Graduate / SOP for Master of Science in Advanced Methods & Data Analysis [9]

I am applying for this master program and deeply appreciate your help to proofread my essay!
There are no specific requirements for SOP of this program. However, I am afraid I write this essay in such a large amount of words that the admission would get tired and bored.

Below is my essay.

Statement of Purpose

Inspired by my freshman study of user behavior in social media, I decided to study statistical methodologies for sophisticated data analysis in the future. Thus, I have taken multiple statistics and programming courses and conducted a variety of relevant research projects during my undergraduate studies, which have well prepared myself for the advanced studies in your program. Given my keen interest in Social Statistics and academic research, I am applying to the Master of Advanced Methods and Data Analysis at University of XXX. I believe your program would be a crucial stepping stone towards my future career as a research scientist in corporate innovation labs.

My aspiration to engage in statistical analysis is rooted in my freshman study on users' location sharing behavior on social media. In this study, I was interested in how social media have inspired people, especially those of my generation, to share moments of their daily lives and to reveal personal information to others. In particular, I focused on undergraduates' location-based information sharing behavior on WeChat, the most widely used social networking service in China. Sample data from the responses of 46 undergraduates in my university were collected through questionnaires. According to the bar charts produced by Excel, the dominating factors in users' self-disclosure behavior lied in their level of extroversion and desire for social connectedness among peers, which verified my initial assumptions. However, it was unexpectedly discovered that such behavior was also driven by people's longing for the optimized image in others' impression based on the results. It came to me that there may exist other ignored explanatory variables due to the unsystematic methodology for data analysis. Therefore, I have determined to master statistical methods systematically in my following undergraduate studies since then, and your program would largely deepen my knowledge in data analytics.

My undergraduate modules have allowed me to understand the fundamental statistical theories and to perform the analysis by relevant programming languages. To begin with, on the basis of linear algebra and multivariable calculus modules, a series of statistics courses have exposed me to a wide range of probability distributions and statistical theories, including those of hypothesis testing and linear regression. Particularly, the course of Linear Statistical Models has provided me of a deep understanding of how regression models extend from continuous variables to categorical ones and how Bayesian methods could be applied to analyze generalized linear models. The rigorous curriculum of your program allows me to acquire a holistic and comprehensive training of statistical analysis-to develop my skills in experimental design, to advance my ability to draw statistical inferences and to practically apply statistics to consulting activities. Furthermore, I have mastered a variety of statistical programming languages including R and Stata through multiple programming projects. Specifically, I am proficient in building, interpreting and visualizing regression models by practice. In order to comprehend the computational algorithms, I explored the numerical approximation methods in the course of Numerical Analysis. Your program would hone my expertise in statistical computing and develop my ability from technical and non-technical aspects through the Applied Statistics Capstone, which could substantially contribute to my future career as a research scientist in data science.

In addition to the methodological training in statistics, I am particularly interested in the possible specializations and interdisciplinary research projects provided by this full-time master program. First of all, it has long been an important one of my research interests to answer cardinal questions in social science by statistical methodologies, starting from my previous study of users' sharing behavior on social media. Accordingly, I intend to pursue the specialization in Social Statistics. Apart from this specialization, I am attracted by the abundant seminars and numerous cutting-edge research projects led by the Center for Statistics and the Social Sciences (CSSS). Among these social science researches, I am especially impressed by Prof. X's work in human mobility based on GPS data. It is of great interest for me to study cluster analysis and topological data analysis by measuring human activity spaces. Additionally, the flexible course-selection mechanism at the University of XXX makes it possible for me to pursue the Data Science Graduate Option offered by the eScience Institute. This option could further strengthen my foundation in data analysis from an integrated perspective of database systems and statistical learning. These sequences of courses and fascinating research opportunities would empower me to investigate my research interests in social statistics with the combination of my research skills acquired from previous research projects.

