The decision to have a separate High School Project Track at NeurIPS 2024 has sparked quite some controversy, with many prominent AI researchers debating pros and cons and personal opinions, primarily on X/Twitter. Initially, I ignored this discussion, but eventually started thinking about it myself. Here are some of my thoughts.
A recent conversation with Jay Shah on his podcast made me think more about career choices and the question of “academia vs. industry” after completing a PhD. Since finishing my PhD, I also had this conversation with many other researchers — and before finishing my PhD I asked recent graduates about this myself. So, in this article, I want to share some of my thoughts.
While attending the Heidelberg Laureate Forum this year, I got to meet Letitia Parcalabescu who is running a YouTube channel called the AI Coffee Break. Among other topics, we talked abou my PhD research on adversarial robustness. Part of our conversasion can now be found on her YouTube channel.
This September, I had the chance to attend the Heidelberg Laureate Forum (HLF) for the second — and probably last — time. The HLF is an incredible experince for young researchers: Mirroring the Lindau Nobel Laureate Meetings, the organizers invite laureates from math and computer science together with young researchers pursuing their undergraduate, graduate or post-doc studies. In this article, I want to share impressions and encourage students to apply next year!
In September, I received the DAGM MVTec dissertation award 2023 for my PhD thesis. DAGM is the German association for pattern recognition and organizes the German Conference on Pattern Recognition (GCPR) which is Germany’s prime conference for computer vision and related research areas. I feel particularly honored by this award since my academic career started with my first paper published as part of the young researcher forum at GCPR 2015 in Aachen.
Recently, I had the opportunity to be a guest on Jay Shah’s podcast where he regularly talks to machine learning professionals from industry and academia. We had a great conversation about my PhD research and topics surrounding a successful career in machine learning — finding a good PhD program and research topic, preparing for interviews in industry, etc.
Report of the 2020 Max Planck PhDNet survey results.
Generally, papers are written to be published at conferences or journals. While some journals care about the LaTeX source used to compile the submitted papers, most venues just expect compiled PDFs to be submitted. However, ArXiv always requires the full LaTeX source to be compiled on the ArXiv servers. As the LaTeX source of every ArXiv paper can be downloaded, this usually involves removing all comments, unused figures/files and “flattening” the directoy structure as ArXiv does not handle subdirectories well. In this article, I want to share two simple scripts that take care of the latter two problems: removing unused files and flattening.
Conducting PhD research can be a long endeavor, involving much more than the publications listed on Google Scholar. As I recently submitted my thesis, in this article, I look back on my time as PhD researcher in terms of numbers. This way, I hope to shed some light on what a PhD can look like in terms of everyday work.
In 2018, I was half a year into my PhD and wrote an article about choosing the right PhD program, which I personally found to be incredibly difficult even though I only had few options to decide between. This article is an updated version, preserving most of my original opinions and advice and adding some perspectives having finished my PhD in the meantime.