Instructor Spotlight: Greg Samsa, PhD

With a strong foundation in mathematics and a passion for applied problem-solving, Greg Samsa, PhD brings both expertise and creativity to the Duke Master of Biostatistics program. After earning an MS in mathematical statistics and discovering a love for applied research through hospital epidemiology, Samsa built a career focused not only on statistical methods but also on how to teach the often-overlooked “artistic” side of statistics— skills like effective communication with investigators. At Duke, he regularly teaches the SAS course and has also contributed to shaping core classes in the curriculum. Dedicated to student growth both in and outside the classroom, Samsa emphasizes hands-on learning, problem-solving, and the importance of approaching programming with curiosity and independence.

Could you share a bit about your background and what led you to the field of biostatistics/bioinformatics? 

I was a math major in college and looking for a field that used it. Statistics seemed less boring than finance, which was the other option I was considering.  I received a MS in mathematical statistics. Curing that time I served as the statistician for an investigator in hospital epidemiology and discovered that I liked applied work.

What is your current research or professional focus outside of teaching?  

My main research focus is discovering how to scientifically teach the artistic parts of statistics (e.g., how to communicate with investigators). 

Which course(s) do you teach in the program? 

I regularly teach the SAS course.  When Jesse and I want to revise a course, he and I will often perform the revisions, teach the course for a year, and then turn it over to others.  I’ve done this with 701, 702 and 719.

What do you most enjoy about teaching this/these course(s)? 

I enjoy teaching in general. For example, I’ve coached middle school soccer, high school tennis, and served as a chess tutor.  Any teacher in any field is happy when their students learn and thrive.

What are the key skills or concepts you hope students will take away from it/them? 

The SAS course is less about the details of SAS and more about the process of learning a computing language — for example, that includes language structure, algorithms and data structures.

Are there particular projects, examples, or applications that students tend to find especially meaningful or exciting? 

I’m not sure that “exciting” is the right word, but the SAS course is noteworthy in that the final exam is a coding interview. 

What do you enjoy most about working with Duke MB students?

They tend to be ambitious, in a good way.

How do you see students grow or change as they move through your course and the program?

I’m happy when students wonder why they need to take a class when SAS programming is so easy.  In fact, if you approach it properly, learning most computer languages is easy.  I like it when students move to the details of coding to a bigger picture perspective about programming.

What advice do you give students for getting the most out of your class?

Try to write code yourself before getting help (e.g., from others, from the web, from AI).  The more actively you engage in programming the more deeply you will learn.

What is something students might be surprised to learn about you?

It’s a long story, but I’ve never knowingly interviewed for a professional job.  I wrongly thought my visit to Duke was a practice interview.

What do you enjoy doing outside of teaching and research?

Tennis, chess, and creative writing, including a man-to-man conversation with my dog.