This page answers some common student questions. If you have additional follow-up questions or concerns, please feel free to reach out to me directly by email!

The answer is most likely 'no'. We use the registrar's waitlist system and give manual overrides only in rare cases of seniors who are trying to finish requirements for a major or minor. If you fall into this group, email me with your information and I will get back to you as soon as possible.

Possibly. Send me an email and we see what can be done. Note that this only gives you the ability to register for the course when your turn comes up during registration. It do not give an priority in getting a seat.

My current research requires me to be off-campus for most of the summer and I am therefore not able to take students looking to do traditional mentored research projects over the summer months. The University has recently made it possible for students to do supervised research where "students are typically pursuing more independent projects under faculty guidance, be it in person or remote." If you have taken the DSST289/DSST389 sequence or one of my independent study courses and would like to work on supervised research, please feel free to get in touch about your proposed project.

I occasionally run independent study courses in the form of a reading group. Usually there is about one per year. I choose a time and topic right before registration for the given semester. Required background for these is usually minimal, but varies with the topic. In order to dedicate my time to these reading groups I am not able to do other independent study projects with the exception of students continuing a supervised summer research project or a previous reading group independent study.

I will share my personal thoughts about graduate programs here; I encourage students to talk to a number of faculty to get a broad spectrum of advice that will allow you to make your decisions based on a variety of opinions.

If you are interested in data science or data analysis, one option is to do a traditional masters degree in statistics or computer science. These programs are offered by schools that tend to also have doctoral students, with masters students often taking the first-year Ph.D. classes. Note that the names of programs is not a great indicator of the content; one school's "Masters of Data Science" might be like another school's "Masters in Computer Science", "Masters in Statistics", or completely different. Look at the actual courses that are part of the program. These programs are great if you are interested in possibly doing a Ph.D. later; they are also more likely to have some funding available. Avoid programs where the number of masters students is very large compared to the number of Ph.D. students. Smaller is much better here! You can roughly use a published ranking on Ph.D. programs as a proxy for the quality of the master program, keeping in mind to avoid massive programs such as Columbia's M.A. in Statistics. Note that these programs will require a decent background in either computer science or probability and linear algebra.

The second option is to consider a program offered through a professional school. These often have names such as a Master of Analytics and may be offered in a business school, information sciences school, or through the school of engineering. I think these programs are the best option for most students. They have much better pipelines into industry and prepare you with a real and diverse set of skills. They are also more likely to be interested in students who come from humanities and social science fields. I particularly know about and recommend the programs at MIT Sloan, CMU's Tepper School of Business, the University of Michigan's School of Information Science, UCLA's Anderson School of Management, and the NC State Masters of Science in Analytics. This not an exhaustive list but just a starting point for your search.

As a final piece of advice, I encourage students to work for a year or two before going on to graduate school. It is much easier to both appreciate the limited amount of time that you have a master's program and also makes a huge different both in getting into programs (particularly those at professional schools, which as I mention above I think are the best) as well as finding a good job after completing a masters degree. It will also help you answer the question of whether you actually need to spend the time and money on a master degree. Often the answer is 'yes', but that is not a given. However, this said, I do understand that going straight to graduate school may be the right choice for some international students due to concerns over their visa status since it is often easier to get a work visa with a graduate degree.

My advice here is a much shorter. If you are trying to decide between different academic fields, pick the one with the best job prospects. That means computer science over statistics, statistics over mathematics, business over economics, and statistics/computer science over almost any other social or natural science. Once you finish your first few years in graduate school, you can always pivot into a research topic that interests you. However, academic job prospects deeply depend on the field you choose to apply to in your early twenties (yes, this is stupid). After you have picked a single discipline—I really recommend just one— apply to a number of schools in the top 25-30 programs in your field. Go to program with the best ranking and/or best funding package.

I am happy to write letters for students who have taken courses with me. Note that I can write the strongest letters for students who have taken BOTH 289 and 389 with me. If we have had only a single class together, it is hard to write too much that is particularly interesting. This matters less for masters programs but is likely not good for a Ph.D. program. Please send your request for a letter along with a CV at least three weeks before you need the first letter. Also, make sure to send me individual requests for each school or position at least 2 business days before the deadline.

Note that graduate school applications increasingly ask reviewers to explicitly rank applicants compared to other students. I do not agree with the premise of this approach, but do not want to jeopardise students chances to programs based on automated filtering from these fields. As an alternative, I select all of the highest categories but explain in my letter that these should not be used in admissions decisions.