I conferences. Above all, I learned to

I have been ‘a jack of all science’ my entire life. I chose biology as additional subject with higher mathematics, physics and chemistry in both secondary and higher secondary level. Despite everyone’s assumption that I made terrible mistakes and would perform poorly, I somehow achieved the highest grades and merit positions in both exams. The secret lies in the eternal synergy of knowledge from diverse background of science, which always mesmerizes me. When I was introduced to biomedical instrumentation, electromagnetic courses and personal interest of computer programming during my undergraduate years, I wanted to study in a field where interdisciplinary research create synergistic technologies. Bioengineering is that field where I can combine math, engineering, computational knowledge with biology to design tools that improve human life. Specifically, in biomedical imaging, physicists invent devices by harnessing the laws of physics, chemists create fluorescent biomarkers for lighting up tissues in molecular level, computer and biomedical engineers animate and process the image for better resolution and analysis. I found it fascinating and chose as my undergraduate thesis. Imaging of the most complex organ- brain, intrigued curiosity in me. While studying imaging modalities, I learned the significance of medical imaging in diagnostic and therapeutic applications. Eventually I started research in brain tumor detection from MRI images.    As a newly minted researcher, I experienced a paradigm shift in my syllabus-based perspective. In this journey, I learned that knowledge has no limit. Those days of studying and experimenting with different imaging techniques invoked a sense of creativity in me. I also gathered hardware-based knowledge of MRI and explored computational imaging in MATLAB. I observed combined segmentation, homomorphic filtering in frequency emphasis, isolate tumor regions efficiently from healthy brain tissues using intensity difference in luminosity. And edge detection maps the metastasis with respect to the skull and other brain parts. This novel method of 2D MRI processing prompted two proud moments of my academic life: receiving runner-up prize in imaging competition and publication in IEEE after presentations in international conferences. Above all, I learned to evaluate the extent of dedication behind every innovation.Tremendous advances in computational techniques motivated me deeply. To hone my programming and computational skills, I took a certified course on MATLAB authorized by Vanderbilt University. The lectures, coding assignments by Dr. Fitzpatrick revived my passion for computational imaging. Self-guided projects on Convolutional Neural Network(CNN) for real time object detection is the outcome of that motivation. Currently, I am working to train a neural network to recognize medical image features. A graduate degree from University of Texas Dallas, confirms my life’s goal to pursue research. The higher education I receive in this great institution will empower me to develop better and cost-effective diagnosis techniques for millions of people who cannot bear the expense and are marginalized out of clinical treatment. Future breakthroughs await in analysis of automated, digitized microscopic images and image guided techniques. Along with advanced sensors, multimodal and parallel imaging of different technologies like US, CT, PET, fMRI and even X-ray, there has never been such amazing time to study bioimaging. Although, I desire to work in this vast interdisciplinary field, at present I am interested in the research conducted by Dr. Kenneth Hoyt in Ultrasound Imaging and Therapy laboratory. I share the same research interest with him in tumor and cancer detection. Precisely, I will focus to contribute in real-time volumetric dynamic contrast-enhanced ultrasound(DCE-US) and 3D ultrasound imaging techniques. Also, biomarkers and targeted drug delivery imaging are the intellectual neighborhoods I find exciting. Ironically, we live in an era, where smartphone cameras are widespread and have higher megapixel resolutions, processors, but fewer than few are used in image-based first-hand diagnosis. So, there are challenges and opportunities to explore. As for myself, working in different engineering fields allowed me to meet people from diverse backgrounds. This experience helped me to collaborate with many fields’ experts. Working in the professional environment also taught me to lead and be independent decision maker. Years from now, I portray myself as a researcher and academician promoting strong leadership in healthcare and medical innovation. This career niche naturally fits my cherished dream. Thus, a Master’s in Bioengineering that specializes in medical imaging will be an ideal platform to equip me with the skills, knowledge and academic preparation needed for further study and research.    I was born early in the morning under one sunny, blue sky roughly a year after the deadliest cyclone my country ever faced – that took thousands of lives and everything my parents had. Despite losing everything, my parents never lost the dream of a new life from disaster shelters. Their immense hard work for the family made their dream come true. From an early age, optimism is the lesson that I learned from my parents. And I crave to see myself living a meaningful life that can impact the lives of others’. When I talked to the brain tumor patient for appropriate consent to share his MRI data in my thesis/research, he was optimistic that he will be cured one day. His story made me optimistic that one day I can effect a cure for people like him. After all, isn’t optimism the best way to see a life?

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