apply these techniques for their research.


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