From Quantum Physics to Climate Tech: My Summer with Open Climate Fix

If there’s one constant in my academic journey so far, it’s that I’ve never stayed in one lane for too long.

I’ve always been someone who jumps between different topics – I get curious, and before I know it, I’m off on a completely new adventure. For example, I started out in theoretical physics, completely absorbed in particle physics and field theories. But by the end of my undergrad, I realised… I’d never actually set foot in a lab! So, in true chaotic-good fashion, I pivoted entirely and did a Master’s in Experimental Nanoscience at Cambridge, working with everything from CRISPR and DNA to perovskites and chemistry.

Fast forward a couple of years, and I’m now in the second year of my PhD, using probabilistic machine learning to tackle problems in quantum technologies. I was happily crunching code and theory when I felt that familiar tug again – time to branch out.

That’s when I stumbled across Open Climate Fix’s Google Summer of Code (GSoC) projects, and one of them stopped me in my tracks: “Applying Probabilistic Machine Learning to Solar Forecasting.”

It almost felt like it had been written just for me.

I applied almost straight away, and when I got the acceptance email, I was ecstatic. I couldn’t wait to dive in. But also, terrified! I mean… a quantum physicist at a climate-focused organisation? For twelve weeks? What if I couldn’t keep up? What if I wasn’t useful? Why did they choose me?!

I decided to go visit the OCF offices early on, and since I’m based in Cambridge, it was an easy journey. Getting off the tube at Waterloo, nerves bubbling, I braced myself. But the moment I stepped in, I was met with warmth, smiles, a lovely tour of the office – and yes, a very good cup of tea! Everyone I met was friendly, welcoming, and genuinely passionate about what they were doing. It was almost infectious.

Early on, we had a GSoC welcome call, and I got to meet the other students working on projects around the world. From [Project X] to [Project Y], it was immediately clear – this summer was going to be buzzing with innovation.

Starting the project, the hardest part (as always) was dealing with the data. But once I got that sorted, I was able to apply my background in probabilistic ML – particularly Gaussian Mixture Models – and begin training models for solar forecasting.

I’ve learned that solar forecasting is both a science and an art – it’s all about predicting how much solar energy will be generated at a specific time and place. This kind of forecasting is vital for grid operators and energy providers to ensure a stable balance between supply and demand, especially as we move toward cleaner, renewable sources. And what really surprised me was just how transferable my background in quantum physics turned out to be. I’ve spent years thinking about uncertainty, modelling complex systems, and applying probabilistic approaches – and all of that came into play here. Whether it was working with satellite imagery, integrating weather data, or training machine learning models, I found that many of the same principles applied.

I owe a huge shoutout to my mentor Felix – without him, I would have been utterly lost at times. From weekly brainstorms to quick Slack messages, his support has been constant and invaluable.

We’re now at the end of the project, and I genuinely can’t overstate how much I’ve learned. Yes, I’ve deepened my understanding of machine learning and climate tech – but more than that, I’ve learned how to collaborate across disciplines, communicate ideas outside of my field, and apply familiar skills to unfamiliar problems.

It’s been eye-opening to see how much innovation happens when people from different backgrounds come together with a shared goal. Stepping out of my academic bubble has reminded me how valuable – and energising – that can be.

I’m excited to see what the team at Open Climate Fix creates next, and I already know I’ll be cheering them on from wherever I end up.

To everyone at OCF: thank you for the kindness, the conversations, and the opportunity to be part of something meaningful. I’m so grateful to have been a small part of it.