The goal of the Professional Science Master’s (PSM) in Industrial Mathematics (a.k.a. MSIM) program is to produce generalized problem solvers of great versatility, capable of moving within an organization from task to task. The graduate will have studied not only the standard mathematical and statistical tools, but also the basic ideas of engineering and business, and will have received training in project development and in modes of industrial communication. The degree requires 36 credits of coursework, the successful completion of the Certificate in Project Management, and the successful completion of an oral masters certifying examination on the student’s portfolio of completed projects. The program is designed for students planning careers in business, government or industry.

List of Projects in Industrial Mathematics

- Survey of Industrial Mathematics (Fall semester)
- Projects in Industrial Mathematics (Spring semester)
- Certificate in Project Management (Summer)
- Four electives in Applied Mathematics
- Two electives in Statistics
- Four cognate courses
- Portfolio defense (last semester)

To be admitted to the Master of Science in Industrial Mathematics program, applicants must have completed (1) the mathematics or applied mathematics courses normally required for the bachelor’s degree with a major in mathematics, statistics, economics, physics or engineering with a GPA greater than 3.0; (2) courses at the senior level in mathematical analysis, linear algebra, and differential equations; and (3) have some familiarity with mathematical software programs such as Mathematica, MATLAB, etc.

Applicants must submit GRE general and subject test scores, degree-granting transcripts, and three letters of recommendation. Click here for the complete information regarding the admission process.

Support is available by serving as a Graduate Teaching Assistant for the Department of Mathematics. Click here to apply for the program (Support will automatically be considered).

You might request literature. For particular information about the program, contact Dr. Peiru Wu (peiruw@math.msu.edu), Director of PSM in Industrial Mathematics.

In addition to meeting the requirements of the University and the College of Natural Science, the student must complete a total of 36 credits for the degree below. The student’s program of study must be approved by the student’s academic advisor, including:

This is one of the industrial mathematics core courses. The course has three objectives:

- To survey mathematics of particular importance to industry
- To gain experience in team project report generation
- To gain experience in oral presentation of project results

The topics covered in this course are listed below (See Table of Content of the textbook, A Survey of Industrial Mathematics by Charles R. MacCluer, Dover Publications, Inc., 2010.).

- Statistical Reasoning
- Monte Carlo Method
- Data Acquisition and Manipulation
- The Discrete Fourier Transform
- Linear Programming.
- Regression
- Cost-Benefit Analysis
- Microeconomics
- Ordinary Differential Equations.
- Frequency-Domain Methods
- Partial Differential Equations.
- Divided Differences
- Galerkin's Method
- Splines
- Report Writing

The last chapter “Report Writing” is the guideline to generate technical reports for your projects and write memos for your computer exercise homework. MTH 843 is designed to train the MSIM students with emphasis on technical writing and to prepare students for MTH 844 (Project in Industrial Mathematics) in spring.

As an essential pillar of the program, this industrial mathematics core course requires students to spend the spring semester working on real-world problems, solicited from local industries and governments etc. We have a history of over 70 successfully completed projects proposed by local companies such as Auto-Owners, Chrysler, Consumers Energy, Dow, Ford, General Motor, Herman Miller, Johnson Control, Pfizer, Steelcase, and many smaller firms; click here for a complete list of the descriptions and final reports of completed projects.

The outline of the course is as follows:

- Team of 3 graduates with undergraduates’ assistance works together for one semester
- Team chooses a significant project proposed by local industry
- Team is advised by one faculty manager in the department and one industrial liaison from the company
- Team prepares a formal written technical report of their results
- Team delivers the project report and PowerPoint presentation at industry site in the end of semester

This requires completion of PHM 857 Project Management, covering such topics as formal project management culture, principles, knowledge areas, and terminology. It will normally be undertaken during the first year of enrollment as a “not-for-credit” option. Certification will also require participation in Industrial Mathematics-specific discussion sessions. After completion of the certificate program is approved by the instructors, the Industrial Mathematics Program, and the Associate Dean of the College of Natural Science, the Office of the Registrar will enter the certificate on the student’s academic record along with the term in which it was completed.

