Nishanth J. Kumar's personal website. Based on [*folio](https://github.com/bogoli/-folio) design.
After having decided to wrap up my PhD and graduate, I recently found myself having to go through the actual industry job search process. Fortunately for me, a number of other people have written useful guides and advice on how to effectively search for a research-adjacent job in AI (see this, this, this, and this). However, my experience looking for jobs in robotics ended up being different…
One of the questions I’ve gotten most frequently over the years is some version of “should I do an AI PhD?” I’ve answered this enough times now — and gotten to see how many of these decisions played out — that I figured it might be useful to just write my thoughts down. I’m also about to finish my own PhD, so it seems like a natural time to reflect on the decision.
This year’s CoRL was the biggest CoRL yet, with over 900 attendees, 11 workshops, and almost 200 accepted papers. While there were a lot of cool new ideas (see this great set of notes for an overview of technical content), one particular debate seemed to be front-and-center: “is training a large neural network on a very large dataset a feasible way to solve robotics?”.
A while ago, I had the opportunity to develop and release a new open-source Python library: PGMax. Since this was to be my first open-source library release, I spent a lot of time figuring out a good set of developer tools to speed up development and enable (hopefully) lots of people to use and contribute to the project in the future. While there are already so many different articles, blog posts…
Writing a good PhD SoP can be a daunting task. Fortunately, there are plenty of good posts out there about how to approach the writing process and what a good SoP looks like (in particular, I followed the structure laid out by this post by Tim Dettmers and this post by my undergrad advisor Stefanie Tellex). When I was writing my own SoP, what I probably found most-helpful on top of the…
Computer Science has become quite the popular field these days, especially amongst undergraduates. As a result, there are a lot more CS-related resources now than there ever were before. There are tons of books, lecture videos, guides, articles, and even memes about everything from understanding difficult CS concepts for coursework, to ‘cracking’ technical interviews, to applying to CS grad…
I recently spent on the order of 2 hours debugging some code that it only took me 1 hour to write. This post is partially intended to be informational for a reader and partially intended to serve as a future warning/reminder for me.
Recently, I was incredibly excited and humbled to learn that I was selected as a 2021 NSF GRFP Fellow. Like most of my accomplishments, this one was only made possible by the support of friends and colleagues, and the mentorship of my incredible advisors at Brown. One resource I found particularly helpful for this application was previous successful applications, specifically Victoria Dean’s and…
One of my favorite blogs in the whole wide Internet is the MIT Admissions Blog. Admittedly, this used to be because I wanted nothing more than to become an MIT undergrad. However, I’ve continued to keep up with these blogs even after being rejected from MIT because many of the posts have been exceptionally genuine, relatable, and even insightful. In fact, I actually kept a copy of one of my…
Earlier this year, I had the incredible privilege of being named a Goldwater Scholar. While winning the scholarship was rather validating and motivating, I thought the application process worthwhile in of itself because it forced me to think hard about my research direction and career goals for the future. During the application process, I found it incredibly helpful to read past sample…