Bodhi Beroukhim is a student at Phillips Academy Andover in the United States. He has gained research experience in genomics and spectroscopy through laboratory work at leading medical and research institutions. By applying statistics and programming, he contributes to projects that use data analysis to support scientific investigation.
Genomics Research at Dana-Farber Cancer Institute
Bodhi interned at a genomics laboratory at Dana-Farber Cancer Institute. There, he worked on developing a classifier to distinguish between somatic and germline mutations.
Using his knowledge of statistics and R programming, Bodhi analysed datasets and identified relevant trends. He also collaborated with graduate students and laboratory directors throughout the project.
As part of this experience, he presented his findings to more than 40 researchers across two laboratories. This opportunity allowed him to communicate his analytical work and engage with professionals in genomics research.
Developing Automated Data Analysis Methods
Bodhi is also working at a spectroscopy laboratory at Harvard Medical School and Brigham and Women’s Hospital. He is leading a project to develop an automated method for data analysis.
Working alongside a statistician and other researchers, he applies statistical techniques and programming skills to the project. In addition, he has taken the initiative to plan project steps and coordinate with professionals involved in the research.
This experience allows Bodhi to contribute to the development of more automated approaches to analysing spectroscopy data. It also strengthens his ability to manage research tasks and collaborate within a scientific team.
Applying Statistics and Programming to Scientific Research
Across both laboratory experiences, Bodhi has applied computational and analytical skills to scientific challenges. His genomics work involved distinguishing mutation types through statistical analysis. Meanwhile, his spectroscopy project focuses on developing automated data analysis methods.
Furthermore, his collaboration with graduate students, statisticians, laboratory directors, and researchers has given him experience working in professional research environments. These opportunities demonstrate how programming and statistics can support investigations across different areas of science.
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