Modeling and Simulation

Use your creativity, imagination and interest in computers to solve real-world problems and investigate the subjects that interest you most through modeling and simulation. This program prepares you to participate actively in a variety of employment or research endeavors in medicine, transportation, and other industries, the public sector or academia. 

Applied mathematical models running on computers are used to simulate a wide range of physical, chemical, and biological conditions, including weather forecasting, climate change, biological populations, epidemiology, ecosystem processes, and pollution. In this program, you will learn to design and implement models to simulate various situations and gain in-demand skills that are applicable to a wide range of fields both in and outside of STEM. 

This interdisciplinary program connects concepts and applications of modeling and simulation with various focused disciplines, such as Environmental Science, Biology, and Economics. Graduates of the major are expected to be highly sought by employers and graduate programs. 

Graduates of the program will go on to careers in technical fields, including programming, applied mathematics, modeling, environmental regulation or consulting, mathematical biology, or mathematical economics, or move into graduate study either in computational science or other disciplines such as biology, environmental science, economics, and more. 

Degree Requirements

The major includes a series of foundation courses in mathematics, modeling, and programming, backed by a choice of courses in biology or earth and environmental science, from which the student can choose their discipline of interest. A project-based capstone course allows students to apply the combined knowledge of modeling and their chosen discipline. 

Majors pursuing a Bachelor of Science in Modeling and Simulation must satisfy the University Core Curriculum requirements and the College speech requirement, COMM 210. In addition, they must complete the following courses and a sufficient number of electives to total 120 credits. 

Foundation Requirements
  • MATH 213 Calculus I and Lab or Math 207 Applied Calculus I
  • MATH 214 Calculus II and Lab or Math 218 Applied Calculus II
  • MSS 100 Introduction to Modeling and Simulation
  • MSS 200 Coding for Quantitative Analysis

and any two additional courses that can serve as prerequisites for the Discipline Courses.

Math Skills Requirements

(Choose three)

  • MATH 301 Linear Programming
  • MATH 305 Math Modeling
  • MATH 317 Differential Equations
  • MATH 342 Numerical Analysis
Discipline Courses

(Choose five)

  • BIO 312 Conservation Biology
  • BIO 332 Fisheries Science
  • ECON 303 Introduction to Econometrics
  • ECON 395 Introduction to Game Theory
  • MATH 225 Mathematical Data Science
  • MATH 250/BIO 250 Introduction to Biostatistics
  • MGMT 325 Business Analytics 
  • MSS 255 Modeling and Simulation of Biological Systems
  • MSS 350 Epidemiological Modeling
  • NATSC 301 Marine Resource Management
  • NATSC 310 Biogeochemical Cycling
  • NATSC 315 Meteorology and Climatology
  • NATSC 333 Environmental Monitoring and Analysis and Lab
Capstone Course
  • MSS 422 Modeling and Simulation Capstone Course

The minor focuses on the mathematical and modeling skills and leaves the discipline up to the students major field of study.  This allows the students in any discipline to combine modeling and simulation tools with their expanded knowledge of the problems in their field to which the tools can be applied.

Foundation Requirements
  • MATH 213 Calculus I and Lab (4) or Math 207 Applied Calculus I
  • MATH 214 Calculus II and Lab (4) or Math 218 Applied Calculus II
  • MSS 100 Introduction to Modeling and Simulation
  • MSS 200 Coding for Quantitative Analysis
Math Skills Requirements

(choose one)

  • MATH 301 Linear Programming
  • MATH 305 Math Modeling
  • MATH 317 Differential Equations
  • MATH 342 Numerical Analysis
Applied Courses

(choose one)

  • MATH 225 Mathematical Data Science
  • MSS 255 Modeling and Simulation of Biological Systems
  • MSS 350 Epidemiological Modeling

Student Learning Outcomes 

  • Describe and compare different approaches for modeling and simulation.
  • Identify situations where models and simulations are used in the student’s focus discipline, such as Biology or Earth/Environmental Science.
  • Design simulation experiments that use existing models in the student’s focus discipline, such as Biology or Earth/ Environmental Science.
  • Demonstrate ability to apply appropriate modeling and simulation approaches to different types of problems.
  • Formulate domain-specific models and simulations of empirical or theoretical phenomena.
  • Utilize appropriate visualization techniques for showing simulation results.
  • Demonstrate the ability to analyze simulations to formulate conclusions regarding the predictive capabilities of a model.
  • Identify models and simulations within academic and professional literature.
  • Communicate modeling and simulation information and results professionally, in both written and oral forms.

Research Opportunities

The creation and implementation of a model is active learning from beginning to end, from the basic skills of computer programming and mathematics, to the application of those skills to address a real-world problems in the capstone class. In addition, the major has excellent opportunities for internships in industry or external research programs (e.g. National Science Foundation Research Experience for Undergraduates.)

Projects and research opportunities available through this major are wide-ranging. Topics that are currently active include ocean circulation, interactions between light and objects, brain function, population dynamics, and epidemiology.

Faculty

The Modeling and Simulation major brings together faculty from across the Feinstein School of Social and Natural Sciences and the Gabelli School of Business to help prepare students for the true interdisciplinary nature of the discipline.

Sean Colin

Professor of Biology, Marine Biology and Environmental Science 
Area of Expertise: Biomechanics and Evolutionary Ecology
scolin@rwu.edu

Edward Dougherty

Assistant Professor of Mathematics
Area of Expertise: Biomathematics, Computational Mathematics
edougherty@rwu.edu

Farbod Farhadi

Professor of Management
Area of Expertise: Mathematical Modeling and Dynamic Optimization
ffarhadi@rwu.edu

Hasala Gallolu Kankanamalage

Assistant Professor of Mathematics 
Area of Expertise: Mathematical Control Theory
hgallolu@rwu.edu  

Matthew Gregg

Professor of Economics 
Area of Expertise: U. S. Economic History
mgregg@rwu.edu

Rupayan Gupta

Professor of Economics
Area of Expertise: Public Economics & Policy, Political Economy
rxgupta@rwu.edu

Scott Rutherford 

Professor of Biology, Marine Biology and Environmental Science
Area of Expertise: Earth Systems
srutherford@rwu.edu

Yajni Warnapala

Professor of Mathematics
Area of Expertise: Numerical Analysis, Integral Equations
ywarnapala@rwu.edu