I am interested in pursuing a PhD program in biomedical engineering with aspecialization on biomedical imaging.
In particular, I would like to work on developing newnon-invasive imaging and computational analysis techniques in order to study and diagnosediseases. For me, it is a fascinating area as it combines mathematical modelling, physics,signal and image processing, and medicine. A PhD program in this area is a cornerstone inmy long-term goal of becoming a faculty member in the area and improving health care.From the early days of my studies, I have been excited by the idea of an academic career.During my junior year in my electronic engineering undergraduate studies, I had theopportunity to participate in several projects on digital signal and image processing thatcompeted in several national project contests. On my sophomore year, I attended aconference where I was impressed with the wide range of applications that electricalengineering and signal processing could have on medical practice. It was then when Idecided that I wanted to specialize on biomedical engineering. For my undergraduate thesis,I developed a recognition system of laryngeal electromyography signals for control.
Thiswork was later published in IEEE Latin American Transactions.Wanting to specialize in biomedical engineering, I applied and was accepted into a fullyfunded PhD program in the USA. Unfortunately, due to a personal loss, I had to reject theoffer and stay in Peru to support my family. This did not keep me from pursuing my careergoals, even though I stayed in Peru, I continued my education in biomedical signals at PUCP,where I entered a Masters program and was given the opportunity to work as a researchassistant in the Medical Imaging Laboratory under the supervision of Professor RobertoLavarello.
Here, I diversified my background and gained experience in linear systems,biomedical imaging, signal processing, machine learning, inverse problems andoptimization. More importantly, I was able to grasp the importance of developing novelimaging modalities as means to improve diagnoses and to gain a deeper understanding ofdiseases: for instance, by improving the resolution and contrast of ultrasound images wecould see pathological hypoechoic structures or small reflectors that would otherwise beoverlooked.This year, I successfully defended my master’s thesis on the development of newadaptive beamforming technique for medical ultrasound images. This technique integratesphase aberration correction (a way to correct ultrasound wave distortion) into an adaptivebeamformer (a method for improving resolution and contrast). The developed techniqueimproves performance over the state-of-the-art and might be useful, for example, inmicrocalcification detection in breast screening.
I have presented this research at twoconferences: the 2016 IEEE Engineering in Medicine and Biology Society Conference and the2016 International Ultrasonic Symposium. Additionally, I have first-authored one journalarticle published this year in Ultrasonic Imaging and I am preparing the resubmission of asecond journal article to the IEEE Transactions on Ultrasonics, Ferroelectrics, andFrequency Control.Additionally, as this thesis project was a joint effort between PUCP and StanfordUniversity (co-supervised by Professor Jeremy Dahl), I have had the opportunity to spendthree months as a visiting research student in the Department of Radiology at Stanford.Aside from working on the experimental part of my thesis, I also participated in anotherproject with Dr. Dahl’s Stanford team on the estimation of speed of sound maps in tissue with pulse-echo ultrasound.This was an interdisciplinary endeavor that involves experts inultrasound, in x-ray and CT, and pediatric clinicians. The application is to noninvasivelyassess Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH),two diseases difficult to identify even with biopsy. This was an interdisciplinary endeavorthat involved engineering experts in ultrasound, x-ray, and CT, as well as pediatric clinicians,and was presented at the 2016 Ultrasonic Imaging and Tissue Characterization Symposium.
In addition, I have also worked on the automatic detection of B-lines (artifacts normallyrelated to pneumonia) using AM-FM features and machine learning algorithms. This projectis aimed at providing more automated procedures for pneumonia diagnosis in pediatricpopulations for rural zones of Peru.After finishing my master’s, I continued working on the digital signal processinglaboratory at PUCP, where I increased my experience on image processing, inverse problemsand optimization techniques. I have presented a novel fully incremental robustbackground/foreground separation algorithm at the International Conference on ComputerVision and I have also developed new faster algorithms for mixed norm regularizationproblems. I have also worked on my own on neural signal processing. This year, I havepresented an abstract at the annual meeting of the Society for Neuroscience (SfN) detailing across-patient seizure detection system in EEG recordings using deep learning.
I won aTrainee Professional Development Award from the SfN that allowed me to attend andpresent my work.Looking forward, I want to continue my research career on medical imaging and imageprocessing, by developing new imaging and analysis techniques, and I am convinced thatYale University is the optimal place to follow my goals. In particular, I am interested in theresearch being conducted by professor professor James Duncan on image analysis forcardiovascular and brain structure applications, in the work of professor Todd Constable onnovel fMRI and quantitative analysis techniques to study brain function, in the research ofthe research of professor Fahmeed Hyder on translational fMRI to study metabolism andbrain disorders, and also in the research of professor Hemant Tagare on heart motionanalysis.In summary, I believe that with my background in signal processing and medicalimaging, I would thrive in your program.
I am convinced that Yale is an optimal place tocontinue my studies as it combines the strengths of one of the best medical schools in theworld with state-of-the-art engineering research, and this unique mixture would allow menot only to develop new imaging technologies but also to be able to translate them intoclinical practice and make a real impact in the quality of healthcare.