My previous research experience in machine learning and data pricing have laid solid foundations for further research at the graduate level. I carried out my first research project in machine learning under the guidance of Prof. X in our Department of Mathematics. By predicting infantile patients' hospitalization expenditures, I deeply understood the advantages and disadvantages of different multi-class classification algorithms. I next demystified convolutional neural networks by studying the semantic segmentation of overlapping human chromosome images. These research projects not only deepened my understanding of machine learning by programming in Python but also enhanced my capability of doing research collaboratively. Currently, I focus on my final year project to develop an effective pricing model for queries of private data, which derives from the question in my mathematical modeling competition. For this project, I have systematically learned relational databases and mastered SQL database skills. My model has been deeply influenced by the non-arbitrage pricing framework established by Prof. X in her project of XX. Therefore, I am immensely looking forward to joining her research team to develop my data pricing model further. To sum up, the diverse specializations and rich research opportunities convince me that your master program would be an excellent match for me and enable me to contribute to the discipline of data science.

With regard to my career plan, I intend to become a research scientist in the statistics research labs of technology companies. Earning the Master of Advanced Methods and Data Analysis would advance my career goal with thorough methodological training in data analytics as well as a wealth of opportunities provided by University of XXX. Your program would enable me to have close contact with the leading scholars in relevant disciplines and expose me to the most cutting-edge researches. During the program, I plan to conduct a graduate Research and Development (R&D) internship in my summer vacation to accumulate practical experience through end-to-end analysis. After graduation from my master program, I would pursue the joint Ph.D. degree in Statistics and Machine Learning in light of my dual concerns of statistical theories and machine learning algorithms. Of great interest to me are the topics of recommender systems and computational advertising. I expect to explore these areas during my Ph.D. program and to engage in the fields of advertising and media consumption analytics in the statistics research department of corporate innovation labs.

To summarize, I believe that my persistent passion for data analytics, my strong academic background in statistics and machine learning, and my research ability would enable me to succeed in graduate study and research of your program. Lastly, I am sure that the excellence of your program, along with my capabilities and motivation, would lead me to my destination-seizing the opportunities for human development through data analysis and realizing them eventually.

Graduate / Personal Statement for MS in Applied Data Science [3]

Hi there! Thanks for reading this thread, any of your advice or comments about my statement would be greatly appreated!

Viterbi School of Engineering application

Instructions
You are required to submit a Personal Statement for our program. The personal statement should describe succinctly your reasons for applying to the proposed program at the Viterbi School of Engineering, your preparation for this field of study, study interests, future career plans, other aspects of your background and interests which may aid the admissions committee in evaluating your aptitude and motivation for graduate study.

There is no required/recommended format or length for the personal statement.

My statement
This summer, after graduation from my undergraduate program, I joined an environmental nonprofit organization dedicated to water source protection as a data analysis intern. During my internship, I performed a time series analysis of water quality data for Lake Taihu, the third-largest freshwater lake in China and, most relevant on a personal level, the lake of my hometown, Suzhou. For generations, my ancestors have lived on the shores of Lake Taihu and regarded it as our primary water source and economic lifeblood. I have always been proud to enjoy such a huge, sparkling gem of nature in my hometown. It never occurred to me that the lake might suffer from the deterioration of the aquatic ecosystem, let alone a shortage of drinking water sources.

However, my analysis of the historical water quality data in Lake Taihu unmasked what had been a blissful illusion and disclosed to me a foul and morbidly verdant lake that has been plagued with severe water eutrophication for decades. The accumulation of excessive nutrients released from non-point pollution sources induced the overgrowth of phytoplankton and frequently triggered large-scale outbreaks of cyanobacteria blooms. My time series forecasting revealed that not only was the lake pollution in the past and present alarming, but its water quality is not promising in the foreseeable future. More significantly, the ecological degradation of Lake Taihu will threaten the drinking water safety in the catchment area, affecting not only Suzhou but also the whole Yangtze River Delta. Unexpectedly, the analysis of water quality data in a lake can disclose such a shocking drinking water crisis in East China, where China's economic and political heavyweights locate.

