Biography

I am a first-generation Salvadoran American student at Lewis & Clark College. I have always been fascinated with the units that structure our life. Every cell must be in tune to carry out the functions of an organism. It seems magical, yet years of evolution have come to play a part in this perfect, structural sequence. The study of these inter and intracellular relationships reveals that the interconnectedness of our world comes from our very framework, from the building blocks that compose us.

Academic Status

Undergraduate Student - 3rd

Research Area/Department

Biology; Chemistry; Data Science

Major/Specialty

Biochemistry/Molecular Biology, Data Science

Degrees Earned or in Progress

Bachelor of Arts/ Biochemistry and Molecular Biology and Data Science/ 2027

Academic Preparation

In my time at Lewis and Clark College, I have accrued a foundation in the hard sciences; I have taken 200 and 300-level courses in biology, chemistry, and data science. These courses supported me in building a technical understanding of how the flow of information, transformations of energy, and structures and functions of metabolic processes sustain life. I use data science to apply these principles and evaluate the significance of these “big pictures.” Throughout my time at Lewis and Clark College, I have developed problem solving skills. I took an applied data science course in collaboration with the United States Fish and Wildlife Services to create current species occurrence maps and predicted their distribution in 50 years based on carbon dioxide emissions. This past summer, I was an intern for the Multnomah County Health Department, where I organized county data and created accessible infographics/data visualizations on various chronic diseases. I am currently an assistant to the head of Data Initiatives at Lewis and Clark’s Watzek Library, where I have created an interactive website on creating data visualizations in R.

Research/Academic Interests

Science is a tool we develop out of necessity and we use data science to make sense of what those tools tell us about life around us. Graphs and statistics are used to draw meaning from niche fields of research. They optimize the way we make informed decisions from science. Data science compiles and sorts individual facts to extract information from them. It bridges the connection between researchers and the community by making science accessible. I am interested in exploring the intersection of molecular biology and programming. I have experience with both, however, in a mutually exclusive way. I hope to explore their overlap on how to use data science as a tool to inform molecular biology procedures and outcomes. While I have most experience in R, I am eager to learn new coding languages.

Computational and Data Science Areas

Biochemistry and Molecular Biology; Cell Biology; Informatics, Analytics and Information Science

Motivation

During my first year, I attended a conference for SACNAS: the Society for the Advancement of Chicanos/Hispanics and Native Americans in Science. I learned how to use science as a tool to support others. One of the conference panelists closed her speech saying, “being connected with your heart doesn’t make you a worse scientist.” I learned that I do not have to separate my identity and experiences from my career. As a student in Sustainable Research Pathways program, my goal is to help create a bridge between my community and research. This internship opportunity will help me learn how to communicate as a researcher by exploring data in collaboration with skilled researchers. I will enrich my intuition and troubleshooting skills as a scientist. I would be honored to use my passion for life sciences and data literacy to become a more engaged scientist. I look forward to applying my background as a molecular biologist, data scientist, and a researcher of color to extract insight from mentors during this internship experience.

Lightning Talk Title

Interconnection of life through molecular biology & data science

Keywords (Maximum 20 words)

Molecular biology; data science; bioinformatics