Part 1 covers the 2nd Programming for the Planet conference (@propl.dev) organised by @kcsrk.info @dorchard.bsky.social and me. There were talks, demos and discussions about what we can do as computer scientists to avert the climate and biodiversity crises anil.recoil.org/notes/icfp25... 🌍

... and I am already looking forward to our next outing! Hopefully, then also with Max MacDonald (who is starting his PhD in October), Matthew Waters (who is another MSci student working with us), and Vasilis Bountris (who is planning to visit us from HU Berlin)!

@uofgcompsci.bsky.social 🏰 🖥️ 🎓

Joining me this time were Kathleen West, James Nurdin, Youssef Moawad, Giulio Attenni, and Magnus Reid.

I am very lucky to get to work with such a bright and friendly group of young researchers at Glasgow! 😊

I believe that research works best as a team sport, with all the obvious benefits, and think that teams work best when there are chances to get to know each other away from the desks from time to time. For example, when there is a tricky flat tire to fix together midway through a bike trip... 🚲 🌬️ 🔧

Many thanks to Chris Anagnostopoulos for the kind invitation to attend and to the whole organizing team and many volunteers for the fantastic conference in Glasgow! 🙏

Always so good to meet colleagues in person – some for the first time, some again after a while! 😊

4: Kathleen will be presenting a short paper on Carbon-Aware Workflow Execution, arxiv.org/abs/2503.13705. This will be Kathleen's first talk at a conference and we are actively working on extending our results in the EPSRC-funded project Casper, so you are most welcome to provide helpful feedback!

3: Fabian will be talking about WOW, arxiv.org/abs/2503.13072, which was accepted as a full paper too – and this one was in the works for a while, with Fabian driving the extensive experimental effort and managing the collaboration between five universities in context of the DFG-funded CRC FONDA!

2: Jonathan will summarize the full paper Flora, arxiv.org/abs/2502.21046. This is an outcome of our DFG-funded research project C5, demonstrating a low-overhead approach to cost-optimizing cloud cluster configurations for big data analytics, evaluated experimentally with 180 Spark application runs!