Here's an episode all about data—mobile phone data, to be exact. What are we talking about when we talk about using “mobile phone data” in our research? How are these data generated? Who produces them? What is this data good for…and maybe not so good for? How is it accessed and used? So many questions! To help provide some answers, in this episode Rachel, Levi, and Dani are joined by special guest, Wenfei Xu, Assistant Professor in the Department of Geography at UC Santa Barbara.

AI is now definitely changing how we live our (geography) lives. Join Rachel, Dani, and Levi for a chat about how Artificial Intelligence is emerging in our GLAD lives. How is it being used "in the wilds" of teaching, research, coding, publishing, and beyond. Should you be farming out your peer reviews to a computer? Vibe coding with your friend Claude? Setting out on AI-generated running routes? And, as always, do we really need more papers faster than ever before? We chat through this, with some advice and reflections on where AI might change our own practice and how it's certainly changing the way academia (writ large) works.

Let us know what you think at thegladpodcast@gmail.com. Did we miss something about AI that you now can't live without? Have we missed your favorite anecdote about a deluge of digital dreck? Send us an email!

Resources we discussed:

Nature's recent editorial on peer review and AI https://www.nature.com/articles/d41586-025-00894-7

Harper Reed's post on how to code well with LLMs https://harper.blog/2025/04/17/an-llm-codegen-heros-journey/

Ethan Mollick's "reasoned optimism" about thinking with AI https://www.oneusefulthing.org/

Simon Willison's blog tracking the frontier of LLMs https://simonwillison.org

Join us for the second part of our conversation about the academic job market! This half, we'll talk a bit about the nuts and bolts of putting together your application and the process from applying to interviewing for (and maybe even getting) the job! Caveat: we're mostly familiar with the US and UK academic job markets and we stick to what we know best in this episode!

Let us know what you think by sending us an email at thegladpodcast@gmail.com or leaving us a review on whatever podcasting app you use! it really helps us out.

Everything you (n)ever wanted to know about getting an academic job in geography or geography-adjacent fields. In this episode your friendly—and pretty experienced at applying for academic jobs—co-hosts talk through the academic job market. Where to look for jobs, timing, what to expect, and how to apply. Caveat: we're mostly familiar with the US and UK academic job markets and we stick to what we know best in this episode!

Today, we’re talking about time management. Or, rather, the lack thereof (both time, and management). It feels like we’re always over-committed. Always running behind. 24h a day sounds like so much and feels like so little. Why? Fasten your seatbelts, let’s find out!

In this episode we talk to Geoff Boeing, streets and urban form expert, mastermind behind OSMnx, and urban planner at USC. We talk (a lot) about disasters and cities, street networks, and open source software. Several callbacks to previous episodes, including our Vibe Check on Cities and Computing Geographically with David O'Sullivan episodes. Also Davis and Weinstein (2002), "Bones, Bombs, and Break Points: The Geography of Economic Activity" and the New York Times on trash, streets, and urban form.

This week, join us for our own retrospective on the year, and a look forward to next. We'll talk a bit about all the data in a year of GLaD, the highs and lows of Work/Life Balance in a year of "too much yes", the NYT Spelling Bee, and all the new and awesome Geography and Data that came with the year.

As always, let us know how your year in GLaD went by emailing us at thegladpodcast@gmail.com

Until next year!

Today, we’re talking about what some would characterize the “topic” of the XXIst Century (others might perhaps not!): Digital Twins. Are we excited about them? Are our eyes so rolled that they’ll never recover? Or is this excited Vs eyeroll dichotomy not very helpful at all? Above all, what even are Digital Twins?

- Here is the Commentary Rachel mentions (free access):

Malleson, N., Franklin, R., Arribas-Bel, D., Cheng, T., & Birkin, M. (2024). Digital twins on trial: Can they actually solve wicked societal problems and change the world for better? Environment and Planning B: Urban Analytics and City Science, 51(6), 1181-1186. https://doi.org/10.1177/23998083241262893

- The DT project for a bridge in Amsterdam, by The Alan Turing Institute: https://www.turing.ac.uk/about-us/impact/bridging-gap-between-physical-and-digital

- AI for continuous environmental project mentioned by Levi: https://waterinnovation.challenges.org/winners/ai-algal-monitoring/

- Larger scale aquatic “digital twin” project at Turing, mentioned by Levi: https://www.turing.ac.uk/research/research-projects/probabilistic-programming-aquatic-ecosystem-models