Blog

Next up in the spotlight is one of our Senior Project Managers in the Center for Quantitative Sciences, Mr. David Biagi .  Learn more about his role on the team and how he may find favor with a four-legged creature in the coming year . . .

Tell us about your group and role within the CQS IT team.
Our team in the Collaborative Studies Coordinating Center provides database and development support to a wide range of research projects. Our goal is to remove technological barriers for our collaborators. Currently we maintain a wide variety of projects for international research groups, including virtual bio-repositories, clinical trial management systems, and outcome aggregation systems. We hope to continue to enable science-at-scale by helping researchers pool their data, resources, and efforts.

What drew you to Vanderbilt and what has been your experience working in a collaborative environment such as this?
I was attracted to Vanderbilt by the personal recommendation of several colleagues. That trust was not misplaced, as it has been a great place to build a career over the last ten years. I have always felt like my input was valued and appreciated the way I have been enabled to pursue and achieve goals I've suggested in support of the department's efforts.

Tell us about your life outside of Vanderbilt. Do you have a significant other? Children? Pets? 
I'm married to my high school sweetheart and we have four daughters ages six months to seven years old. There's a long standing family debate raging over whether or not we should get a dog. I stand alone in opposition and I plan to lose this debate sometime next year.

Meet one of our newest faculty members, Dr. Simon Vandekar, an Assistant Professor in the Department of Biostatistics.  He is a great addition to our group and it's a pleasure to get to know him.

What are your research interests and what is the focus of your research? What have been the major findings so far?  
My statistical research develops inference procedures for high-dimensional data with a particular focus on neuroimaging data. This research has been published in Biostatistics, Neuroimage, and JASA. My collaborative research studies how the brain changes through development and how it is affected in psychiatric disorders. This work has been published in the Journal of Neuroscience, Nature Communications, and Science. My research has relied on family-wise error rate, spatial extent inference, and semiparametric procedures and I would like to begin to develop nonparametric procedures that control the false discovery rate. I am also interested in high-dimensional measures of replicability and the stability of findings across varying preprocessing parameters.

Tell us about any honors you have received, awards you have won or any significant publications you've had.
I was awarded the Saul Winegrad Oustanding Dissertation in my graduate group when I graduated in May 2018. My most recent first author publications were in JASA, Biostatistics, and the Journal of Cerebral Blood Flow and Metabolism.

What was your draw to statistics and what are some of your goals?
I realized I loved statistics after working in a neuroimaging lab after graduation with a BS in psychology. The goal of my research is to develop statistical tools that can be immediately applied to real world problems. I am most interested in semiparametric methods to do this.

Can you share the status of any of your past students?  What is your philosophy about teaching or research?
I haven’t mentored any students, but I look forward to the opportunity! I personally learn mathematical or statistical tools best when I use them to solve problems in my research. I think statistical methods should try to make realistic assumptions about the data and that the analysis approach should be determined by particular questions or hypotheses.

What makes Vanderbilt special in your experiences of collaborating with others? What are your thoughts on controversial statistical topics such as adjusting the p-value for multiple comparison, the choice between Bayesian, likelihood, or frequentists, ethical issues, etc.?
The collaborators I’ve worked with here seem extremely focused on the wellbeing of their patients, which makes working with them more rewarding. My work is in multiple comparisons adjustment and I see it as a way for understanding the amount of bias induced by looking at hundreds of thousands of variables, but I don’t think that we should use hard thresholds to decide about the unknown state of the world. Two studies that presents results with and without adjustment are equally valid, but the first provides more evidence against the null hypothesis. I am interested in learning more about semiparametric likelihood and Bayesian methods. I like the probabilistic statements the Bayesian philosophy affords but have an aversion to priors or heavily parametric models because I’m not sure how assumption violations affect the bias and interpretation.

Tell us about your life outside of Vanderbilt. Do you have a significant other? What about your hobbies? 
My spouse currently lives in Houston with our two dogs (a dachshund and a basset-lab mix), where she is doing an internship, but she will get to move here soon! I like hiking, camping, running and visiting the many delicious breweries we have in Nashville. I also like foraging for mushrooms.

Finally, what is something about you that most people at Vanderbilt still don't know about you? (Until now, of course!)
My wife and I dabble in extreme sports. My favorite was hang gliding, but we also tried sky diving and go scuba diving not too infrequently.

