About Me, Longer Version

One of my friends said that using the following post as my “About Me” page was too long, but I stubbornly want to have the longer narrative of my journey somewhere on this website, anyway.

My journey into biostatistics

I wanted to go to medical school

By the time I was in high school, I absolutely knew that I wanted to go to medical school.

I even had the opening of my medical school application essay:

It rains hard in North Carolina, and the downpour washes many of the earthworms in the suburban lawns onto the pavement, where they would surely die in hours under the scorching sun once the clouds cleared. As I walked to my bus stop in the mornings, I would carry a small twig and try to rescue all of the worms I saw by putting them back in the grass - even if it meant missing the bus and invoking my parent’s displeasure to drive me to school.

This was supposed to lead to how I always knew I “wanted to help others,” but reading that now is, bluntly, cringe-inducing. “Helping others” is a simple human trait that every single other applicant had, but what could I do? I knew that it wasn’t that strong of an argument, but I had been lucky enough to be born into a loving and safe upper-middle class family. I was also blessed to not have a personal medical story to share where I got hurt but was fascinated by the medical care I received.

The truth is that, at the time, I had been exposed to only a few archetypal careers: the doctor, nurse, lawyer, engineer, teacher, etc. Of those, I knew that becoming a doctor sounded the best, so I put everything toward pursuing it without much of a thought to look beyond.

Learning about biostatistics

Even though my father is a statistician, I didn’t know about biostatistics until partway through my sophomore year at the University of North Carolina, Chapel Hill (UNC). At the time, I had narrowed my medical goals into becoming a medical oncologist, but a college counselor recommended I look into biostatistics. I was well into my quantitative biology major at the time, but I thought that a biostatistics degree might help distinguish me from others in my medical school application.

I started my junior year without any second thoughts about medical school. I had agreed with two of my friends to take an MCAT class during the spring semester, but, as it turns out, by December I had to tell them how I had decided to change my entire life trajectory. (I still remember that moment vividly - we were walking in the school of public health campus back toward the main campus after class, and I was so nervous that they would be disappointed in me! But they took it very well.)

I realized that I lacked their raw passion for practicing medicine - while I had things like the shadowing hours and the coursework under my belt, I didn’t find myself excited to volunteer in the ER (like one of my friends) or take a gap year to volunteer in another country (like the other). Instead, I found myself increasingly drawn toward my biostatistics coursework. What really convinced me to pursue biostatistics as a career was a course project in which I read Deadly Medicine by Thomas Moore. To me, it really spoke to the importance of statisticians in medical science.

Even though I had decided not to pursue medicine itself, it was clear to me that I would want to study the closest thing (in my opinion) in biostatistics: clinical trials. The only thing left for me, at the time, was to decide where to apply for graduate school.

In my senior year, just before I applied, the Joint Statistical Meetings (JSM) took place in Seattle. I convinced my dad to go and let me tag along because I had heard great things about the Department of Biostatistics at the University of Washington. After speaking with some professors and students there, I was pretty convinced that it was my dream school. The department is known for being a very rigorous program with a focus on ensuring its students have an excellent theoretical foundation - even though I wanted to be an applied statistician in clinical trials, it seemed practical to start my career with as much theory as I could, rather than learn more of it on my own.

When I applied, I fully expected to be rejected: browsing the students’ pages at the time, I did not feel like I stacked up at all. Somehow, however, the admissions committee slipped my application into the “Acceptances” pile. I was also accepted to UNC’s Biostatistics program, but I thought this was my chance to move out on my own and experience the big city life (I grew up in North Carolina - visiting UNC was a frequent trip when we had guests). In addition, I had heard a rumor that departments preferred to hire new professors from outside of their PhD program, and in the back of my head, I maintained the hope that I’d come back to live in Chapel Hill. (Who knows if that’s what is in store for me!)

Excited, but with a heavy heart for leaving UNC, I moved to Seattle in Summer 2016. (My girlfriend and I drove across the country and visited many national parks along the way - definitely a life-changing experience that I highly recommend, if possible!)

A short overview of graduate school

Quickly after starting, I learned what “rigorous” coursework meant: it was really hard.

In my first-year statistical theory sequence, it felt like the professor was only teaching the class to the students who had already taken a class with the course textbook; the rest of us just had to catch up. It seemed as if in every lecture he would use the word “recall” when describing a completely new concept.

Nonetheless, the other first-year biostatistics students and I commiserated and survived. The second year felt a bit better: while the classes were even more difficult, it felt as if everyone in the class was on the same page. By some miracle, I even managed to cap the second year by passing both of the qualifying exams: it was a huge relief to be able to continue onto the dissertation phase of the PhD.

My third year also included the opportunity to take the applied statistics that I had been excited to take since undergrad. It was an absolute honor, in particular, to take a class in clinical trials from a giant in the field like Tom Fleming (incidentally, I was even more lucky to TA for him the following year!). The concepts were familiar, but hearing them from him was illuminating.

My fourth year passed in a complete blur. I no longer needed to take classes, so my academic time was spent solely on research and TA work. Outside of academics, I also had the opportunity to do consulting: as an independent consultant, I helped an orthodontics student with a data analysis for his thesis, and I also joined Nayak Polissar’s group of The Mountain-Whisper-Light Statistics to work on a variety of projects.

Now

At the time of writing this, it is Summer 2020, and I am doing a virtual internship at Amgen, while the world is being ravaged by Covid-19.

In my internship, I have the privilege to work on simulation-based design considerations for confirmatory clinical trials. While I did (perhaps, arrogantly) believe I could do it, I did not expect to be given an opportunity like this - I felt this was something left to the senior statisticians with years of experience under their belts.

Working at Amgen in simulation-based design has been an amazing experience because it takes my interest in the design of clinical trials and additionally allows for enormous creativity. With simulations, it really is a matter of “if you can imagine it, you can do it” (given enough wrestling of the code…).

After my internship ends in September, I will return to my dissertation work with the hope of graduating in Summer/early Fall 2021 and proceeding into a career (of course, planning around Covid may be a fool’s errand).

As someone interested in being a clinical trials statistician, I am blessed to have a wide variety of options spanning academia, government and industry. In any of those areas, I am confident I can realize my hopes of growing into a thoughtful and capable leader in clinical trials statistics.

Categories: Personal