Mohamad Soltani

Assistant Professor, Department of Accounting and Business Analytics

Contact

Assistant Professor, Department of Accounting and Business Analytics
Email
soltani@ualberta.ca
Address
2-29C Business Building
11203 Saskatchewan Drive NW
Edmonton AB
T6G 2R6

Overview

About

Mohamad Soltani is an Assistant Professor of Operations Management in the Department of Accounting and Business Analytics at the Alberta School of Business. His research interests lie in the empirical analysis of service operations, with a focus on healthcare operations. In particular, he uses large-scale data sets to uncover latent interactions between healthcare policy makers, service providers, and patients in order to improve efficiency of services and quality of care. His research has been selected as the Winner of Production and Operations Management Society (POMS) College of Healthcare Operations Management Best Paper Award Competition in 2020.

Mohamad received his PhD in Operations Management from the Wisconsin School of Business at the University of Wisconsin-Madison. He also holds Master of Science and Bachelor of Science degrees in Industrial Engineering from Amirkabir University of Technology (Tehran Polytechnic) and Isfahan University of Technology, both in Iran.

He teaches Predictive Business Analytics and Operations Management at the Alberta School of Business.


Research
  • Healthcare operations management
  • Service operations management
  • Empirical studies in operations management
  • Data analytics

Courses

OM 420 - Predictive Business Analytics

Application of predictive statistical models in areas such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to extract data from relational databases, prepare the data for analysis, and build basic predictive models using data mining software. Emphasizes the practical use of analytical tools to improve decisions rather than algorithm details. Prerequisite: MGTSC 352 or OM 352.

Winter Term 2021
OM 620 - Predictive Business Analytics

Application of predictive statistical models in areas such as insurance risk management, credit risk evaluation, targeted advertising, appointment scheduling, hotel and airline overbooking, and fraud detection. Students will learn how to extract data from relational databases, prepare the data for analysis, and build basic predictive models using data mining software. Emphasizes the practical use of analytical tools to improve decisions rather than algorithm details. Prerequisite: MGTSC 501.

Winter Term 2021

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