This week we are excited to feature Quanhu "Tiger" Sheng who is one of our Research Assistant Professors in the Department of Biostatistics and also the Technical Associate Director of VANGARD.  Learn more about his work and interests here at Vanderbilt as you read on below:

What is your area of interest and what have been your findings? What are the next steps for your research?
I like coding and I always believe the algorithm development and/or paper should not be the end of our bioinformatics/biostatistics research, therefore I  focus on developing algorithms and implement software to help the lab, the collaborator and the research community.

For example, I have worked on TurboRawToMGF, BuildSummary and ProteomicsTools for proteomics research, NGFPERL, GLMVC and TIGER for next generation sequencing analysis. Almost all of those findings have come from my very close collaborations with various wet lab researchers. The manuscripts produced have been published in journals such as  Rapid Commun Mass Spectrom, J Proteome Res, Genomics and Journal of Extracellular Vesicles. Currently, I am very interested in large scale next generation sequencing analysis using cloud computing. I hope I can provide some software solutions to help people who want to migrate the analysis from a local cluster to a cloud platform.



Tell us about some of your achievements-- any publications, leadership positions, and/or committees you have served on.
I have published 83 peer-reviewed papers with the majority of those being related to qualitative and quantitative proteomics, glycomics, next generation sequencing and multi-omics data integration. I am currently the Technical Associate Director of VANGARD (Vanderbilt Technologies for Advanced Genomics Analysis and Research Design).  In addition to that, I am leading a group to develop the NGS analysis framework in ACCRE which can dramatically improve the reproducibility and efficiency of data analysis.

What was your draw to the field of statistics and what are your goals?
Actually, my major was bioinformatics, but I have learned so much since joining the Center for Quantitative Sciences and then the Department of Biostatistics. I have learned that even with the very basic t-test, I need to make sure that the data truly supports the assumptions. I really believe that statistics is an essential part of both basic science and clinical research, and that the Department of Biostatistics will play more important roles in the Vanderbilt research community in the near future. Currently, I define myself as an entry-level biostatistician and an expert in bioinformatics. My goal is to apply my knowledge in precision medicine to help doctors and patients.

Can you share the status of any of your past students? What is your best advice for aspiring statisticians? 
I haven't had any students yet but I have guided a lot of our postdocs and staff members at various stages.  I really enjoy sharing my experience with people.

For those aspiring statisticians, I hope they can also work with some technical fields, such as code management, test driven development and even cloud computing. Those fields will make their research more robust, more efficient, and most importantly, more reproducible.

What makes Vanderbilt special in your experiences of collaborating with others? 
When I joined the team in 2012, I immediately felt the closeness from the collaboration between the basic science groups and clinical groups, and the discussions between the bioinformaticians and biostatisticians were amazing. It felt like a new window had opened up for me at that time. I have enjoyed this environment and getting the chance to work with all of the experts from different fields.  Today data science has become the hottest field in the world and I expect that statistics will play an essential role in healthcare data science in the future.

Tell us about your life outside of Vanderbilt. Do you have a significant other? Children? What are your goals for the future?
My wife and I have two lovely sons. I love to play basketball with friends at recreation center and with my kids at backyard. My goal is to keep my family safe and happy in the future.

Finally, what is something about you that most people at Vanderbilt still don't know about you? (Until now, of course!)
My colleagues definitely believe that I am such a kind, mild-mannered person, but you will see a different side to me on the basketball court; I become very focused and assertive.  And I have to admit that I am no good at remembering peoples' names.  So, if you ever meet me down by the court just know that I may not remember your name even though we may have met; please forgive me.

Today we are getting to know one of our Department's adjunct professors, Dr. Rafe Donahue.  Get the inside scoop about his research and interests!

What is the focus of your research and what have been the major findings so far?
As an adjunct faculty member working in industry, my research doesn't quite line up with the research of my strictly-academic colleagues.  The work I do, however, helps patients in a very direct sense, by getting products to market for the benefit of patients and health care providers.

The work that has kept me busy for the last decade or so revolves around a growth factor used in joint fusions, surgeries that eliminate pain by making two bones grow together across a joint that, typically, is damaged by arthritis and thus is painful.  This growth factor, we have shown, when properly applied, can be used in place of an autograft, a piece of the patient's own bone, harvested from elsewhere in the body.  These autografts can themselves result in problems, hence the value of a product that can be used in their place.

