“It’s a supportive and collaborative environment” — making connections as a PhD student in and outside the classroom

U-M CSE PhD candidate Sarah Jabbour discusses how collaboration is centered in her experience as a graduate student.
Sarah Jabbour

CSE PhD student Sarah Jabbour began her education in computer science  after taking EECS 183 in her third year of undergraduate studies. Now, she participates in the Michigan AI Lab as a PhD candidate and works to develop machine learning models that can map chest x-rays to diseases with the ultimate goal of augmenting clinical care.

We recently spoke with Sarah about her experience as a graduate student in computer science and engineering. Here’s some of what she had to say: 

What got me interested in computer science

I came across CSE by accident. I was a third year undergrad here, and I  took EECS 183 because I needed the course for another major. I really liked it, so I switched my major  and took as many computer science classes as I could. I took a class on machine learning with Prof. Jenna Wiens, and she just happened to have a spot in her lab for an undergraduate to do some research, so I took advantage of that.  I became really intrigued by the idea of using artificial intelligence and machine learning for healthcare and realized how many people and patient populations you could help in this way. 

Being a PhD student

I really like being a PhD student because you form a bond with your research topic. You get to go really deep into the weeds on a topic that’s really exciting to contribute to and have your name on it. It’s nice to feel like you have an impact on the field, and a PhD lets you do that. 

What interests me about artificial intelligence in particular is the impact it can have, especially in health care and the potential number of patients we can hopefully help using this technology. When I decided to pursue a PhD, I wanted to be somewhere with a great research hospital and focus on AI. I eventually chose Michigan because of my relationship with  Professors Jenna Wiens and David Fouhey, who are now my advisors, and because of the opportunity to collaborate with physicians at Michigan Medicine.

Collaborating within CSE and beyond

What I really enjoy about CS is that the people in the division are great. I’ve made many friends in CSE and in the AI Lab, and it’s a very supportive and collaborative environment. Whether it be Michigan Medicine or other schools at the university, there are always external collaborations going on that are very exciting.

In a typical week, we’re in constant communication with our collaborators in other departments. Their expertise is helpful when discussing how we can use machine learning or AI in general in their field, and we really use domain expertise to guide what we develop.

My advisors and I meet weekly, if not more than once a week. We’re always emailing, and they give me really good advice on my research. Even when I’m stuck on research, they’re there to guide me if I’m going in the wrong direction and to get me back on track. They’re always there to  remind me that research is slow, but so long as we keep chipping away, we’ll get somewhere. 

I have really great access to the broader professional community, whether it be through my advisors helping me network or putting me in contact with people in general at events like conferences where you get the opportunity to meet a lot of people outside of your specialty.

Better together

I think my advisors have done a really good job of putting together cohorts that get along really well. My labmates and I are all great friends, so we see each other outside the lab a lot. We’re always planning things like movie nights or friendsgiving when it’s the holidays. 

We’re also always giving each other feedback on research, and especially in times when research is going slow, we’re always there to support each other and remind each other that it’s a marathon and not a sprint here. If you have questions about areas that you’re not really familiar with, you generally have someone you can talk to in another room. So I tend to take laps around the department and see who’s available to discuss problems with me.

Women in computing

Being a woman in computer science can be challenging because you don’t see a lot of women in computer science right now. Sometimes it can feel like you don’t belong or you’re not qualified enough. But having a woman as an advisor is always a reminder that women do have a place here. At CSE, the Michigan AI Lab has a faculty that is 50% women, which is really inspiring. The women faculty in the department are people we look at and say, “Hey, it’s possible to have a career in research as a woman in computer science.”

What I’d tell someone thinking about getting their PhD in CSE at Michigan

I think that I’ve been really lucky because I am in a cohort and lab where I feel very supported. That might be the most important part of a PhD. It’s not necessarily about going somewhere with a big name, but about going somewhere where you can see yourself enjoying your full five years.

One important thing to keep in mind is that a PhD is really long, and it’s important to find time for yourself and do things outside the PhD for your mental health. The second thing I would say is look for a lab where you’ll get along with the students, because you’re going to be with them all the time. 

Computer science is really challenging, and it’s going to be hard everywhere. But I found that during my time in CSE at Michigan, I have had a lot of resources at my disposal to make it easier. So it might be challenging academically, but this is the right place for me.