MATH 380 Introduction to Mathematical Modeling
Instructor: Hemanshu Kaul
Office: 125C Rettaliata Engg Center.
E-mail: kaul [at] iit.edu
Time: 3:15-4:30pm Tuesday and Thursday.
Place: Hermann Hall 007
Office Hours: Tuesday at 12:30pm-1:30pm, and Thursday at 4:30pm-5:30pm. And by appointment in-person or through Zoom (send email).
TA Office Hours: There is no TA assigned to this course. However, you are allowed and encouraged to ask for help at the Math Tutoring Center in RE 129. In particular, Alaittin Kirtisoglu, Wednesday 2pm-5pm.
ARC Tutoring Service: Mathematics tutoring at the Academic Resource Center.
|Course Information|
|Advice|
|Announcements|
|Examinations|
|Project|
|Weekly Class Log & HW|
|Supplemental Readings|
|MATLAB/ Mathematica|
Course Information:
The Course Information Handout has extensive description of the course - topics, textbook, student evaluation policy, rules for HW, as well as other relevant information. Read it carefully!
The official MATH 380 course topics.
Advice for students:
Excellent advice by Francis Su on good mathematical writing.
On a more abstract note, here is a discussion by Tim Gowers on Language and Grammar of Mathematics - which is part of what you are learning in a course like this.
Excellent advice for math majors, especially those planning to go on to graduate school, by Terry Tao, 2006 Fields medallist. Excellent reading.
Read this book on a variety of experiences in the journey to learn mathematics:
Living Proof
Some of the primary sources of information/discussion for careers in Mathematical and Data Sciences:
MAA - Careers
SIAM - Careers
INFORMS - Careers
AMS - Careers
Class Announcements:
- Thursday, 1/15 : This webpage will be updated every Thursday unless otherwise announced.
- Tuesday, 1/13 : Check this webpage regularly for homework assignments, announcements, etc.
Examinations:
- Exam #1 : TBA. Syllabus: Based on topics, examples, applications corresponding to HWs #1-#5.
- Exam #2 : TBA. Syllabus: Based on topics, examples, applications corresponding to HWs #6-#10.
- Final Exam : TBA by the university. Syllabus: All topics covered during the semester.
Project:
Instructions: The project is an important part of this course - not just in terms of the grade, but for the sake of comprehensive, practical understanding of how to apply the modeling framework to an open-ended real-life problem. This is why the problem statements that I have given to you are just short and open-ended descriptions of the certain real-life situations. You have complete freedom in mathematical interpretation of the problem and how you "solve" it. The only requirement is that you use the mathematical modeling process, and justify your model and its conclusions as they apply to the problem. Its a test of your creativity in formulation of models and solution methods, and your ability to find and understand relevant mathematical knowledge.
Read carefully through this list of instructions and advice for your project.
Look through the example project report given at the end of this SIAM report in Appendix B on page 50 of the pdf file for an example on how to format and write your project report. The pages 1-50 of this pdf file are also useful as a detailed overview of how to approach the modeling process for a project. Also, look through SIAM Computing and Communicating Handbook for further technical suggestions for working on your project and the report.
Deadlines for the semester project (unless announced otherwise in class):
Third week of February: I will send you the list of project topics by email.
2/23: Email me with project team members (2 per team)
2/28: Email me with your choice of project topics among the project descriptions sent to you by email.
3/10: Each project team shares with me a 1-2 page document of your project plan to get started.
3/31: Discuss the initial draft and model(s) of your project with me in person. All members of your team must be present.
4/15: Email me the status of your project report and the current draft of your Project report.
5/1: Final submission of Project report and associated materials/programs/etc. Email me the PDF file of the report and other related programs/files before 10pm, Friday, 5/1. This Email should list in detail the contribution of each member of the team.
Weekly Class Log with HW:
- Week #1 : 2 Lectures.
- Topics:Discussion of class structure and purpose. The process of math modeling - discussion with examples, Principle of proportionality, difference equations - examples from accounting/ finance/ science, discrete time vs. continuous time, limiting behavior of DDS(discrete dynamical system) and example of modeling births/deaths/resources through non-linear discrete dynamical systems. (From Sections 1.0, 1.1, 1.2, and elsewhere)
- Lecture Notes: Outlines of lectures without all the details as discussed in the classroom. Notes#1.
