BIO

Evan Barlow

Dr. Evan Barlow joined the faculty in the Supply Chain Management Program in Weber State University ’s Goddard School of Business & Economics in 2016. He completed his PhD in Operations Management at Northwestern University ’s Kellogg School of Management . He also has a B.S. degree from Brigham Young University and a M.S. degree from the University of Texas at Austin in chemical engineering. Prior to studying at Northwestern, he spent 4 years as a process R&D engineer at Bristol-Myers Squibb, where, among other accomplishments, he helped develop a process to mass produce a new cancer drug.

Dr. Barlow’s research focuses on the business analytics and artificial intelligence. He also engages in research at the intersection of economics and operations management. He is currently a member of INFORMS and M&SOM .

ACADEMIC PUBLICATIONS AND WORKS IN PROGRESS

Operations and Supply Chain Management Academic Papers:

Barlow. Puzzle—Integer Linear Programming: Spreadsheet Solver Excellence Without Excel
Barlow. Go West? A Case of Expanding Political Consulting Services
Song, Barlow, Sun. Exploring Topics and Trends on Pedagogical Research: Comparative Analysis
Giraud-Carrier, Barlow. Coal-to-Carbon-Fiber Business Case Analysis Report
Barlow, Allon, Bassamboo. The Autonomous Flexible Labor Force
Barlow, Allon, Bassamboo. Poaching Workers in a Supply Chain: Enemy From Within?

Pharmaceutical Industry Professional Papers:

Lobben, Barlow, et al. Control Strategy for the Manufacture of Brivanib Alaninate, a Novel Pyrrolotriazine VEGFR/FGFR Inhibitor
Broxer, Barlow, et al. The Development of a Robust Process for a CRF1 Receptor Antagonist

Semiconductor Industry Academic Publications:

McClure, Barlow, et al. Effect of Dilute Nitric Acid on Crystallization and Fracture of Amorphous Solid Water Films
McClure, Barlow, et al. Transport in Amorphous Solid Water Films: Implications for Self-Diffusivity

Medical Device and Healthcare Academic Publications:

Goodman, Barlow, et al. Computational Model of Device-Induced Thrombosis and Thromboembolism

Renewable Fuels and Sustainability Academic Publications:

Hunsaker, Barlow, et al. Renewable transportation fuels from biomass and black liquor

COURSES TAUGHT

SCM 3050: Operations and Supply Chain Management

Supply chain management is the value creation engine of every organization. The focus of this course is to acquaint students with the core elements of supply chain management: 1) customer value, 2) collaborative value creation, and 3) systems thinking. The course introduces and defines the three primary functions that compose supply chain activities- 1) purchasing, 2) operations, and 3) logistics-and shows how they need to work together to create the high-quality, low-cost, and innovative products and services that customers expect to find in today’s marketplace. Important analytical tools are introduced. Prerequisite: MATH 1010

SCM 3500: Spreadsheet Modeling for Decision-Making

Spreadsheet software enables business people to model and analyze quantitative problems in a wide variety of business contexts. This course covers spreadsheet modeling in terms of optimization models for deciding the best set of decisions to meet constraints and performance objectives; simulation models for considering uncertainty in business operations and decisions; and other decision models and tools. Through conceptual and applied topics, this course will enhance one’s problems solving and modeling capabilities as well as Excel spreadsheet skills. Prerequisites: MIS 2010, QUAN 2600.

MIS 2040: Business Analytics with Python

This course introduces Python within the context of business analytics. Students will learn Python programming basics and be exposed to the business analytics workflow, starting with interacting with SQL databases to query and retrieve data, through data wrangling, reshaping, summarizing, analyzing and ultimately reporting their results. Prerequisite: MATH 1040 or QUAN 2600.

MBA 6620: Data Mining for Business

The broad availability of data, either within organization or about market trends, has led to increasing interest in the methods for extracting useful information and knowledge from data. This course will change the way you think about data and its role in organization. We will examine how data mining technologies can be used to improve decision-making. We will study the principles and techniques of data mining, and we will examine real-world examples and cases to place data-mining techniques in context, to develop data-analytic thinking, and to illustrate that proper application is as much an art as it is a science. Prerequisites: MBA 6050 & MBA 6051 or equivalent courses in statistics or instructor approval.

MIS 3230: Data Mining for Business

This course will examine how data mining technologies can be used to improve decision-making. Students will study the principles and techniques of data mining, including gaining knowledge of the algorithms and computational paradigms that allow computers to find patterns in large datasets. Students will examine real-world examples and cases to place data-mining techniques in context, to develop data-analytic thinking, and to illustrate that proper application is as much an art as it is a science. Prerequisite: MIS 2030.

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