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PHD Industrial Engineering, Operations Research

Growing up in Seoul, Korea, I was immersed in a city which has grown into a truly global city. I clearly recall looking up at the skyscrapers, at the feet of giant whose shadows stretched for miles; the engineers abilities and imagination seemed staggering and limitless. The city is truly enormous, the world's second-largest metropolitan, with half of the entire South Korean population calling the greater Seoul area home. More than this, Seoul is my country's chief economic, political and cultural center. It is no wonder I grew up in awe of the engineering accomplishments that have made Seoul so very unique. And in recent years, the international population has been steadily growing, with many citizens being fluent in at least two languages, as I am.

Since my time as an undergraduate, I have maintained a consistent path to Operations Research, and a Mastery of its fundamentals. I had a strong interest in computational statistics especially handling large-scale datasets. In data mining, statistical database, multivariate statistics, computational statistics, econometric analysis classes, I became fluent in my handling of large datasets and running simulations using SAS, S-Plus, Minitab and Matlab. My undergraduate education flowed logically into a graduate Industrial Engineering degree, which was focused primarily on stochastic process, data mining techniques and feature extraction methods. Throughout this time I increased my proficiency in English, even spending approximately two years at the University XXX, a school in which I earned a UBC scholarship for the highest GPA out of 89 other Korea University students.

During my Master's research, I learned some very valuable lessons, not the least of which was during my interpretation of biomedical data project, with my advisor professor Woojin Chang. While I was to explore the non-stationary signal type data in ovarian cancer and develop feature extraction method and make a model for prediction of ovarian cancer in early stages, I lacked the requisite knowledge of biomedical data to apply the correct methodology, and, thus, my initial results were not satisfactory. From this, I learned some very important lessons: insufficient knowledge in the field and general statistical analyses under strong assumptions often cause problems in applying to various fields. Learning from this experience, I set about the project with renewed vigor, re-adjusting my approach. Still there were more lessons to be learned, particularly that methods adopted from another field of study such as wavelet transform can be more suitable for the data that do not satisfy strong assumptions. Data exploration was done by careful examination of peaks of signal in time domain and wavelet coefficients in frequency domain. Large signal type and non-stationary data sets are wavelets transformed so that distinct features of the data are extracted in wavelet domain rather than time domain. The application of my wavelet-based feature selection method to a mass spectrometry data set for ovarian cancer diagnosis resulted in nearly 100% classification accuracy when statistical classification methods were employed. With this research project, I won Master's theses competition and published my paper in the Journal of Korean Institute of Industrial Engineers.

While the domain of my professional career has been national defense and security issues, the work has always been firmly related to operations research and or statistics. There are clear parallels between the working environment I have been immersed in these past few years as a researcher, and the IEOR. On the most practical level, working for the XXX Institute of Defense Analysis, Center for Modeling and Simulation, we were a XXX government-funded research organization; the IEOR as a department funds their doctoral students. The pressures were very real, with my work supporting such stakeholders as XXX Joint Chiefs of Staff and the Ministry of Defense. Moreover, I was working in a multidisciplinary team environment and I would find the transition near seamless to IEOR academic work.I have worked for the Center for Modeling and Simulation at XXX Institute for Defense Analyses since 2006.

As a research analyst, I participated in several XXX government sponsored defense modeling and simulation projects. Often I cooperated with domestic and international organization including XXXs Army Materiel Systems Analysis Activity. While XXX has given me an excellent education in terms of being an effective researcher, I feel I will quickly exhaust every possible avenue of promotion and challenge at my current level of education. More than this, though, I feel motivated to return to the academic world for further development for this reason among one other. XXX research as opposed to academic research as defense research projects tend to last one year or less, and need immediate results, affecting XXX policy maker's decisions and, as a result, the research is not always conducted under the most ideal circumstances. To be completely honest, I was frustrated by spending half of my time gathering data and studying defense knowledge, which was critical, of course, arguably the most important, and the precious remaining time performing research. I was left feeling that deeper analysis and research was blocked by the time limitations of projects. This was simply not a good research paradigm.

The work that I have been involved in with the XXX Institute of Defense Analysis, utilized a simulation based acquisition package called Synthetic Theater Operations Research Model, a package which is based on operations research (OR), with methodologies such as linear programming, scheduling, transportation problem, and stochastic simulation. I was particularly intrigued with the OR features and this is one aspect of my desire to seek out the finest, most specific education possible in this area.

For the future, I envision returning to the classroom, this time as a professor attached to a university with ample opportunities for ongoing research, research which I can expose my students to. It would be an excellent opportunity to expose students to relevant, current research with real-world applications. Given my defense department research experiences and IEOR education, I feel that I would become a very effective professor, indeed. There are many opportunities in the field of Operations research, a field which is inherently multidisciplinary, and that could benefit from incorporating such elements as finance, biology, and homeland security. Through quality research programs, I will be able to devote my time and energies to making progress in these relevant and largely unexploited studies.The IEOR program and its opportunities to work with professors as teaching assistants, being involved in the curriculum will lay the necessary groundwork for my own burgeoning teaching ambitions. I cannot think of a more ideal environment in which to learn not only my own subject matter, but gain invaluable exposure to a quality curriculum, its design process, implementation and management. Even within my two years of teaching assistant work, I was not able to participate at such a level, adding my own insights into course design. However, I am certain I can work with great confidence and ease regarding the more routine administrative tasks, and grading given my background.

The overall goal for my future professional development and research would be to explore viable paths to solving quantitative decision problems, equipping myself with in-depth knowledge of optimization techniques, statistical methods, and simulation. I envision my studies and research leading to streamlining present methodologies and saving valuable resources with a constant eye on optimizing decision making.

IEOR has a reputation for being one of the finest Engineering and Applied Sciences departments in the nation, with a wealth of disciplines that are genuinely career-driven. Upon researching the faculty's research interests, I find that they are a match for what I have studied, researched, including stochastic process, statistics, modeling and simulation. Moreover, I feel that I would be an excellent complement as I have interest in and some experience in a variety of fields such as biomedical, national security, and financial engineering. IEOR offers the opportunity for exposure to all of these fields.

The reputation of IEOR is more than impressive. IEOR's doctoral candidate selection process alone, with an approximate 3% acceptance rating, is indicative of an educational experience that guarantees not only quality, and conceptual continuity, but a low student-to-professor ratio; an intimate and personalized relationship, one in which I feel that my academic purposes will be brought to fruition. I look forward to the opportunity to develop myself as a creative leader for Operations Research. Your time and consideration is greatly appreciated and I eagerly await a personal interview.

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