- Homework:
The homeworks listed below are from the course textbook, Giordano, Fox, Horton, A First Course in Mathematical Modeling, 5th edition.
You are required to follow the detailed instructions and rules for HWs given in the Course Information Handout and through email comments.
Work on the HW problems before and over the weekend so that you ask for help on Canvas forums or in-person with the instructor or the TA during office hours on Tuesday, Wednesday, and Thursday.
- Reading HW: Read and understand all Examples from Sections 1.1 and 1.2.
- HW#1 for Submission. Due Thursday, 1/22, by 11pm in Canvas. Submit a single PDF file through Canvas Assignment.
Section 1.1: #3bc, #10, (#12a and #13a).
Section 1.2: Submit any two of the following three sets of problems: #2, (#6 and #7), #9.
Questions? Ask on Canvas Discussion Forum. Or, Ask for help during the instructor and TA office hours, or through email to the instructor.
- Week #2 : 2 Lectures.
- Topics: (stable and unstable) Equilibrium values/fixed points and solutions of DDS, Solutions methods and stability of equilibrium values of homogenous and nonhomogenous linear DDS, Interacting discrete dynamical systems via a interacting species population model (Competitive Hunter model), discussion of real-life conservation strategy in terms of the model. Proportionality in non-linear or translated linear systems -examples from physics. (From Sections 1.3, 1.4)
- Lecture Notes: Outlines of lectures without all the details as discussed in the classroom. Notes#2.
- Homework:
The homeworks listed below are from the course textbook, Giordano, Fox, Horton, A First Course in Mathematical Modeling, 5th edition.
You are required to follow the detailed instructions and rules for HWs given in the Course Information Handout and through email comments.
Work on the HW problems before and over the weekend so that you ask for help on Canvas forums or in-person with the instructor or the TA during office hours on Tuesday, Wednesday, and Thursday.
- Reading HW:
Read and understand Examples from Sections 1.3 and 1.4.
- HW#2 for Submission. Due Thursday, 1/29, by 11pm in Canvas. Submit a single PDF file through Canvas Assignment.
Section 1.3: #1f, #2e, #3a, #6, #14ad.
Section 1.4: #2, #4.
Questions? Ask on Canvas Discussion Forum. Or, Ask for help during the instructor and TA office hours, or through email to the instructor.
Supplemental Reading:
For an alternate point-of-view and for additional applications, refer to the following books and articles:
- M.M.Meerschaert, Mathematical Modeling, Fourth Edition.
- H.P. Williams, Model Building in Mathematical Programming, Fifth Edition.
- Hillier and Lieberman, Introduction to Operations Research, 7th edition onwards.
- Wikipedia on Math Models
- OR Models
- The Unreasonable Effectiveness of Mathematics in the Natural Sciences, a famous 1960 article by Eugene Wigner, a Nobel prize winning physicist.
- For a bit of insight into what randomness means and one way of characterizing a random sequence of numbers, read through this short essay: Probability vs Randomness.
- Real-life evidence for Geometric similarity based modeling!! Strongly recommended!
- Chasing the Elusive Numbers That Define Epidemics
- Hard Lessons of Modeling the Coronavirus Pandemic
- Mathematicians and Blue Crabs
- Ecologists nightmare is a mathematicians dream
- Universal Geometry of Geology
- Modeling Brains: Ignore the Right Details
- Equation-Free Prediction in Ecological models
- Nature's Critical Warning System
- A Mathematical Model Unlocks the Secrets of Vision
- How Nature Defies Math in Keeping Ecosystems Stable
- Evidence is only as good as the model, and modeling can be dangerous business. So how much evidence is enough?
- Universal Law of Turbulence
- A Statistical Search for Genomic Truths
- All Change Is a Mix of Order and Randomness
MATLAB Information:
Mathematica Help:
Octave and
Scilab, two (FREE)
alternatives to MATLAB and Mathematica
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