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Meet the NextGen scholars: Pedro

16 April 2026
  • NextGen

Welcome back to Meet the Scholars – a blog series celebrating the talented students supported by G-Research scholarships. These awards form a key part of our NextGen initiative, which is dedicated to nurturing the next generation of researchers in STEM and AI/Machine learning (ML).

These stories spotlight the individuals driving the future of research: their academic journeys, areas of focus and what the opportunity means to them. In this edition, we meet Pedro, who’s returning to academia to pursue a PhD focused on probabilistic machine learning.

Yeah. Uh, so my name is Pedro from my PhD. I'll be going, um, down to Cambridge in, uh, January. Uh, I'll be doing my PhD in computer science, but mostly in machine learning. Uh, I really want to pick up on, uh, foundation models and, uh, self supervised learning, uh, but moving a little bit away from texts more towards different modalities, like imagery and, uh, time series. Uh, my area of research when I was studying, uh, was in machine running space, mostly applied to simulators. Uh, at the time was focused on, uh, COVID simulator and how we could build, um, emulators for, for that simulator. I just think it's extremely captivating how these, uh, models are so generalizable and then almost the bottleneck becomes human creativity and, uh, really thinking through which problems are worth solving. So I guess that's something that I really look forward to having three years where if I do things right, we might move the needle in positively, uh, for someone somewhere, I guess.
Open video transcript

Pedro’s journey so far

“Originally from Portugal, I moved to the UK to study Computer Science and Mathematics at the University of Manchester.”

Pedro went on to complete his master’s at the University of Cambridge, where he researched machine learning techniques in agent-based simulators. After graduating, he spent a year and a half in industry, gaining first-hand experience of how research ideas evolve into technical products.

“That time in industry gave me a clearer understanding of how innovation translates into impact. It reinforced my desire to explore the underlying theory more deeply, while staying connected to practical applications.”

From curiosity to contribution

The G-Research PhD Scholarship marks Pedro’s return to full-time research.

“The scholarship gives me the freedom to focus on the theoretical foundations of probabilistic machine learning, while remaining close to real-world use cases. It’s an opportunity to ask deeper questions about methodology rather than just applications.”

One area Pedro is particularly keen to explore further is reinforcement learning.

“It was one of the first machine learning topics that felt conceptually intuitive to me. I worked on an applied RL project during my master’s and now I’m excited to dive into the underlying theory in much greater depth.”

For Pedro, research impact is about expanding understanding in ways that change what’s possible.

“Impact means contributing to work that meaningfully changes how we understand and interact with the world. Academic research is a rare privilege – the chance to explore ideas that can ultimately reshape reality.”

Opening Doors Through NextGen

Beyond funding, Pedro sees the scholarship as a platform for collaboration and shared learning.

“I’m particularly looking forward to connecting with the other scholars. It’s an incredible opportunity to be part of a cohort doing impressive work across many areas of machine learning. I’m excited to see what collaborations might grow from that.”

Looking ahead, Pedro hopes his research will advance foundational understanding while retaining the potential for meaningful real-world application – embodying the definition of impact that motivates him.

What is G-Research NextGen?

With a mission to solve the world’s most complex challenges, we’re committed to shaping the future of research and innovation.

Through G-Research NextGen we will work with academic partners, educational organisations and charities to help support the next generation of STEM talent.

Learn more

Quickfire with Pedro

One word to describe your research philosophy?

Purposeful.

Favourite way to clear your head after a long day?

Going for a run – sometimes switching it up with HIIT workouts or tennis. Occasionally I’ll finish the day with a live stand-up show.

One concept you’d like to explore more deeply?

Reinforcement learning – particularly its theoretical foundations rather than just downstream applications.

A concept in machine learning more people should know about?

Continuous Thought Machines.

What excites you most about being a G-Research Scholar?

Being part of a cohort working across different areas of machine learning and learning from each other’s research.

Hear from our other scholars

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