Personal Statement for University of Wisconsin Biomedical Data Science

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  • nerrix
    University: University of Wisconsin - Madison
    Nationality: United States
    November 11, 2019 at 1:55 am

    Personal Statement for University of Wisconsin Biomedical Data Science

    My primary research interest is in statistical genomics, and my goal is to work in academia as a noted biostatistician who can efficiently solve questions arisen from the field of genomics. I am currently studying statistics at the University of Wisconsin – Madison, and I involved in a research project developing a statistical model to gain an in-depth understanding of bulk cell RNA sequencing data. What’s more, I worked on several newly-generated data and obtained some impressive results from them. All those projects have opened my eyes to a broad range of research in not only statistical genomics but also many statistical problems that I didn’t realize. They motivated me to undertake further study through a Ph.D. program.

    Under the supervision of Professor Sunduz Keles, I conducted research that tries to estimate the cell proportion functions in bulk RNA sequencing data using single-cell RNA sequencing data, functional data analysis, and non-negative least squares. In detail, I developed a regression model with positivity constraints on the cell proportion functions for different cell types along the inherent trajectory. The result outperformed most methods and brought about some brand new information, and this method will be submitted to Genome Biology. Also, along with Dr. Daniel Conn, we worked on several single-cell data from Dr. Emery Bresnick’s lab to gain insight into the hematopoiesis system.

    From those experiences, the most direct enhancement among my skills was my coding. Statistical genomics required a tremendous amount of coding, and I have not only become a faster coder, but I was also familiar with all the packages and methods commonly used in single-cell sequencing analysis. What’s more, the experience of talking to biologists was very precious and essential, and I think it is unique among most applicants. From this, I got to understand some of their real demands. For example, the very basic question they would ask was between two conditions (Wild type and Mutanted), which genes downregulated or upregulated. There are some tricky questions like the change of regulation of genes on the GATA2 binding factor between two conditions. I got to have a more precise understanding of what biological questions we were caring about and understood more on statistical genomics not only on a statistical level but also on biological. I think the most important thing I learned from this was seeing how sedulous everybody made working on projects. To push forward projects requires effort, but what I saw was that whether professors or Ph.D. students, simultaneously worked on five or six projects. They could still do well in all of them and had a beautiful personal life apart from academical life. The best example is that some of the Ph.D. and Post Doc students were getting married, but they could work on research and plan the wedding at the same time. They epitomized scientists and working with them enabled me to have a better sense of time management, teamwork, and executive ability.

    I also took courses that are suitable for this field to prepare for being a noted biostatistician fully. My score is monotone increasing every semester, and it is still enhancing even when I was in UW – Madison. I took statistical methods for clinical trials (STAT 641), which required us to cooperate with students in medical school, and I am aware that biostatisticians need to discuss with biologists to understand those questions so that we can design experiments to solve the questions more efficiently. I took statistical computing (STAT 771) since in statistical genomics, we always face a vast amount of data with sparse entries. Even in solving linear systems, using the inverse of a matrix is not a wise decision. In this course, I also got to know some theoretical properties of dimensionality reduction, which is essential in the context of single-cell RNA sequencing analysis, and as I wrote, solving linear systems or least square problems helped me in my research as well. When it comes to working in academia, speeches are necessary, so data science practice (STAT 628) is beneficial concerning that. Of course, all other classes helped enter a Ph.D. program, like causal inference, and all the traditional statistical courses I took. These are also courses we can choose in the topics in this BMDS program, so I was fully prepared.

    Except for those academical achievements, living in Madison in almost two years, I am quite adept at life here. Many people are sad about the six-month heavy snow, but I enjoy it since the color, and the breezing breath made my thought clear. Also, though I am not a crazy football fan, when this season begins, I am excited to see a massive amount of people cheering upon Wisconsin Badger. More importantly, the academical environment is perfect here. Working with Professor Sunduz Keles aroused my interest in statistical genomics, and it was also inspiring working in her research group with her Ph.D. students. I regard UW – Madison as my academic ‘home’; I benefited enormously from the vast breadth of experience and areas of expertise of a prestigious faculty and the consistently challenging but supportive atmosphere in the department. I aim to further the department’s and the university’s reputation for academic excellence. I am aware that the doctorate program will attract other very well qualified applicants. Still, I genuinely believe that I can add significant value based upon a very successful academic career, research experience, extensive work experience, intellectual curiosity, and, perhaps most importantly, a genuine passion for this field of study and its development. I can assure the reader of highly enthusiastic, committed, and diligent participation in the program if selected.


    November 16, 2019 at 9:08 pm

    Score: 38.2


    1. More than half of the sentences exceed 20 words. Very difficult to read.
    2. Paragraphs are lengthy and wordy. Three paragraphs exceed 150 words (80-100 is appropriate);
    3. The length of this essay (920 words) is wordy. Shorten it to 500-600 words;
    4. More than 3 consecutive sentences start with the same word;
    5. Numerous grammatical/syntactic/logical/factual errors.