Data Science MS Capstone Advisor Selection Guide

The Data Science MS program is a Plan B only degree which has a capstone project component required for all students. Students must register for the capstone course DSCI 8760 as a part of degree requirements. Projects can be completed in one or two semesters (3-6 credits of DSCI 8760) depending on the nature of the project and faculty expectations. It’s common for students to work on their capstone in the second half of their time in the program, but it’s never too early to make connections with faculty to learn about their research and explore possible project topics. We encourage you to explore faculty and their research labs both in the Data Science program as well as other departments.

Once you have confirmation from a faculty member they will serve as your advisor and you are ready to enroll in the Data Science capstone course (DSCI 8760) you will need to request a permission number through this form.
Request a permission number

Below are requirements and things to keep in mind as you consider capstone project ideas and who to connect with to discuss serving as your capstone advisor.

Strategies for connecting with faculty and things to keep in mind

When approaching faculty about the possibility of serving as your capstone advisor, it is helpful to:

Open with an introduction about yourself, that you are a student in the Data Science MS program and you are currently searching for a capstone advisor
Discuss your areas of interest and how it might align with their research/area of expertise
Ask if they have the capacity to advise students and are able to meet to discuss your project idea(s) further

While it may feel odd to approach faculty you have never communicated with previously, it is still completely appropriate to connect with them about the possibility of serving as your advisor. We are a research institution, and faculty expect to be approached by students in this capacity.

It is ok to connect with faculty via email initially. As a general rule of thumb, you should tailor unique emails to each individual faculty you reach out to, e.g., include details on their specific research and what interests you about it. Emails lacking specifics to the faculty member will read as a generic email that could be sent to a large group of faculty and tend to not prompt a response.

Faculty are very busy, so it’s possible emails might get buried in their inbox and won’t respond. It is appropriate to send a follow up email if you do not hear back, but it’s common courtesy to allow them a couple weeks to respond before sending a follow up.

If you happen to have a class with the faculty member you are interested in working with as your capstone advisor, it may be convenient to visit them during their office hours to initiate capstone project conversations.

Unfortunately, not all faculty have the capacity to take on new students. Their availability is subject to change each semester. The program cannot keep tabs on which faculty are and are not able to advise students. This means it’s possible you will need to connect with additional faculty before your capstone advisor is finalized.

Capstone advisor eligibility requirements

Faculty who are automatically eligible to serve as Data Science capstone advisors are those who are affiliated with the program.
Data Science Graduate faculty

It is possible to have a capstone advisor who is not affiliated with the Data Science program, but those will need to be reviewed and approved on a case by case basis. To have a non-Data Science program faculty member serve as your capstone advisor, please send the following information to the Graduate Program Coordinator at [email protected]:

Brief description of the proposed project you and the faculty have discussed
The faculty member’s CV/resume

Once this information is provided it will be sent to the Data Science Director of Graduate Studies for review and final decision. Because data science is applicable in many areas this is an option a number of students are approved to do, but it needs to be clear that the research project has some data science component to it and that the faculty member has some degree of data science background.

At a minimum, faculty must have graduate education responsibilities in a University of Minnesota graduate program in order to serve as a capstone advisor. To learn if a faculty member has graduate education responsibilities, you can visit this website.
Graduate education faculty role list

Another group of faculty you may want to consider looking into as a capstone advisor are those associated with the University of Minnesota’s Data Science Initiative (DSI). A list of DSI faculty can be found here.
Data Science Initiative leaders and core members

Individuals from outside the University of Minnesota are not eligible to serve as faculty advisors for graduate students.