This experience in data analysis has shown me the enormous potential of data science and how it empowers us to uncover the hidden past and predict unknown futures. I look forward to further studying the application of data science during my master's study. My undergraduate training has provided me with a solid theoretical foundation in probability, statistics, and a broad range of mathematical skills such as linear algebra. I broadened my understanding of computer vision and honed my programming skills in Python and Java by multiple applications of deep learning in medical image processing. Currently, I am working on a research project that uses GAN-based medical image augmentation to boost the performance of CNNs in the classification of interstitial lung disease on HRCT images. The rigorous curriculum of MS in Applied Data Science would transform me into a more professional data scientist, educating me in the holistic pipeline of data analytics, introducing me to the state-of-the-art machine learning techniques, and immersing me in real customer data analytic challenges through the professional practicum. However, more importantly, your flexible elective track would allow me to ponder over the security and privacy of big data applications, where my particular study interest lies. My previous research in the economics of privacy made it clear to me that the subject of private data analysis is my passion, which has driven me to this USC Viterbi's program.

Technology that relies on big data analytics has permeated our daily lives, and personal data is the oil that fuels a multitude of mobile applications. There is growing concern over potential erosions of privacy in that personal data is being recorded, gathered, and tracked beyond individuals' control. Though governments have enacted privacy legislation to regulate the collection and processing of user data by technology companies, such strategies limit the productivity that data-driven technology may boost, and the demand gap for personal datasets remains. Instead of restricting the access to datasets, why not create a fair and unified data marketplace where the demand for data can be satisfied with fair compensations for individuals' information disclosure? This idea struck me when I was addressing Problem F, Cost of Privacy, in the 2018 Interdisciplinary Contest in Modeling during my junior winter vacation. In designing the pricing function of queries, we were inspired to add random noise to the true query results and charge data buyers for the degree of perturbation they can tolerate. It was based on this assumption that we finally established our query-based pricing model of private data in the contest.

Nevertheless, I did not regard this result as the ending of my engagement with data commercialization but decided to make it concrete. I aimed to determine an arbitrage-free pricing model of data commodities with which individuals are able to control their private data through financial means. With this approach, capital can flow from data consumers to data owners freely, similar to what prevails in the derivatives market. I chose this research topic as my final year project. It took me on a journey to realize that the core of quantifying the economic value of data is the trade-off between privacy and utility. In this context, I was naturally drawn to differential privacy, a theory founded on noise generation, which parallels my idea of noise addition in the contest. The more I immersed myself in the discussion of differential privacy, the more I find the elegant balance between the privacy and accuracy of statistical analysis it achieves as well as the field of data privacy fascinating. I look forward to continuing my study of this field in depth under the guidance of Prof. X and Prof. Y in the USC CS Theory Group. I am deeply attracted by Prof. X's innovative work in privacy-preserving algorithms and Prof. Y's contemplation in the interface between algorithmic game theory and mechanism design. The opportunity offered by this master's program would allow me to further my thinking both in the auction design of information markets and in the broader privacy-preserving data analysis. Therefore, I believe that the Viterbi School of Engineering is the ideal place to develop my academic interests.

My internship at the nonprofit organization has shown me the impact of public welfare initiatives on society and the urgency of their decision-making transformation with data-driven analytics in the digital era. For one thing, I hope to become a data science practitioner who brings value to the industries where advanced data analytics capabilities are in demand. For another, I aspire to be a guardian in the data-driven world, safeguarding data privacy but also promoting the circulation of data and the development of data-centric innovation. With the prospect of creating a trustworthy digital society, I am convinced that the best opportunity for me to follow my chosen path is to pursue my graduate education in Applied Data Science at the USC Viterbi School of Engineering.