Lucy Shen, Smith College
Not until recently, I find how much BDSI has changed my academic life. I used to be confident and self-satisfied about what I learned, the number of projects that I completed, and the grade that I received for statistics and data science class before this summer. However, the 6-week program gave me a chance to retrospect myself; I eventually saw a bigger world, interacted with people who have same passion about machine learning applications in public health and put my hands on such complicated MIMIC III dataset that I could never imagine before. I should also thank to professor Wiens, professor Koutra, our GSI Shengpu and all my teammates. Working with them definitely made me more productive, organized and helped me develop leadership skills.
When I am back to Smith College this semester, I audit the machine learning class
which I took one year ago but forgot lots of conceptions. I found that because the
morning lectures of BDSI provided a review briefly, I still remembered 90% of the
algorithms and formulas. Compared with one year ago when I took machine learning first
time with lots of confusion, this semester I really touch the core of professor's
lecture this time. Besides, so many changes occur without notice, I developed a sense
of comprehensive view after this summer. Right now, whenever I want to solve a problem,
whether a problem in statistics or in other fields, I always start with a general
pipeline (what I learned in my group project) and follow the pipeline in the execution.
The most important point is that it comes clear to me why I want to be a data scientist.
Even though I got upset and annoyed by bugs from time to time and even though I stayed
up so late at night, I valued the potential application of statistics and data science
researches the most. Hearing so many stories about phenomenal discoveries of data
science in public health from journey lectures and from reading cases, I hope one
day I can also be one explorer in this field.
And I have to say that your words at the end of this summer almost made me tear down and became one of the motivations for me recently, "What are you doing everyday? Beautifying your CV or doing something meaningful to others."
As a graduating senior, I feel sorry that I did not attend BDSI during the first summer break so that I could decide my major earlier and took more classes and researches. I made up my mind to continue to graduate study in this field and hopefully one day, I can also be a journey lecturer for BDSI.
Fengling Hu, Amherst College
As I look back at the experiences that have shaped my academic career, I remember you sharing some of the emails you had received from past BDSI participants with all of us during our experience at U-M. I wanted to write a brief (or maybe not so brief) testimonial/update to you in that sentiment, describing how BDSI has adjusted, transformed, and advanced my academic trajectory.
If you remember, I was one of the few pre-med participants in my year. Entering BDSI, I was nearly 100% set on pursuing a career as an MD; I saw statistics only as a tool for my current work in basic science research and future work in clinical research. However, at BDSI, I saw how cool statistics theory could be through morning lectures and learned how much impact biostatistics could have on patient care through journey lectures. BDSI was a turning point in my perspectives on statistics and in my life goals.
One goal of BDSI is to inspire participants to pursue graduate studies in statistics, and it has done just that. From my dream to pursue an MD, BDSI influenced me to pursue an MD-PhD, with the PhD in biostatistics, bioinformatics, or the like.
I've already written my statements, submitted my applications, and begun to receive a couple interview invitations for the coming months! I even applied to U-M's MD-PhD program (with the Department of Biostatistics) and hope to hear back from them soon so I can continue to learn from all of the BDSI faculty.
Thank you so much for opening my eyes to this fascinating and powerful field. I'm really excited at the prospect of doing more work in biostatistics. I hope to have the chance to write back with more good news in the future!
Dan Hartman, University of Chicago
its been a big big summer we've had fun by the dozens
gonna pack our bags soon, leave this hall called couzens
but in a couple'a weeks, you're gonna get that itch again,
and make a return to the old u michigan
back to pedro and his kid, and sophia and ishpreet,
back to frita batidos and back to hunting for a seat
the days were hot but you guys are hotter
so hit me up unless boni drops my phone in the water
the server was down, but it's just as well
need another 6 weeks just to navigate shell
and our singles had space but i think we need more
cause akshay somehow used up all 32 cores
and i know, i know, the lectures are a bummer
but it's give and take in this big big summer
and if there's one thing to take away from this song
some models are useful but all models are wrong
And I just really wanted to express my appreciation for the conversation we had after the end of the program. It's really helping me to frame a lot of my questions regarding my future. But more than that, I'm just so thankful for BDSI and all of the work that you and the rest of the staff put into making it the experience that it was. I took from it so much more than I thought I would.
Jonathan Boss, Michigan State University
BDSI 2015, now U of M Biostatistics MS '18 Candidate
"The summer program here is unique in that it operates at the intersection of computer science, statistics, and human health. It is crucial to expose undergraduate students to the cutting edge of biostatistical research, in order to invigorate them about the direction the field is going."
