Hello, I'm Justin Hong.
I am a second year Ph.D. student at Columbia University in the Computer Science Department. I am excited to be working with the Azizi Lab. I am interested in developing scalable and easily interpretable computational methods for unraveling the complexities of biological data.
Previously, I was a research engineer at the Yosef Lab at UC Berkeley, where I contributed to open source package scvi-tools for the deep-probabilistic modeling of single-cell omics data.
I attended UC Berkeley for both undergraduate and graduate (M.S.) studies in Computer Science & Molecular and Cellular Biology. I was fortunate to have been advised by Professor Yun Song and Professor Kannan Ramchandran for my Master's program, during which I developed a method for deconvolving bulk RNA-seq data using a single-cell RNA-seq reference dataset.
Previously, I worked as a software engineer at Nuro working on developing evaluation and introspection tools for our autonomy stack. This involved filtering through massive amounts of data to understand where the bot underperformed and tracking the performance of future software iterations on relevant scenarios.
Feel free to contact me at firstname dot lastname at columbia dot edu.