Getting to know Virginia Tech’s latest CUBE cohort
Students with varied interests and experience levels work together to learn more about the field of collaborative biostatistics
With a mission to raise awareness of collaborative biostatistics and diversity in the field, Collaborative Undergraduate Biostatistics Experience (CUBE), an eight-week summer program hosted by the Virginia Tech Center for Biostatistics and Health Data Science, returned in 2023.
This summer, five students — three who were based at Virginia Tech and two based at the University of Virginia — took part in CUBE, which was awarded a five-year, $1.25 million grant from the National Institutes of Health in the spring.
The program, which is geared toward underrepresented undergraduate students, is built on four pillars:
- training in introductory biostatistics;
- training in R programming;
- professional development;
- and a collaborative research project addressing questions in various disciplines.
With funding coming from the National Institute on Drug Abuse and the National Institute on Alcohol Abuse and Alcoholism, projects for this summer’s cohort at Virginia Tech were specifically targeted toward enhancing data science research training in addiction research.
Learn more about each of the three students housed at Virginia Tech for CUBE 2023 — including their summer research projects, their academic backgrounds, future goals, and what they gained from the program.
Alicia Alvarez, rising senior at Cal State East Bay
Alvarez worked with Jeff Stein, an associate director for the Center for Health Behaviors Research, on a project titled “Quantifying the Relationship of Reward Certainty with Delay-based Decision Making.” A goal of the project was to perceive certainty on delay discounting – whether a level of certainty would impact whether an individual chooses to receive an award now or in the future.
I first heard about the program at a statistical conference that I attended earlier this spring, and I happened to get a grant through the American Statistical Association to attend the conference. I saw a presentation about CUBE, which was geared towards Ph.D.s and universities to see if they would like to incorporate the program at their university. Because I got a grant to attend, I was one of the few undergraduate students that was at the conference, and I got to hear about the program.
I am a statistics major at my university, but I have been considering grad school and going into biostatistics. They don't really have biostatistics training at the undergrad level at my school, so I wanted to look for a way to study biostats, specifically in the healthcare field. This just seemed like the perfect fit because I would be able to do it now as an undergrad, to help prepare me for the future.
I think it has been working on the project and seeing actual biostatisticians at work. When we're in school, we get taught these methods, but we don't get to apply them in real world situations. Being immersed in the real-world aspect of it has been great, just to see how people actually work in the field, because you don't really get to experience that when you're in class.
I would say the role that biostatisticians play in the whole big picture, from research and where the role of a biostatistician would come in. I just didn't know how it fit together, so I think that has been the biggest take away – how we can work from start to finish on a project and that we're kind of immersed in every aspect of it. That’s been really cool. Plus, I have also learned some statistical modeling that I didn't know before. I hadn't been able to study that yet, but I don't think I probably would have been exposed to it until grad school.
I would tell them to do it. If they're interested in statistics at all or any type of health sciences — even if you're not wanting to be a statistician — it’s a great experience to see how it will fit in any type of biomedical or health field. It's really helped me think about what the next step is in my education.
Makara Le, rising senior at UMass Amherst
Le worked with Stein on the project, “Examining the Mediating Effect of Delay Discounting on the Impact of Simulated Scarcity with Cigarette Smoking Behavior.” The project assessed the relationships between delay discounting, scarcity – simulated in this experiment by reading a narrative about an abrupt transition to poverty – and cigarette craving and demand.
I heard about this program from my Intro to R professor. He emailed us about this opportunity and I thought that it would be a cool experience, I've never really seen anything like it before. Also, I'm from Massachusetts — I’ve never been to Virginia, so I wanted to push myself out of my bubble and come down here.
No, not at all. I'm an economics major and the only kind of biostats experience I had was in my R class – and I only took that because I'm pursuing an IT minor.
Honestly, everything about biostatistics. This is all so completely new to me. Specifically, I would say everything about research design and the importance of statisticians when it comes to before, during and after a study. That's not something that ever really came up in my studies before.
The people, my mentors. I've learned a lot from them and I've never really been in a working environment where I've been so supported. Like just now – I was so confused about what I was doing, but Alicia [Lozano] took the time and walked me through what I needed to do, step by step. She doesn't leave the room until I fully get a grasp of what is being asked of me.
All I know is that I probably want to get a graduate degree. I really like what I'm doing here and I've learned a lot about what I can do for myself in the future, and I think it's just made everything more complicated. There are a lot of opportunities I can pursue.
Yeah, in an insane way. Not only the physical opportunities I can achieve, but also different paths that I didn’t ever consider taking before. I would have never considered doing a Ph.D. in statistics before this program, but now I am considering it and looking into different types of opportunities like that. Getting a Ph.D. in general — I never thought that I wanted one, but everyone that I've met through this program has inspired me and I think I want to follow in their footsteps and go on that same career path.
I would say you have to do it. I think the networking opportunities that you get out of this are so incredible. Everyone here is so well-connected, and you get to meet so many different types of people. Also, this program is so unique in the way that they prioritize your learning to do a good job versus going into any other internship or any type of program like this where you're kind of expected to already have a skill set. I've never gotten training like this before, and I get to take it with me in the future.
You walk out of this program with so much added to your toolkit that you just didn't have before. We had biostats courses, and then we also had R courses, on top of a project that we now get to apply all our knowledge to. Also, I get to work with a collaborator — not only do I get access to the people in this center, I also get access to people who are doing research on other parts of this campus.