🙌🏽 Lead @geodatascience.bsky.social & @qmrg-rgs-ibg.bsky.social
✍️ Editor @region.bsky.social
💻 Project: https://de-bias.github.io/debias/t
🔗 www.franciscorowe.com
Delivered seminars at UQ and Griffith University—fantastic discussions on mobility, data science & climate change.
More on DEBIAS 👉 de-bias.github.io/debias/
Delivered seminars at UQ and Griffith University—fantastic discussions on mobility, data science & climate change.
More on DEBIAS 👉 de-bias.github.io/debias/
Join our exciting project with @Ofsted at the @geodatascience on early childhood education & labour force participation.
Work with novel geospatial data & methods with real-world impact.
🗓️ Deadline: 1 June 2025
📥 Apply: lnkd.in/egTWyUT8
Join our exciting project with @Ofsted at the @geodatascience on early childhood education & labour force participation.
Work with novel geospatial data & methods with real-world impact.
🗓️ Deadline: 1 June 2025
📥 Apply: lnkd.in/egTWyUT8
Diving into how digital traces, registers, censuses & surveys can help us better understand human mobility. Looking forward to great discussions & collaborations!
Diving into how digital traces, registers, censuses & surveys can help us better understand human mobility. Looking forward to great discussions & collaborations!
🗓️ Deadline: 7th March, 2025
📥 Applications: lnkd.in/eZcN5YfU
🗓️ Deadline: 7th March, 2025
📥 Applications: lnkd.in/eZcN5YfU
1️⃣ What drives spatial & temporal variability?
2️⃣ Are there tipping points where behavior shifts? 🔎
1️⃣ What drives spatial & temporal variability?
2️⃣ Are there tipping points where behavior shifts? 🔎
1/ 🚍 We look at how predictable bus rides are, exploring the spatial & temporal variability of bus use in Beijing using smart card data & explainable machine learning. 🧵👇 #Transit #UrbanMobility
🔓https://doi.org/10.1016/j.jtrangeo.2025.104126
1/ 🚍 We look at how predictable bus rides are, exploring the spatial & temporal variability of bus use in Beijing using smart card data & explainable machine learning. 🧵👇 #Transit #UrbanMobility
🔓https://doi.org/10.1016/j.jtrangeo.2025.104126
In this first stage we are focusing on measuring and identifying key predictors of biases in human mobility data extracted from mobile phone apps.
An unexpected finding 👇
In this first stage we are focusing on measuring and identifying key predictors of biases in human mobility data extracted from mobile phone apps.
An unexpected finding 👇