Treasure Island Pedagogies: Episode 40, the one with the Hammock

Posted on: 23 May 2025 by Dr Tunde Varga-Atkins in General

In Episode 40, the Treasure Island Pedagogies podcast features insights on postgraduate research supervision, with guests sharing coaching strategies, interdisciplinary tools, and collaborative approaches that support PhD students' growth. From lightbulb moments to luxury items, the episode highlights the balance between guidance and independence in research supervision.

Speakers: Eva Caamaño Gutiérrez, Christopher Overton, David Joss

Date: 23 May 2025

Treasure Island Pedagogies: Episode 40 podcast

(Treasure Island Pedagogies Episode 40 - Podcast Transcript)

Read or listen to find out our guests’ lightbulb moments, teaching props, pedagogies and luxury items that they would take to their Treasure Islands for precious contact time with students. 

Eva Caamano Gutierrez, University of Liverpool, UK

@evacaamano.bsky.social

• Original discipline: I completed a five-year degree in Biotechnology at the University of León in Spain, followed by an MSc and PhD in Systems Biology at the University of Warwick, UK.
• Current Role: I’m the Director of the Computational Biology Facility. As a team, we support data science, software development, and bioinformatics across the biomedical sciences. I lead a portfolio of 20–50 projects, focusing on scientific delivery, direction, and income generation, while coordinating a team of around 15 post-PhD professionals. Although teaching is a smaller part of my role, it remains an important aspect of my academic identity.
• Lightbulb moment: A particularly niche but memorable moment came during a PhD project focused on machine learning and pancreatic cancer metastasis. One student reported metrics that were almost too perfect—99% accuracy, sensitivity, etc. After critically reviewing their methodology, they exclaimed: "Oh no! I oversampled the minority class before splitting the data into training and test sets." This caused identical pathogenic variants to appear in both datasets—classic data leakage. The realisation was profound: oversampling must occur after the train-test split and only on the training data, to preserve independence and avoid inflated performance. That moment encapsulated the importance of rigorous validation in data science.
• Teaching Prop or Pedagogy: In formal teaching, I use live, anonymous quizzes with concrete questions. These foster engagement by removing the fear of being wrong in public and give me the chance to explain the reasoning behind answers, busting common misconceptions along the way. With research students, I adopt a coaching style that promotes curiosity and scientific rigour. I constantly ask: Why did you choose this? What’s the evidence? I encourage intentional choices and due diligence. If something seems too good to be true, it usually is — so we dig deeper, question everything, and validate thoroughly.
• Luxury Item: A drink with colleagues and friends on a Friday evening — or a good book if I’m enjoying some solitude.

Christopher Overton, University of Liverpool, UK

• Original discipline: I began with six weeks of Architecture at the University of Liverpool, before switching to a four-year MMATH degree in Mathematics and completing a PhD in the same field. I briefly worked as a PDRA at the University of Manchester before becoming a Principal Infectious Disease Modeller at the UK Health Security Agency. I now divide my time between the UKHSA and my role as Lecturer in Mathematics for Healthcare at the University of Liverpool.
• Current Role: Lecturer in Mathematics for Healthcare at the University of Liverpool.
• Lightbulb moment: My first PhD student is now in their second year, and we’re working towards their first publication. It’s hard to pinpoint a single moment, but when I read a recent draft of their paper, I found myself thinking, “Wow, they really know what they’re talking about.” Suddenly, the narrative we’d been building and the mathematics underpinning it all clicked into place. It was a powerful reminder of how much growth can happen in 18 months — for both student and supervisor.
• Teaching Prop or Pedagogy: I embed research into teaching wherever I can. In my modules, we read current research papers and tackle homework based on research-style questions. Through my PhD supervision, I naturally engage with research, but I also conducted an action research project into how supervisors can best support interdisciplinary PhD students. This deepened my understanding of the challenges they face and helped me shape better, more inclusive supervisory practices.
• Luxury item: Assuming my one-year-old son doesn’t count as an “item”, I’d bring my gaming PC.

David Joss, University of Liverpool, UK

• Original discipline: I’m a Professor of Physics at the University of Liverpool, where I also completed my BSc and PhD in Nuclear Physics. Over the years, I’ve lectured at various UK universities and worked as a scientist in a national laboratory.
• Current Role: I’m about to step into the role of Nuclear Physics research group leader. Our group includes nearly 50 people—academics, postdocs, technical staff, and postgraduate researchers. I’ve had the privilege of supervising many research students throughout my career.
• Lightbulb moment: As a supervisor, I realised the importance of actively managing expectations for new research students and scaffolding their learning as they progress. They don’t need to know everything from day one. For many students, the key realisation is that experiments often don’t go to plan. Sometimes Nature doesn’t cooperate, the phenomena you’re studying are too subtle to detect, or equipment fails. But these “failures” are actually vital learning opportunities. They build resilience and critical thinking. Always have a plan B when booking time at a research facility.
• Teaching Prop or Pedagogy:I’d bring a software package called Radware, which we use to analyse gamma-ray emissions from excited nuclei and map the quantum states within a nucleus. Beyond its technical utility, it fosters collaborative, side-by-side analysis between supervisor and student. It flattens the hierarchy, inviting genuine scientific dialogue.
• Luxury item:A good book and a hammock.

Any Sparks? How Might Our Joined-Up Treasure Islands Look Like?

When our islands come together, they form an archipelago of possibility: a richly collaborative space where curiosity, coaching, and critical thinking converge. Tools like Radware sit beside interdisciplinary roadmaps; hammocks lie within reach of laptops; books share space with dashboards of data. What connects us is a shared commitment to mentoring over mere supervision. We guide students as explorers, not just executors — encouraging rigour, resilience, and reflection. Our joined-up Treasure Islands become more than the sum of their parts: a haven where learning is dynamic, student-led, and deeply rooted in real-world complexity.