CMSE 801 - Semester Project#

As part of your semester in CMSE 801, you are expected to complete a fully-fledged data analysis or computational modeling project. This is your opportunity to choose a topic that sounds interesting to you and dig into it.

At the end of the semester you’ll submit your work as a detailed Jupyter Notebook as well as presenting your findings to the rest of the class.

Choosing your project#

You have the freedom to choose from any of the techniques that we have covered and will be covering in class. These techniques include, but are not limited to:

  • Data Science: analyzing, modeling, and visualizing data

  • Computational Modeling: building, running, and evaluating models with

    • ordinary differential equations

    • compartmental models

    • agent-based models

Furthermore, you can also choose nearly any topic that you find interesting or exciting. Possible areas of interest may be:

  • Physical Systems: modeling problems in physics, chemistry, ecology, biology, etc.

  • Social Science: modeling people and their interactions

  • Finance, Banking, and Economics

  • Diseases: modeling the tissue scale or the person scale

No matter what you choose, the main goal is to define a question that you think you can answer using the techniques we’re learning in class and not just a question that you can look up the answer for on the internet.

Project requirements#

A successful project will include all of the following components:

  • A question that you will attempt to answer.

  • A model, expressed in broad mathematical or descriptive terms, that can be applied to a dataset or chosen topic.

  • Computational methods that seek to answer your question. (This will vary from project to project, depending on the context).

  • Meaningful visualizations that productively convey your results.

  • An answer to the question or an explanation as to why you were unable to answer the question.

Locating data and models#

You’ll need to spend some time figuring out what model is the right model to use or what data are available to answer your question. The internet is your friend for this part. You should be able to find the details you need to compute your model or the data you want to analyze on the web. These are some possible, non-exhaustive resources for locating data:

You may also wish to explore some of the additional resources listed on this page:

For the models, you’ll need to do a bit of background research and determine which of the models we’re working with in class are the most appropriate for your question.


When you’re finding datasets online you should make sure to record exactly where you found the dataset and cite the source in your final project notebook. Additionally, if you use any code that you find online to complete part of your project you must give credit to the original source code and cite this in your project as well. Any code you use that is found online and not properly cited will be considered plagiarism and violates the academic integrity expected of you in this course.