Tell us us about any recent publications you've had.
Our research typically gets published in major medical journals.  I was fortunate to get recent publications in Journal of Bone and Joint Surgery, Foot and Ankle Surgery, and Foot and Ankle International.

What was your draw to statistics at Vanderbilt and what have you learned as a statistician? 
The Vanderbilt biostats group is a vibrant team of fiercely-bright, top-notch professionals who are not only good statisticians, they are also good people. My relationship with Vanderbilt provides a strong connection to the academic world and provides valuable support to keep the work I do grounded.

Being a statistician has helped me understand how to look at data and see more than just means; it's about understanding variability and distributions.

What is your best advice for aspiring statisticians? 
My advice to aspiring statisticians is to commit to getting details right, whether they are statistical or scientific.  It's not good enough to say, "Well, that's good enough."  Credibility comes with getting the details right.  Learn the science; become conversant with your collaborators; don't accept being just a "Would you like fries with that analysis?" kind of statistician.  If your collaborators only want someone to compute p-values and sample sizes, get different collaborators.

Good statistics is about good design.  Fancy analyses will not save poor design.

Oh, and if your program takes days and days to run, either your analysis is too complex or your coding is not optimal.  Or both.  (That'll fire up somebody.)

What are your thoughts on controversial statistical topics such as adjusting the p-value for multiple comparison, the choice between Bayesian, likelihood, or frequentists, ethical issues, etc.?
General statistical rant:
We can be our own worst enemies sometimes because of how we teach statistics.  Look at the typical class: roll some dice, deal some cards, flip some coins, probability, conditional probability, here's how to compute a mean and a standard deviation and a median, here's how to do a t-test, f-test, chi-square test, regression, Bayes rule, use this R code to compute this, use this R package to compute that, use this SAS program to get data into a format for submission to FDA: everything we teach them is _technical_.

But if you go to seminar, the discussions aren't technical; they are strategic. "How does this impact the bias?"  "What does this do to the Type I error rate?"  "How does one present these data in the context of treating patients?"

So, people take our courses and they think that we are technical people doing technical work and they think, "I'll just save a ton of time and money and just download a copy of the super-EZ-stat app for Excel and I'll do this all myself!"  Or they think, "All I really need is a sample size and I'm too busy to do it myself; I'll just have the statistician compute that sample size for me when I'm in Boca next week."

But, as we statisticians know, it's much more complicated than that.  THIS STUFF IS REALLY HARD.  And it takes a lifetime to REALLY understand it.  There's a great article out there somewhere by Dick DeVeaux and a buddy called something like "Math is Music, Statistics is Literature"  It says that you can be a child prodigy in math and music because they are fields that are completely contained within themselves, so you can get folks like Mozart, who composed as a small child, and Guass, who showed, also as a small child, that the sum of the first n integers is (n)(n+1)/2.

But to write really good literature and to do really good statistics, you need to have life experience.  You need to understand the human condition and have seen the world in action.

Statistics isn't technical, even though we teach it that way.

Multiplicity/testing thoughts:
Feel free to do multiplicity adjustments but, better yet, show me the whole distribution of p-values (and not just the mean).  How do we deal with correlation?  How do we deal with the fact that in my lifetime I have look at thousands and thousands of p-values?  What's the impact of that?

P-values and inferential statistics only work in a narrow, forward-looking framework:  "If I run this experiment and if the null is true and if the data follow the distribution laid out in my plan, then the chance of a false positive outcome is 5%...".  Once the trial is run, everything is subject to all sorts of philosophical nuance.  We need to be very careful.

There's a big difference between inference from planned experiments and modeling data from EMRs and the like.  Bayesian stuff is great for things like that but not so much for planned experiments.

And let's not think that Bayesian methods, as slick and sexy as the math is, are a panacea for all the ills in our modern stats world.

Ethical issues thoughts:
This should go without saying but let's not lie or cheat or stack the deck or mislead.  We are nothing as statisticians if we aren't trustworthy.  We shouldn't have to teach that but if we do, so be it.

Tell us about your life outside of Vanderbilt. Do you have a significant other? Children?What about your hobbies and future goals? 

