As Prof. Verghese and supported by an interdisciplinary team.

As an only child of engineering professors, I grew up on Bilkent University campus, an intellectual
oasis in Turkey. Prior to joining MIT, I shadowed doctors and witnessed surgeries thinking
that I can fulfill my desire to impact lives by becoming a surgeon. Prof. Lander’s biology
class was an eye-opener. Through his vision of deciphering information encoded in the human
genome, I realized that medical research can advance medicine at large. My aptitude and love
for engineering pushed me towards my goal: to pursue a Ph.D. in biomedical engineering and
do interdisciplinary research.
My first taste of such research was at the MRI center of Prof. Atalar. To reduce the amount
of eddy currents induced on an RF shield, improve the SNR of the image, and minimize the
loud noises of scanning, I designed several RF shields and evaluated their performances using
simulations. I learned about conducting scientific literature review, testing different models,
and presenting my findings.
I experienced the excitement and the challenge of making high-impact contribution at the
Graybiel Laboratory. To improve the monitoring of the dynamics of dopamine neurotransmission
in the brain, we wanted to develop dopamine sensors that affect physiological processes in the
brain minimally and sample at high spatial densities and wide spatial distributions. I was tasked
with building and testing exquisite carbon-fiber sensing devices. The fragility of the carbonfibers
and the unforgivingness of the process made it extremely tough. I persevered and built
many devices that were later used in vivo in non-human primates. My second project involved
developing, building, and testing a new set of instrumentation that would allow recording
dopamine from an increased number of sites. I accomplished this goal after a long process of
examining various methods of insulation for noise reduction in the recordings, designing and
building printed circuit boards, and testing the new instrumentation with numerous sensors
both in vivo, by conducting rat surgeries, and in vitro. The sensors, ten times smaller than
their counterparts, were able to record from up to 16 sites concurrently. Although this process
was full of many challenges and failures, its potential to enhance Parkinson’s treatment was a
constant source of motivation. Being an integral part in both the research and the write-up of
two papers disseminating our findings that might enhance the quality of lives is an experience
I would like to pursue through my life.
As part of the yearlong Advanced Undergraduate Research Program, I am currently conducting
research supervised by Prof. Verghese and supported by an interdisciplinary team. The aim
is to use capnography, the measurement of CO2 concentration in exhaled air, to develop a
non-invasive and accurate diagnosis and monitoring method for respiratory conditions. A simple
mechanistic model that successfully diagnoses chronic obstructive pulmonary disease (COPD)
patients is available in the literature. To extend this nonlinear mechanistic model to other
respiratory ailments, I am developing and implementing various low-complexity mechanistic
models to evaluate their success in fitting measured data and providing estimates for several
underlying respiratory parameters such as tidal volume, pulmonary compliance, and flow
resistance. I already developed a novel model that successfully represents features of congestive
heart failure (CHF) and differentiates between CHF and COPD capnograms. Next, I will create
mechanistic model-based algorithms that will determine a patient’s respiratory condition in
real-time using a capnograph. This elusive opportunity to take charge of a project and to work
with Prof. Verghese one-on-one has greatly enhanced my growth as a researcher. We hope to
compile our findings as a paper during Spring 2018.
I worked as a data scientist and software engineer in two healthcare companies. Throughprojects aimed at improving the efficiency of healthcare, I mastered my skills in applied computer
science. Working with business analysts, medical doctors, and product managers improved my
cooperation and communication skills in multi-disciplinary teams. During January, I will intern
at Phillips Research where by employing machine learning I will analyze and determine features
in medical images for CHF diagnosis and reinforce my knowledge in respiratory ailments.
MIT taught me to overcome and enjoy challenges. In a digital electronics course, my partner
and I decided to build a speech recognition system. We were warned that implementing the
Fourier Transform and applying filters in real-time would be hard. We persisted and the end
result was exhilarating. In another project, when I was not as lucky with my partners, I took
over their incomplete parts to ensure a decent completion.
Growing up with academicians, I was lucky to observe and receive great teaching. I taught in
a classroom setting when I was invited to become a Lab Assistant for an introductory EECS
class. I guided students as they worked on software and design labs. It is very fulfilling to
see the transition from blank stares to enlightenment. I believe that teaching structures my
thought process and makes me a better researcher. I aspire to become an academic to teach,
use, and generate knowledge to ultimately have an impact on lives. I would not have found my
passion if it were not for the countless opportunities and support I received. As an academic, I
wish to provide the same encouragement to others trying to find their paths.
I truly wish to surpass my solid undergraduate foundation through Ph.D. studies at Yale. BME
Department homes many distinguished scholars conducting high-impact research in Biomedical
Imaging, my area of interest, and the distinctive Yale opportunity to research across schools
is fascinating. The researches conducted by Professors Duncan, Carson, and Papademetris
especially appeal to me as I believe with my coursework preparation on signal and image
processing, computer vision, and deep learning, my research experiences on MRI and in a
neuroscience lab, and my software development internships, I have the preliminary preparation
and the enthusiasm to delve into Special Investigations with them.
I only had a glimpse of the world of research. I would love to join the Yale family and persevere
in pioneering medical innovations touching lives.