- MTH 810 Error-Correcting Codes
- MTH 840 Chaos and Dynamical Systems
- MTH 841 Boundary Value Problems I
- MTH 842 Boundary Value Problems II
- MTH 848 Ordinary Differential Equations
- MTH 849 Partial Differential Equations
- MTH 850 Numerical Analysis I
- MTH 851 Numerical Analysis II
- MTH 852 Numerical Methods for Ordinary Differential Equations
- MTH 880 Combinatorics
- MTH 881 Graph Theory

- STT 461 Computations in Probability and Statistics
- STT 801 Design of Experiments
- STT 843 Multivariate Analysis
- STT 844 Time Series Analysis
- STT 847 Analysis of Survival Data
- STT 861 Theory of Probability and Statistics I
- STT 862 Theory of Probability and Statistics II
- STT 863 Applied Statistics Methods I
- STT 864 Applied Statistics Methods II
- STT 865 Modern Statistical Methods
- STT 866 Spatial Data Analysis
- STT 886 Stochastic Processes and Applications
- STT 888 Stochastic Models in Finance

- Civil Engineering
- CE 801 Nonlinear Structural Mechanics
- CE 829 Mixing and Transport in Surface Water
- CE 863 Applied Numerical Methods for Civil and Environmental Engineers

- Computer Science and Engineering
- CSE 802 Pattern Recognition and Analysis
- CSE 803 Computer Vision
- CSE 830 Design and Theory of Algorithms
- CSE 835 Algorithmic Graph Theory
- CSE 872 Advanced Computer Graphics
- CSE 881 Data Mining
- CSE 885 Artificial Neural Networks

- Economics
- EC 811A Mathematical Applications in Economics
- EC 811B The Structure of Economic Analysis
- EC 812A Microeconomics I
- EC 812B Microeconomics II
- EC 813A Macroeconomics I
- EC 813B Macroeconomics II
- EC 816 Economic Thought II
- EC 820A Econometrics IA
- EC 820B Econometrics IB
- EC 822A Time Series Econometrics I
- EC 822B Time Series Econometrics II
- EC 829 Economics of Environmental Resources

- Electrical and Computer Engineering
- ECE 466 Digital Signal Processing and Filter Design
- ECE 837 Computational Methods in Electromagnetics
- ECE 848 Evolutionary Computation
- ECE 849 Digital Image Processing
- ECE 863 Analysis of Stochastic Systems
- ECE 867 Information Theory and Coding
- ECE 885 Artificial Neural Networks

- Environmental Engineering
- ENE 801 Dynamics of Environmental Systems
- ENE 804 Biological Processes in Environmental Engineering
- ENE 822 Groundwater Modeling
- ENE 823 Stochastic Groundwater Modeling

- Mechanical Engineering
- ME 820 Continuum Mechanics
- ME 821 Linear Elasticity
- ME 830 Fluid Mechanics I
- ME 840 Computational Fluid Dynamics and Heat Transfer
- ME 851 Linear Systems and Control
- ME 860 Theory of Vibrations
- ME 872 Finite Element Method

- Marketing
- MKT 805 Marketing Management
- MKT 806 Marketing Analysis
- MKT 809 Pricing, Profitability and Marketing Metrics
- MKT 819 Advanced Marketing Research
- MKT 865 Emerging Topics in Business

- Supply Chain Management
- SCM 800 Supply Chain Management
- SCM 826 Manufacturing Design and Analysis
- SCM 827 Competing Through Supply Chain Logistics
- SCM 833 Decision Support Models
- SCM 843 Sustainable Supply Chain Management
- SCM 853 Operations Strategy
- SCM 854 Integrated Logistics Systems

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