Deeksha Pai, University of Michigan
"So, we had some struggles from the start
Downloading jupyter notebook is not for the faint of heart
I'm just kidding, most of us used Rstudio anyway
There was the occasional python user but anything else was so yesterday
Understanding spatial bias was not an easy task,
We would ask, every day, wait, what's a microarray and what's a plate?
And to be honest, we still never really got that part straight.
8x8 spots are on one well plus 95 more,
16 special wells, control spots, what else could you ask for?
All the heat maps we made.. man, you would think we were on fire!
And we were, so hopefully none of you want to retire.
We learned so much about R and machine learning, thanks to our mentors
Professor Gagnon-Bartsch, all these brilliant designs were yours.
Hopefully we've done your project justice, and all went well.
Professor Tewari, thanks for the great talks, they were swell.
And let's not forget Young and Greg, the best GSIs with the best R code.
We thank you guys for the complicated functions that you graciously bestowed.
Our little machine learning group of 12, man we've come a long way.
Though I'm not sure any of us ever want to look at another bioassay...
While everyone else stayed in SPH, to cc little we all walked,
Sitting in that hot little classroom, but hey, we really rocked!
We've got the best models in the bus-in-ess
Cross validating so hard, we don't even KNOW what over fitting is.
So many decision trees, forget Nichols, call us machine learning Arboretum.
Heres where I say something statistical so I can end with- degrees of freedom...
Obviously I'm running out of rhymes,
So I'm going to end this fast,
Data Mining and Machine Learning and BDSI were a blast!! "
Miriam Goldman, Arizona State University
"I really enjoyed all the social events and the opportunity to meet so many nice, different, people who were interested in biostats."
Ben Sadis, University of Michigan
"I really would like to thank everyone who put effort into making this program happen…" "It was really neat to have the opportunity to interact with and learn from so many professors and researchers who are leaders in their fields."
Marissa Ashner, Illinois Institute of Technology
"I learned more about biostatistics and big data than I ever imagined learning in six weeks, and I think all of the knowledge I gained here will be useful for continuing my education."
Tahmeed Tureen, University of Michigan
"My experience with BDSI was phenomenal. I met incredible faculty members and researchers from several disciplines such as statistics, biostatistics, and computer science. Some of these people are really famous. There was a point during my time with BDSI where I was explaining what 'Survival Analysis' was to the guy that is known as the 'Guru of Survival Analysis'... Me, an undergrad was explaining the rudimentary aspects of a statistical method to the guy that is world famous for that method... Just talking with and being around these people really cemented what I want to pursue later in my life. If I could one day become a part of something as amazing as the University of Michigan School of Public Health and have my work impact people's lives in a positive way, I'd consider all these hours I put into school worth it."
Danielle Demateis, The College of New Jersey
"I really appreciated and felt Bhramar's dedication toward the program. Her journey lecture and outreach has inspired me to follow her path of being a female leader in biostatistics."
Gabriel Goulart, Cornell University
"The Institute introduced me to a lot of different concepts regarding to Big Data and Biostatistics. The multi-disciplinary of the Institute is the major strength of it. Also, the opportunity to work with different people from different fields was unique."
Chinwendu Nwokeabia, Notre Dame of Maryland
"The journey lectures are amazing, and very helpful in providing a snapshot of potential careers after graduate school. The sense of camaraderie as the weeks passed was great and that was mostly due to seeing each other outside of the classroom. Many of the lectures, particularly the professional development and programming ones were very helpful; I do not have much experience with programming, so I am grateful for the chance to have a little practice in it."
Pooja Iyer, University of North Carolina
"I learned so much — not only about public health — but about my potential future and gained experiences that I would not have received anywhere else."
Rima Das, Massachusetts Institute of Technology
"My favorite part was seeing how big data is applicable in so many fields."
Michael Thompson, University of Massachusetts
"As an undergraduate, you're trying to figure out where to go and how to get there. One of my favorite parts of the program were the journey lectures where you get to see how faculty started out and how they got to where they are today."
Tianna Burke, Howard University
"I learned a lot about different subjects and I started learning about coding online after the institute."
Eli Ben-Michael, Columbia University
"Working with students and professors from many backgrounds was very valuable to me. The institute exposed me to many ideas from many fields that I may not have seen otherwise."