I have a wife of 27 plus years; we have a little doggie and live south of Nashville in warm and cheerful Nolensville.  We are active members of Holy Family Catholic Church in Brentwood.

We have three children.  Harry (b 1993) is a lieutenant in the Army stationed (currently!) in Tacoma, WA.  Zach (b 1994) is a second-year law student at the University of St. Thomas in Minnesota.  Olivia (b 1996) is an artist and care-giver living in Overland Park, KS.  They are wonderful sources of Joy and Light.

I have a couple of things that keep me busy outside of work.  We have a very large and well-organized Lego collection and we build things and go to conventions and all that.  We are part of a local Lego club that hosts an event every November at the public library in Nashville.  I typically build replicas of buildings I like or mechanical computing machines.

I also like to make sawdust in my workshop and the occasional furniture that might result from that.

I would love someday to own and run a working bison ranch but I'm thinking that's not going to happen.

Finally, what is something about you that most people at Vanderbilt still don't know about you?Here's something about me that most people don't know: I applied for the astronaut program at NASA several years ago.  I actually successfully navigated the application process and my credentials were  reviewed.  I was, of course, rejected; but I successfully made it through the process.  It was a very interesting experience!

This week we are excited to feature Cathy Jenkins, a Biostatistician IV, in the Vanderbilt Department of Biostatistics. Read on to learn more about her work and interests here at Vanderbilt:

What has been the focus of your research during your time in the Department?
For most of my time at Vanderbilt, I have split my time evenly between the Division of Infectious Diseases and the Department of Emergency Medicine.  My work with Infectious Diseases has been all HIV research using data collected locally, as well as from larger regional cohorts such as North America or Central and South America.  In one study, we saw that obesity is an increasing problem among persons living with HIV. The investigator I worked with on this project is interested in understanding HIV in the context of this obesity problem along with HIV in the context of the co-morbid conditions that come along with obesity.

My work with Emergency Medicine has largely focused on the management of heart failure in an acute care setting.  As the population ages, the number of people showing up to ERs with signs and symptoms of acute heart failure is increasing.  While it is clear who the sickest of the sick are and should be admitted, there is a large gray area where it is unclear how best to help patients manage their disease.  In one particular study using data from a large national emergency department database, we saw that on average about 80% of patients coming to the ER with acute heart failure were admitted.  This leads to huge costs both for the patient and the hospital.  Our goal is to be able to identify those who are safe for discharge from the ER to reduce the burden on both the patients and the hospitals.

How did you become a biostatistician?
I came to statistics by a very circuitous route.  I have an undergraduate degree in chemistry and a masters in applied math. I always enjoyed applications in the chemical/biological realms and found the teaching aspects that come along with working as a statistician appealing.  Just like with teaching, communication is key in my job. The investigators with whom I work have varying levels of statistical backgrounds so being able to adapt to their comfort level is a necessity.

What makes your role within Vanderbilt special? 
I have greatly appreciated all of the opportunities I have had here at Vanderbilt.  I started here in 2005, not too long after the department was started.  From the beginning, we have always been encouraged to be 'life-long learners' and given resources to help us with that.  I am grateful to be able to be a part of interesting research that is looking at current problems in need of sustainable solutions.

Tell us about your life outside of Vanderbilt. 
When I am not at work, I am typically doing something outside.  I have friends from my days at Auburn with whom I vacation every year.  We have hiked in many beautiful places including the Grand Canyon, Alaska, Olympic National Park, Maine, and the Canadian Rockies.  For the last several years, I've also done a few sprint triathlons.  I don't burn up the course by any means; my goal is to have fun and simply to finish!  And oh yeah, I am an Auburn football fan -- War Eagle!

Finally, what is something about you that most people at Vanderbilt still do not know about you? (Until now, of course!)
When I was in junior high, my entire class had to enter an oratorical contest sponsored by our local Optimist Club.  Shockingly, this introvert made it all the way to AL/MS districts!  You never know what you can do until you try!

The Vanderbilt Department of Biostatistics proudly welcomes its newest students into the Master's and PhD programs for the 2018-2019 academic year!

In our Master's program, we have Ryan Moore joining us from the College of Wooster, Yan Yan from Middle Tennessee State University, and Yue Gao who recently received her master's degree from Peabody at Vanderbilt.

