This post introduces recommended resources that are useful for research, aimed at machine learning researchers. If you know of other resources worth recommending, please let me know.
How to Do Research
- A Survival Guide to a PhD
- Andrej Karpathy’s guide to getting through a PhD. Its advice is useful not only for PhD students but for research in general.
Writing Papers
- How to ML Paper
- Covers the overall structure of a paper and key points for writing each section.
Rebuttals
- How to ML Rebuttal
- Covers the right mindset for rebuttals and how to write them.
Research Presentations
- 伝わるデザイン (“Design That Communicates”, in Japanese)
- Covers key points for making slides and posters easier to read.
- ノンデザイナーズ・デザインブック (Japanese edition of Robin Williams’s The Non-Designer’s Design Book)
- A book covering design basics for people who are not designers. It introduces four design principles (proximity, alignment, repetition, and contrast), and simply keeping them in mind greatly improves how your slides and posters look. It also helps with designing figures for papers.
- スティーブ・ジョブズ 驚異のプレゼン (Japanese edition of Carmine Gallo’s The Presentation Secrets of Steve Jobs)
- Summarizes the key points of presentations by Steve Jobs, a presentation genius. Its advice is useful not only for research talks but for presentations in general.
Grant Applications
- 学振特別研究員になるために～2026年度申請版 (“Becoming a JSPS Research Fellow: 2026 Application Edition”, slides in Japanese)
- Explains how to write applications for research funding, starting with the JSPS Research Fellowship (Gakushin).