Year-end reflection: My 2020 highlights

The last day of 2020 is finally here. To bring this decade to a close, I thought I would take a moment to share some of the highlights from this year in the form of pictures and anecdotes. As much as I would love to remember this year as a year of setbacks and bottlenecks, in retrospect, it has been packed with some very surprising yet noteworthy moments. On a personal level, 2020 has been a year of many firsts, much as has been the case for the society in general where we have together achieved incredible things as a community despite challenging circumstances.

A paper that changed my life - The Bayesian LASSO

As tough as this year has been, it goes without saying that 2020 is a particularly good year to be thankful for science, which happens to be one of the many things that are often taken for granted. While similar thankfulness posts have appeared elsewhere, I want to share a different take as a computational scientist. As the title suggests, I am shamelessly borrowing idea from the so-called most influential series that are widespread in the popular culture.

Student paper awards and travel grants - A resource for data science graduate students and postdocs

This post is motivated by the growing list of awesome public repositories that curate a list of resources dedicated to a specific topic (such as this, this, and this, among others). As a graduate student, I often struggled to find such a centralized resource, especially when it comes to student paper awards and travel grants, geared towards data science graduate students and postdocs (broadly defined). On the surface, these awards help you save a few hundred dollars of registration and other out-of-pocket travel expenses but they are also worth the effort to go the extra mile in getting a nice gold star for a CV.

Early-career setback - A throwback to my first paper

This 15th August marked 7 years since I submitted my first paper (first-authored research article). Coincidentally, it also completed five calendar years last December, which gave me a chance to measure it’s 5-year impact (erring on the conservative side of course). I am very happy to see that it has been well-received as shown in the figure above (the R code to generate the plot is publicly available). To interpret it more accurately in plain English, it has performed significantly better than an average paper in the same journal or same discipline (Statistics).