In our PhD program, Rebecca Irlmeier joins us from the University of Missouri, Julia Thome from Cornell College, Chiara Di Gravio has arrived from the University of Southampton where she was working as a Statistician, and Yi Zuo from University of Boston School of Medicine where she was working as a Lead Statistician.

We are so grateful to have these new faces here on campus. Here's a big congrats to an exciting new chapter in your life!

This week we are featuring Dan Byrne, Senior Associate in Biostatistics and Director of Quality Improvement & Program Evaluation in the Vanderbilt Department of Biostatistics.  Read on to learn more about his work and interests here at Vanderbilt.

What is your area of focus and what have been the major findings so far in your research?
My research focuses on how we can use biostatistics, predictive models, and artificial intelligence to improve health outcomes.  In our Learning Healthcare System Platform, we have created a "Dream Team," which is working on conducting large pragmatic trials during routine clinical care.  Recently, we published two papers in The New England Journal of Medicine showing that balanced IV fluids are superior to saline.  We estimated that these findings could save thousands of lives per year.  The next step in this research is to ensure that these safer fluids are ordered in the hospital and assess the impact on mortality.  In other words, have we completed the last mile of work in biostatistics to make sure our results are implemented in a sustainable way?

Tell us about your publications.
I have published more than 130 papers and one book, “Publishing Your Medical Research”; 18 years ago, I was recruited to Vanderbilt based on this book.

What is your current research interest and what do you hope to see come from it in the future?
My current interest is in testing with randomized controlled trials how artificial intelligence methods can be used to improve patient outcomes.  Our Cornelius team has created a large number of real-time predictive models, for example for readmissions and pressure ulcers, and tested these in randomized controlled trials.  We are now exploring Deep Learning methods and working to create the Vanderbilt Artificial Intelligence Lab (VAIL).  The current challenge is how to integrate predictive models and AI tools into hospital operations while conducting a randomized controlled trial.  This will be the area in which Vanderbilt can become a leader in this exploding field.

What is your best advice for aspiring statisticians?
My advice is to be relentlessly helpful and positive in teaching biostatistics and supporting physician-scientists so that they can become successful researchers.  Also, I would advise aspiring statisticians to become leaders at making forward progress in improving health outcomes and avoid the Brownian motion of academic medicine. Over the past 35 years, I have trained hundreds of physician-scientists, mostly in the MSCI program; and this approach has worked for me.

In your experience, what makes Vanderbilt special?
The research that we are doing in the Learning Healthcare System and artificial intelligence requires an enormous amount of collaboration and respect for the scientific method.  Vanderbilt is uniquely positioned to be a leader in this area based on our culture of collegiality and our strength in medical research.  It has been an honor to work with so many amazing people at Vanderbilt and see all of these programs that we created flourish and help others, for example: the Department of Biostatistics, The Biostatistics Graduate Program, Biostatistics Clinics, Clinical and Translational Research Studios, Go for the Gold employee wellness program, Flulapalooza, CRC Research Skills Workshops, the Learning Healthcare System Platform, The Master of Science in Clinical Investigation program, and the Cornelius predictive modeling project.  Before coming to Vanderbilt, I was a self-employed statistical consultant for 10 years.  Hopefully, based on this experience and our culture, we can be as nimble as entrepreneurs and as rigorous as academics to develop and test artificial intelligence methods in a way that impacts health outcomes.

Tell us about your life outside of Vanderbilt.
I have a wonderful wife, Loretta, and two great children, Michael and Virginia; and I enjoy taking adventurous vacations with my family.  I just returned from a 4-day sailing trip with my son Michael.

This week we are excited to feature one of our IT team members in the Spotlight series.  Shawn Garbett, a Senior Application Developer in the Vanderbilt Department of Biostatistics, tells us more about his interests and research. 

What was your draw to statistics and/or Vanderbilt?
I have always had a love of mathematical modeling throughout my career starting with hydrology models at TVA. I was hired into the Quaranta lab doing mathematical models of cancer progression here at Vanderbilt and got to work with a wonderful group. There was a desire to tie the models to observed microscopy data and I discovered the depth of statistical reasoning researching the problem. This led to statistics becoming a new passionate pursuit to the point I went back and got my masters at Penn State in applied statistics. Working with a department full of world class statisticians is a dream come true.

