Laila Poisson has a PhD in Biostatistics from the University of Michigan (2010). She is a Biostatistician at the Henry Ford Health System, in Detroit, MI, as well as an affiliated Assistant Professor at Wayne State University.
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ResearchGate profile
Constantine: Laila, how did you get interested in statistics?
Laila: We honestly didn't do much in the way of statistics education in my K-12 years. I think I got the idea of a mean and I was able to read basic graphs when I graduated, but that was it. I liked the sciences, including math, so when I went to college I gravitated toward a program called "biomedical sciences." It required biology, chemistry, and physics. I didn't want to give up math, so I pursued a minor. Unfortunately, this degree track was designed to prepare people for medical school, and I didn't want to be a doctor. Alternative "career paths" were pharma sales rep or lab tech at big pharma, also not for me. Fortunately, my math-major fiancé noticed an MS program in "biostatistics" offered in the math department and my training fit the bill. I married that man, took his last name (no, I have no genetic ties to the famous Poisson family), and began my career in biostatistics.
Constantine: What is your job and what does your 'typical' workday involve?
Laila: I work as a biostatistician at the Henry Ford Health System and I am also an affiliated Assistant Professor at Wayne State University. My "typical" workday has lately involved way too many meetings, but "on average" I spend my time in one of three arenas. About 65% of my time goes to neuro-surgery and neuro-oncology research. I collaborate with a team of MDs and PhDs to battle brain tumors. The work is a mixture of clinical, cell and animal model, and high-throughput "omics" analyses. I feel that my training in biology has helped me to understand the disease. This last year I even took the lead on the clinical analysis of the upcoming marker paper on lower grade gliomas (grades II and III) from The Cancer Genome Atlas Analysis Working Group. Beyond brain tumors, about 15% of my time is devoted to the analysis of metabolomics data for cancer and chronic disease. My collaborators are more junior, like me, so we do a lot of grant writing. Finally, 20% of my time is spent teaching. My main commitment is to the MPH program at Wayne State University where I teach the elective in regression models. But, I also do internal education programs here at the hospital for residents and fellows.
Constantine: You have been a member of TSHS for a few years. Do you consider TSHS your primary section or is it secondary?
Laila: Yes, I suppose it's my primary section. I've tried lots of sections over the last decade but TSHS is the section in which I've found my best fit.
Constantine: What is your reason for participating in TSHS?
Laila: Though teaching is currently part of my "typical" day, most of my colleagues here at HFHS do very little teaching. I enjoy teaching and get a lot of inspiration and support from being a member of TSHS. I love that I can embrace a hands-on style classroom for teaching statistics to adults and professionals! I haven't made the "flip" in my classroom, but I've come a long way from 3-hour power point orations.
Constantine: Do you attend JSM or other conferences? If not, why not? If yes, what do you get out of it?
Laila: I started attending JSM a few years ago. It took a while to make the leap because the size intimidated me. However, I like the breadth of topics available at JSM. I can learn new things about cancer research and still talk to educators about how to build our new MPH in biostatistics. Another great aspect is that, because of its size, I get to catch up with statisticians that I've met over the years but whose specialties differ from mine.
Constantine: What are your thoughts about statistics in the future? About statistics education?
Laila: My recent tactic to ease student anxieties about statistics is to start class by explaining that statistics is all about summarizing data so that we can see the big picture out of big table of numbers. Everything and everyone collects data nowadays and we need trained people who can make sense from the noise. We also need educated consumers of statistics because, as we know, "all models are wrong but some are useful." I'm thrilled that my daughter has been exposed to data sciences since kindergarten. I've got a great picture (see above) of her collecting data from the local grocery store parking lot to determine the most popular car color. In case you were wondering, it is black. However, "stripy" did get one count.
Constantine: What are some of your interests outside work, statistics, etc.?
Laila: Outside of work, a great deal of my time goes to my family. My husband and I have two lovely young children, and we are local to both sets of their grandparents as well as aunts and uncles. "Me time" is spent cooking or dabbling in yoga. Right now I'm exploring vegan recipes and international spices. And, in my "free time," I put my teaching skill set to another use as the chair of the Sunday school program at our church. There's not a lot of cross-over to statistics, though my K-2 kids have counted animals two-by-two.
[This interview was conducted through emails, in February 2015. The text is based on Laila Poisson's own words, with minimal editing by Constantine Daskalakis.]