Miscellaneous

This is just a page where I’ll put some online resources that I believe are of use to potential, current or former students or anyone else who stumbles upon my website. These resources primarily target academia, but is not strictly speaking restricted to this domain. However, one thing is certain: If its on this page, I found it useful.

• Effective Communication of Scientific Results by Prof. Amaral (UAlberta CS). This is a fantastic resource to anyone who needs to craft and give a presentation about their work, whether that be a student presenting their paper in an oral session of a conference (e.g., AAAI, NeurIPS, CIKM, SDM, etc.), a postdoc trying to secure a faculty position or an invited distinguished professor visiting another university institution to give a talk. It explains why it is better to have less text than more in a slide. Why, counter-intuitively, it is better to use Microsoft Excel (or equivalent) to present tabular results in a paper instead of screenshotting a LaTeX table. Finally, it also explains why it is much harder to prepare a 5-minute presentation than a 15-minute presentation. These insights stem from time when Prof. Amaral attended a lecture by Preston Manning, a former politician from Alberta and Leader of the Opposition (‘97-‘20).
• How to Read a Paper Prof. Keshav (UWaterloo CS). This is another awesome resource, especially for young academics who may have little to no idea of what the hell they’re supposed to do when their PI gives them a reading list. As science advances, academic papers have become more complex and their methods increasingly difficult to comprehend. While understanding may prove a daunting task, Professor Keshav’s “Three-Pass Approach” aids greatly in this understanding.
• Make it stick: The science of successful learning by Brown, Roediger III and McDaniel and Algorithms to live by: The computer science ofhuman decisions by Christian and Griffiths. Both of these are excellent resources for learning what to bring into the classroom, and for also helping to understand how a computer scientist can cast certain CS algorithms as helping to predict human behaviour, e.g., greedy search/selection is very much a natural tendency.
• Thesis Preparation Checklist by Yours Truly. Okay, this one is likely a case of just “tooting my own horn” so to speak. I spent a lot of time making my PhD thesis look nice. Probably more time than I’d like to admit. However, rather than keep those guidelines to myself, I’ve decided to put them out into the open, right here!