Tell us about a major finding in your current research.
On my current health policy project, I've found a technique that allows one to have tunnel states with memory accurately inside a Markov model. Many observed risks are of the form "For X years after event Y the risk is Z". This violates Markov assumptions as it requires memory of an event in time, but Markov models are a preferred method in the economic modeling domain. With this method discovery one can continue to the Markov modeling framework with minor adaptation without relying on ad hoc methods while having states with memory.

Tell us about a significant publication that you've contributed to during your career so far.
If I were to pick a publication to highlight, it's "An unbiased metric of antiproliferative drug effect in vitro". Mass screenings of cancer drugs were based on a metric developed back in the 1970s. The growth inhibition effects were being estimated without log scaling the observed cell sizes. Further complicating the observations is that there is a non-linear (even on log scale) effect as cell requilibriate to their new conditions, i.e. long term response is not short term response. A more robust measurement of growth effect could be made with the same equipment, but by simply log scaling data and shifting the time window of observation post equilibration. This has led to increased accuracy in cancer drug screening.

What is your philosophy about teaching and/or research, and what is your best advice for aspiring statisticians?
I think teaching and research go hand in hand, and love the fact that statistics is now part of elementary education in the US. Sarah Fletcher was a summer student in the Quaranta lab and I mentored her at the time. She wanted to really make the microscopy estimates we had as robust as possible and she educated me on how statistical reasoning was the best approach to tying modeling to microscope observations. I introduced her to Jeffery Blume and she went on to be one the first graduate biostatistics students here at Vanderbilt. She's now at Harvard. I was lucky to have her as a student.

I think the best advice for aspiring statisticians is to question every assumption. Make sure that one knows every assumption of the techniques being used, test them, and explore them.

What are your thoughts on controversial statistical topics such as the role of data science in the future, adjusting the p-value for multiple comparison, the choice between Bayesian, likelihood, or frequentists, ethical issues, etc.?
I think data science runs the risk of mass "plug and chug" approaches from folks who are not aware of the pitfalls of analyzing observation data. A majority of the really large data sets available in data science are observational. This is a big opportunity for statisticians because they've had years of research into this very topic and have many tools for dealing with it. I heard recently the term 'multiple regression' at a data science symposium referred to as 'artificial intelligence' multiple times.

Statisticians have worked with this AI since the 1920's! The value of statistical reasoning is now being realized on a global scale. I predict that over time the distinction between observational and random data will get highlighted far earlier in education, even possibly in introductory courses to address this issue.

I personally am attracted to likelihood methods in general, and like the idea that a p-test shouldn't necessarily be against a point estimate but a relevant set. On a related topic, the term "significant" has a very different meaning to those outside the field and is a continued barrier in communicating to a broader public. I like to use "discernible" as a substitute when communicating to a lay audience. Communication of statistical results is going to be increasingly important for rational choices in the public sector.

Tell us about your life outside of Vanderbilt. Do you have a significant other? Children? Pets? Hobbies? 
I am married to Lisa McCawley in the Department of Biomedical Engineering at Vanderbilt. I have 2 daughters, one attending Ohio Wesleyan and the other at Hume Fogg. We also have 2 cats. I love to play strategic board games and play piano, and on a cold cloudless night I can be found in a field looking through a telescope.

Finally, what is something about you that most people at Vanderbilt still don't know about you? (Until now, of course!)
I worked for many years doing formal models of software development for the government and on one contract wrote the control software for an infusion pump for emergency bullet wound treatment. It was the first closed loop device ever approved by the FDA. I didn't know at the time, but the client was the White House and the first deliveries all went to Air Force One.

On Sunday, July 29, the Vanderbilt Department of Biostatistics hosted its first ever Vanderbilt Night mixer at the Joint Statistical Meetings (JSM) of 2018 held in Vancouver, British Columbia. This is one of the largest statistical events to take place in the entire world!
 
Amazingly, there were more than 6,500 attendees, visiting from 52 countries. More than a thousand of those attendees were students.
 
After a full day of meetings and courses, our Department faculty, staff, students, alumni and several special guests attending JSM, gathered together to eat, drink, and be merry.
 
By hosting the Vanderbilt Night mixer, we were able to shed more light on our biostatistics program at Vanderbilt to those in the medical research community, while giving all of our department members a chance to unwind and talk more on a personal level. 
 
