M. Hosein Zare, PhD

About

Hosein is an Assistant Lecturer of Operations Management at the Alberta School of Business since July 2020. He teaches courses on operations management, optimization, data analytics and modelling techniques in management. Prior to joining the Alberta School of Business, he was a Postdoctoral Associate at Ivey Business School. His research focuses on healthcare analytics and the optimization of service systems. He received a PhD in Industrial Engineering from the University of Pittsburgh in 2018. 

Research

• Healthcare analytics and operations
• Optimization of service systems
• Bilevel Optimization

Teaching

Hosein has experience in teaching courses in statistics, optimization, operations management and supply chain management. At the Alberta School of business he teaches courses on operations management, data analytics and modelling techniques in management.

• OM 420/620: Predictive Business Analytics
• OM 422/622: Simulation & Computer Modelling Techniques in Management
• OM 471/671: Decision Support Systems
• MGTSC 501: Data Analysis and Decision Making

MGTSC 501 - Data Analysis and Decision Making

This course begins with a survey of graphical and numerical techniques available for studying and describing data. Following an introduction to probability distributions, an overview of statistical inference for means and proportions is provided. Regression, analysis of variance and decision analysis are then utilized to analyze data and support decision making. Time series models are also briefly discussed. The data and decisions analyzed throughout the course will be representative of those commonly encountered by managers. During the required lab sessions, spreadsheet analysis of data, Monte Carlo simulation and the use of software for statistical analysis will be presented. Not open to students who have completed MGTSC 511 and MGTSC 521.

OM 422 - Simulation and Computer Modelling Techniques in Management

Computer modelling of management systems in such functional areas as accounting, finance, marketing and operations. Basic concepts of deterministic and probabilistic (Monte Carlo) simulation and their applications. Microcomputer implementation of case studies using spreadsheets particularly emphasized. Required term project. Prerequisites: MGTSC 312 (or equivalent STAT course), MGTSC 352 or OM 352; and FIN 301 or ACCTG 311. Not to be taken by students with credit in MGTSC 422.

OM 471 - Decision Support Systems

The course focuses on the creation of decision support systems using Microsoft Excel-based spreadsheet models and the associated macro programming language, Visual Basic for Applications (VBA). Students will learn how to create Excel-based applications to aid managers in making decisions based on data and analytics. These applications will have graphical user interfaces, appropriate models in the spreadsheet or in the background, and output reports. Fundamentals of VBA, such as the Excel object model, variables, control logic and loops, subroutines and function subroutines, and user forms will be introduced. Prior programming experience is not assumed. Student projects in this implementation-oriented course will come from different areas such as forecasting, regression, supply chain network design, employee scheduling, and portfolio optimization. Prerequisites: MGTSC 312, MGTSC 352 or OM 352.

OM 622 - Simulation and Computer Modelling Techniques in Management

This course will discuss computer modelling of management systems in such functional areas as accounting, finance, marketing, and production. Basic concepts of deterministic and probabilistic (Monte Carlo) simulation and their applications will also be covered. Micro computer implementations of case studies using spreadsheets will be particularly emphasized. A term project will be required. Prerequisite: MGTSC 502 or OM 502. Not to be taken by students with credit in MGTSC 632.

OM 671 - Decision Support Systems

The course focuses on the creation of decision support systems using Microsoft Excel-based spreadsheet models and the associated macro programming language, Visual Basic for Applications (VBA). Students will learn how to create Excel-based applications to aid managers in making decisions based on data and analytics. These applications will have graphical user interfaces, appropriate models in the spreadsheet or in the background, and output reports. Fundamentals of VBA, such as the Excel object model, variables, control logic and loops, subroutines and function subroutines, and user forms will be introduced. Prior programming experience is not assumed. Student projects in this implementation-oriented course will come from different areas such as forecasting, regression, supply chain network design, employee scheduling, and portfolio optimization. Prerequisite: MGTSC 501.

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