This is an example personal statement written by a student who was accepted and
enrolled in the MIT EECS PhD program.
_____________________________________________________________
Throughout my life, I have been compelled by a desire to understand what
fundamentally drives seemingly complex systems. In high school, I took a class that
dissected the ideas in Hofstadter's Godel Escher Bach. One idea that resonated
strongly with me is that large observable phenomena are usually made of smaller,
elusive yet simple components. This idea was reinforced by my time at XXX
when I discovered the applications of discrete differential geometry (DDG) in
computer graphics. The DDG framework beautifully constructs fundamental
building blocks in discrete geometry, leading to simple and intuitive descriptions
of the complex behaviors of hair, cloth, water, and more. In addition to helping
me discover my primary interest, my past research experience has given me
a large, eclectic background. I have also held several teaching assistant (TA)
positions, and have experience creating course materials and assignments. I want
to continue studying simulation and geometry processing as a university
professor. Earning a Ph.D. in Computer Science at MIT would allow me to pursue
my research interests and give me new opportunities to contribute to the field.
My past research experiences have helped me discover new ways of
thinking and pinpoint my interests. In Spring and Fall of 2014, I joined Prof.
XXX and Dr. XXX in studying the control of decision making. An earlier paper
by the XXX lab provided compelling evidence that the inferior lateral prefrontal
and frontopolar cortex act as a hub of arbitration. We sought to further validate this
result by studying the arbitration between model based (MB) and model free (MF)
learning using fMRI data and Dynamic Causal Modeling (DCM). Understanding
this arbitration would enlighten us to how decisions and learning occurs in the brain.
I computed the exceedance probability for hypothetical biological networks and
used similarity scores with known brain networks to determine the most likely
models. We then perturbed the remaining models and iterated DCM analysis to
obtain the best model. I learned how it is possible to incrementally gain insight into
the behavior of something as complicated as the human brain. While I greatly
enjoyed learning the background, and performing the analysis to obtain results,
ultimately I did not have the necessary background in neurobiology to continue.
In the summer after my junior year, I participated in the XX Program
(XXX). I had the honor of studying quantum secret sharing (QSS) with Professor
XXX. The classical (n, k, L) secret sharing scheme encodes L symbols (the
secret) into n symbols (shares) such that any k of the shares can be used to
recreate the original secret. Varying degrees of security allow for partial leakage
of the secret by fewer than k shares. We expanded QSS by defining
quantum strong security, a far more nuanced condition than its classical analog.
Furthermore, I created a QSS protocol and proved that it holds the integrity of
quantum strong security. Strong quantum security is critical to the eventual use and
safety of quantum computation. This work was published in XXX. During the
weekly lab meetings and discussions with my mentor, I gained an international
perspective of higher education and was exposed to many exciting
mysteries in quantum information. During the weekly lab meetings and
discussions with my mentor, I gained an international perspective of higher
education and was exposed to many exciting mysteries in quantum information.
Briefly introduce your
research interests and
background
For each experience,
clearly describe your
research problems,
specific contributions and
quantifiable outcomes to
demonstrate your skills