Hello, and welcome to my blog! I am currently a Ph.D. student in the NIH-Penn Immunology Graduate Partnership Program, and I am interested in the early development of autoimmune diseases.

I had a non-traditional path for reaching where I am today. I joined my first research lab in May 2013, working under the tutelage of Fernando Martinez, a Ph.D. student at the time. While I was there, I worked on ALS and CRISPR/Cas9, and in doing so, gained competency in wet lab skills, such as cloning, tissue culture, qPCR, and assay development. From 2017 to 2019, I worked at True North Therapeutics, where I studied diseases of the complement immune system, many of which were autoimmune diseases. For example, our lead antibody drug, sutimlimab (TNT009), was granted FDA approval on February 4, 2022 for the treatment of cold agglutinin disease (CAD), an autoimmune disease in which patients have complement-activating IgM autoantibodies to their own red blood cells, which causes anemia and drastically lowers patients’ quality of life. It was because of my work here that I first became interested in autoimmune diseases. I also began dabbling in Python programming.

In 2019, I enrolled in Metis, a 12-week data science bootcamp focused on machine learning and data analysis and visualization, with the goal of transitioning to a dry lab role. I achieved that milestone when in January 2020, I became a Data Scientist at Invitae, a clinical genomics company. I handled ad-hoc root cause analyses of customer issues arising from our next-generation sequencing (NGS) assays, and I built dashboards using Tableau to monitor new assays. In 2021, I joined Thermo-Fisher as an R&D Data Scientist, where my main project was the epidemiological surveillance of COVID-19 variants using customer datasets from our TaqPath COVID-19 combo kit. Because I joined close to the founding of our team, I had the opportunity to lay the foundation for our pipeline: using Python and SQL, I engineered a scalable, extract-transform-load (ETL) pipeline in a AWS to extract information from customer files and load transformed, tabular data into an Amazon Athena database for consumption by our Power BI dashboard. I also handled ad-hoc analyses, such as analyzing the outcomes of sample repeats.

This blog features the portfolio I created during my education at Metis, any software-related topics I learned during my journey, and any technical topics I find interesting. For a detailed summary of my experiences, please see my extended-resume.

If you would like to chat about anything science or data science related, please feel free to email me at harrison.c.wang@gmail.com.

Happy reading!