Quinn Orion Flynn McFee is pursuing a degree in Applied Math & Statistics with a minor in Physics & Mathematics from Johns Hopkins University. They have diverse interests in math, art, music, and science. Through their coursework and research experiences, they have developed skills in data analysis, computational statistics, and database management. Currently, they are working on an interactive statistical map using R and are interested in applying their skills to pharmaceutical testing and analysis.

1. Quinn Orion Flynn McFee
Applied Math & Statistics
Physics & Mathematics minor
3020 Guilford Ave
Baltimore, MD, 21218
610.639.1577 qmcfee1@jhu.edu
Since the beginning of my undergraduate career at Johns Hopkins I have had major changes in the vision
of myself as a future professional. I come from a very strong, mathematical background and have
always been very influenced by something that is both tangible and applicable, yet mysterious in the
most fundamental ways. However, my heavy involvement in music, art and science seemed to pull me
in opposing directions. In addition to the calculus available in high school, I also earned full marks on my
advanced placement three-dimensional art portfolio and it was recommended I go to art school. My
interests and pursuits at first glance seemed very far apart, but I’ve come to see them as
complementary and equally beautiful. In fact, this spring I will have an art exhibit of an ongoing series of
anthropomorphic sculptures (available to view from my resume) in which each piece was made up of
large prisms with every face made of an irregular polygon. It was through the process of mixing math
with art that I realized how many commonplace objects made beautiful by their mathematical
decompositions.
I matriculated into Hopkins pursuing Physics, which I revere for our universe’s display of math,
both fundamentally beautiful and deep, and often overlooked from day to day. I took the physics major
head on as a freshmen, studying multivariate calculus my first semester and beginning the track set
forth. The physics department trained me to think analytically about complex systems, simplifying them
into fundamental mechanics that can be described by rigorous mathematics. As I advanced at Hopkins, I
was challenged by more abstract courses like special relativity, wave phenomena and quantum
mechanics. At that point, any previous classical intuition was unreliable and deceiving, but I noticed the
math always talks. I began to develop a mathematical intuition for them. It is misleading to ‘picture’
what an electron or a pole-vaulter running a seventh the speed of light through a barn should look like.

2. Instead, I looked for symmetry, phase shifts, and probability distributions to see how systems ought to
behave.
My junior year I started doing undergraduate research for the High Energy Physics Department,
writing signal selection programs and fitting data to identify special muon decays of the Higgs and Z’
boson jets using a C++ based language called ROOT. In a few days, I had to build this language from the
source code and pick up the language on the go independently. I have grown used to rely on myself and
adapt to new situations quickly. I became less interested in the physics of particle collisions and more
interested in properties of their distributions. The same distribution for the energy-momentum of
particle collisions could be used to describe the distribution of the number of patients in a hospital over
a year. It was exciting to use data straight from CERN and Fermilab, but, as the research continued, I
grew more interested in the structure and management of these enormous databases. It was then that
I added Applied Math and Statistics to my major and became a Physics minor. Discrete mathematics
opened my mind to applications of math beyond the natural world. The more I learned as an Applied
Math student, the more I saw the beauty in abstract or artificially constructed relationships and the
mathematics that describe, analyze, and optimize these relationships to solve a motley of real world
problems or even a game of marble solitaire. Before studying applied math, I would have never known
how interesting an airline schedule could be.
I am presently working on a completely data driven research project, developing the database
for a global, interactive statistical map in R, which has only made me more interested in managing large
amounts of data, making sense of it, and reorganizing it in a meaningful way. I am now equipped with
many tools for running hypothesis testing, different linear and robust regression for parameter
estimation and running residual diagnostics for determining (non)normality or (non)constant variance.
In addition to R, I am continuing to learn more data driven packages in development languages like
python (numpy, scipy, etc.) Above all I have gained the perseverance to take onto any project and see
it through to the very end. Currently I am interested in using computational statistics to help design
pharmaceutical testing and analyze the effectiveness of these tests, imaging, and data mining. I wish to
not only contribute to the pool of knowledge in the future, but use my love of math to further
contribute to the wellness and safety of others and our environment. I would love to contribute in any
way I can and I look forward to hearing from you.