The event was so enjoyable that most stayed for the full two hours catching up and visiting like old friends do. The food was great, the city was awesome, and everything went off without a hitch!
 
Thanks to everyone who was able to join us for the Vanderbilt Night mixer and we'll look forward to hosting another mixer at JSM 2019!

For our next featured member in the Spotlight  series, we talked to Jennifer Thompson, a Biostatistician IV in the Vanderbilt Department of Biostatistics, to learn more about her research and outside interests.  Read on and enjoy!


What is the focus of your research and what have been the major findings so far?
My primary work so far has been with the Vanderbilt Center for Critical Illness, Brain Dysfunction and Survivorship. We work to describe, understand, and improve in-hospital and long-term outcomes among patients and families who experience acute critical illness. The center currently has about ten principal investigators and an incredible support team, all doing multidisciplinary work in pulmonary/critical care, anesthesiology, psychiatry, trauma, and palliative care research.

In 2013, we published an NIH-funded cohort study which described the huge burden of cognitive impairment among survivors of critical illness and how brain dysfunction during that illness is a risk factor for worse outcomes. We are currently working on R01 grants which look at the efficacy of medications used to treat delirium in the ICU, and outcomes for the use of different sedatives in ICU patients.

We have also worked to understand the mechanisms and phenotypes of delirium in the medical and surgical ICUs, to characterize and look for risk factors for brain dysfunction in trauma patients, and look for predictors of frailty and long-term functional and cognitive problems in ICU survivors so that we can try to modify our care and improve their experiences.

What was your draw to statistics and what lessons have you learned from being a biostatistician?
I'm analytical and practical by nature, and declared a math major in college without too much thought as to what I would do after graduation. I was exposed to biostatistics through a summer internship at TVA (of all places!), and realized it would be a perfect way to apply my analytic skills to important problems. After I finished my master's at UNC-Chapel Hill, Vanderbilt was hiring and I was able to move back to Tennessee, my home state.

The lessons I've learned over the years have been enormous! Of course my statistical knowledge has grown immensely, but I've also learned how to manage timelines and projects and personalities, and to communicate with all kinds of people - some of whom care deeply about the statistical details, and some of whom care not at all. :) I love being part of a team that truly works together to solve important problems, and biostatistics and my work here has been a great way to do that.

What is your best advice for aspiring statisticians?
My best advice is to have a mindset that is open to continually learning new things, both about data science/statistics and the subject area you're working with. It didn't take me long out of graduate school to realize how little I didn't know yet! And with statistics and clinical research in general constantly evolving, you'll never be finished, which is a little overwhelming but also really exciting.

Also, I cannot overemphasize how important communication is to this field. Your statistical theory means nothing to a clinical researcher if you can't explain what the numbers and Greek letters actually mean - and in a way that you and they can then explain to their clinical colleagues so that your work can actually make an impact. Sometimes this looks like just writing an email or speaking up in a meeting; sometimes it's creating a clear, concise data visualization that gets your message across better than three paragraphs of a Results section ever could. Often it will be both.

What makes Vanderbilt special in your experiences of collaborating with others?
One thing I so appreciate about the group I work with is that my statistical teammates and I are considered to be part of the team, rather than technical consultants who hit a few buttons and give them some numbers to plug into their manuscript. That has so much benefit for both sides, and serves to not only make my work life more fulfilling, but also to make the science better.

I'm really excited about current movement in the direction of openness and transparency in research. It's been a bit slow going in clinical arenas compared to other areas, given the hugely important concerns about patient privacy as well as other considerations, but I hope that it will soon be expected practice to share analytical code, make statistical analysis plans obviously and transparently available, etc.

Tell us about your life outside of Vanderbilt.
I love to both travel as often as I can (most recently to Japan!), and have Nashville as a home base - this is such a great city undergoing so much transition right now, and I'm excited to be here to watch and participate in it. I'm lucky enough to also live close to five nieces and nephews who get as much of my attention as they'll allow.  Outside of work, I'll often be found hiking in one of the parks around town, spending time with my friends and community here, watching movies at the Belcourt or seeing just about anyone at the Ryman.

Finally, what is something about you that most people at Vanderbilt still don't know about you? 
I didn't see the original Star Wars movies until 2010, when I was unexpectedly snowed in with my family for Christmas and we watched the entire series in a SyFy marathon.