This page is perpetually under construction.  I use this to gather an incomplete list of resources that have been formative in my mathematical journey. 

Nuts and Bolts - Typesetting and foundations 

• Learn to type mathematics!  Overleaf (in browser) good for beginners, getting feet wet, and collaborating.  Eventually work up to a dedicated TeX editor (many options): TeXStudio, Kile, TeXMaker, LaTeX plug-in for VSCode (what I currently use most regularly).  

• I hear that the Khan Academy has a number of very good (free) math tutorials especially the Calc 1 and Calc 2 sections.

• 3Brown1Blue Essence of Calculus Series -  presents concepts from Calculus in a very visual way

Appreciating math:

• Eddie Woo (TED talk) Mathematics in a sense you never knew you had

• Numberphile 

• Veritasium

Research math culture:

• Undecidable problems (Bjorn Poonen) : Brief and deep survey across several areas of math

Web comics (academic "pop" culture):

• Math with bad drawings is an easy to read math blog by a teacher in the UK with topics ranging from arithmetic all the way to graduate level stuff.

• Spiked math is a fun math themed web comic. 

• PhD Comics one portrayal of the sometimes hilarious and confusing moments in graduate school.

• xkcd, SMBC, and Abtruse goose are nerdy webcomics some of my friends follow.

Pursuing a career in academia:
As of 2026, the pipeline to obtaining a position in academia is a deeply sloped pyramid... that is to say that numerically the prospects of obtaining an academic position is bleak.  A perpetual anecdote throughout my interactions with senior mathematicians is that "it was easier back in my day."  Appreciation of any field can be deepened when viewed from an external lens.  Intimate understanding of alternate career pathways will deepen appreciation for any field by providing a perspective from an external lens.

Much of the process of pursuing a career in academia is not formally stated.  There is a high variability in what different institutions are looking for.  In short there is no silver bullet.  Here are some resources that I've found that might be helpful for navigating those uncertain moments:

• Advice by Kimball Martin on pursuing academic jobs (good resource for PhD students to glance at early on to get a sense for what people are looking for)

• An article by Dick Canary on applying to Research Postdocs

• Resources collected by Dan Margalit 

Artificial Intelligence usage in Mathematics/Academia:

I endeavor to understand the impact of Artificial Intelligence (AI) on mathematics and ramifications thereof.  This has been particularly influential in how I view the evolving role of education.  In an effort to have more conversations I am recording here resources that I have found particularly notable in developing my own understanding.   

A panel discussion on using AI in mathematics (Takeaway: Prompt-engineering and "high-level" AI usage) 

An interview with Ken Ono.  (Takeaway: the importance of reasoning and how math education may help) 

Presentation at ICM2026 by Terrance Tao (Takeaway: analogy using generative AI is like overeating for the first time)

Video podcast with Andrew Ng (Takeaway: Warning on using generative AI for learning purposes)

Other related references: "Empire of AI" by Karen Hao