NRF Youth Month 2025: Vuako Maluleke

The NRF supports the growth of the next generation of researchers and scholars to sustain South Africa’s knowledge enterprise. June is Youth Month, and this year the NRF is celebrating the youth who are shaping tomorrow through research today. We thank all participants for sharing their stories with us.

Mr Vuako Maluleke is a Master’s student in Nuclear Physics at the University of Venda. He received funding from the NRF for his Master’s studies, and he is conducting his research at NRF-iThemba LABS.

How did your journey start?

My academic journey began at the University of Venda (Univen), where I completed both my undergraduate and Honours degrees in Physics. Growing up, I was always drawn to understanding how things work, particularly in science and technology, so pursuing Physics felt like a natural choice.

It was during my Honours project that my academic path truly began to take shape. That’s when I was first introduced to coding and using Python to analyse experimental data. This experience opened my eyes to the power of computational tools in scientific research. I was fascinated by how data analysis and automation could enhance accuracy, efficiency, and insight, especially in fields like nuclear physics.

This exposure inspired me to pursue my MSc research on the automation of gamma-ray spectrometry using Python-based techniques, with a focus on machine learning and artificial intelligence. I am currently conducting this research at NRF-iThemba LABS, a national facility that offers advanced research infrastructure and expertise in nuclear science. Being part of this environment has deepened my practical understanding of radiation detection and spectrometry, and it has also broadened my perspective through collaboration with experienced researchers and access to cutting-edge technology.

I chose to continue my postgraduate studies at Univen because of the strong academic support; access to meaningful research opportunities; and its growing emphasis on computational and nuclear physics. I didn’t envision this exact path growing up, but each step from curiosity in science to hands-on coding and now national-level research has guided me to where I am today.

How has your affiliation with the NRF impacted your studies/career?

I began receiving funding from the National Research Foundation in 2024, at the start of my MSc degree, and I am currently a beneficiary. Although my relationship with the NRF is still relatively recent, the impact it has had on my academic and personal life has been significant.

NRF funding has enabled me to pursue my MSc research full-time without the stress of financial constraints. This support has been especially important in allowing me to conduct my research at NRF-iThemba LABS, where I’m working on the automation of gamma-ray spectrometry using Python and machine learning. The opportunity to work in such a world-class facility is one I may not have had access to without the NRF’s support.

Personally, the NRF funding has provided stability and motivation. Coming from a modest background, this support has made it possible for me to focus on my studies, deepen my skills in computational and nuclear physics, and grow professionally. It has also opened doors for networking, mentorship, and exposure to national-level research.

In many ways, the NRF has not just funded my studies, it has empowered me to pursue research that contributes to scientific innovation and national development.

What is your research focus/area of expertise?

My current research focuses on the automation of gamma-ray spectrometry using machine learning and artificial intelligence. This work sits at the intersection of computational physics, nuclear physics, and data science, with the goal of enhancing the efficiency and accuracy of radioactive monitoring, particularly in mining and environmental applications.

My main supervisor is Dr Fulufhelo Nemangwele at the Univen, who provides overall guidance on the theoretical and experimental aspects of the project. I am co-supervised by Dr Edward Nkadimeng at NRF-iThemba LABS, who plays a key role in supporting the machine learning component of my research. His mentorship has been especially critical in helping me apply AI tools to analyse gamma-ray spectra and automate key parts of the spectrometry setup. I also receive support from Dr Ntombizikhona (Zina) Ndabeni, who provides guidance in low-energy nuclear physics and helps me strengthen my understanding of the fundamental physics involved.

The core of my work involves developing a Python-based framework that can classify and interpret spectral data more efficiently using convolutional neural networks (CNNs) and Kolmogorov-Arnold Networks (KANs). The goal is to automate the process of identifying radioactive isotopes and quantifying their activity levels from raw spectral data. This research is not only technically challenging but also highly impactful, as it contributes to improving safety and decision-making in radiological monitoring.

Working across institutions (Univen and NRF-iThemba LABS) has given me a valuable opportunity to bridge academic learning with real-world scientific applications, while also strengthening my expertise in AI, machine learning, and nuclear instrumentation.

How is your research helping to shape a better future?

My research is aimed at solving a critical challenge in the field of nuclear science: the manual and time-consuming nature of gamma-ray spectrometry, which is essential for identifying and quantifying radioactive isotopes. This process is especially important in environmental monitoring, nuclear safety, mining operations, and medical applications. However, the traditional methods often rely on expert interpretation and lack the speed, scalability, and objectivity needed in modern settings.

By automating gamma-ray spectrometry using machine learning and artificial intelligence, my research helps improve the accuracy, speed, and efficiency of spectral analysis. This means that radioactive materials can be detected, identified, and analysed more reliably and quickly, reducing human error and enhancing response times in critical environments.

In the context of environmental and occupational safety, this research contributes to more effective monitoring of radiation exposure in mining areas and other radiation-prone zones. It has the potential to support better regulatory compliance, protect public health, and ensure safer workplaces.

Moreover, by using open-source tools and developing scalable Python-based algorithms, my work helps make advanced nuclear analysis more accessible to developing countries and under-resourced laboratories, paving the way for inclusive scientific advancement.

Ultimately, I hope my research will help modernise nuclear instrumentation, contribute to data-driven decision making, and support the broader goal of using science and technology to build a safer, more sustainable future.

Being a young researcher often means juggling numerous responsibilities and expectations. How do you stay motivated and/or balanced?

Being a young researcher definitely comes with its challenges—balancing academic responsibilities, research deadlines, personal growth, and sometimes even financial or family pressures. But what keeps me motivated is purpose and passion. I’ve always been driven by a deep curiosity to understand how things work and how science can be used to solve real-world problems. Knowing that my research in automation of gamma-ray spectrometry could one day contribute to environmental safety or improve monitoring systems in the mining industry gives me a strong sense of direction and responsibility.

I also stay motivated by surrounding myself with supportive mentors and peers. My supervisors, Dr Fulufhelo Nemangwele, Dr Edward Nkadimeng and Dr Ntombizikhona Ndabeni, not only guide me academically but also encourage me to stay grounded and focused. Their belief in my potential reminds me that I’m not on this journey alone.

To maintain balance, I’ve learned to manage my time carefully, prioritise tasks, and take care of my mental and physical well-being. I make time for regular breaks, walks, and sometimes just stepping back to reflect. I also enjoy engaging in science outreach or attending workshops, which gives me a fresh perspective and helps break the routine.

Most importantly, I remind myself that growth takes time. I embrace small wins, stay open to learning, and stay connected to the bigger picture of why I started this journey in the first place.

What has been your proudest achievement to date?

One of my proudest achievements to date was being accepted to conduct my MSc research at NRF-iThemba LABS, one of the leading nuclear research facilities in Africa. Coming from a rural background in a small village called Nghalalume under Giyani in Limpopo, this milestone represents how far I’ve come both academically and personally.

During my Honours year at the University of Venda, I was introduced to coding and data analysis using Python—something completely new to me at the time. That experience not only sparked my interest in computational science but also led me to pursue my MSc research in automating gamma-ray spectrometry using AI and machine learning.

What makes this journey even more rewarding is the opportunities I’ve had to share and grow my work on national and international platforms. I’ve presented my research at the Centre for High Performance Computing (CHPC) Conference, the South African Institute of Physics (SAIP) Conference, and I had the privilege of participating in the SA-JINR Summer School, which broadened my understanding of nuclear science and connected me with peers and professionals from across the continent and beyond.

These experiences have been incredibly humbling and empowering. They’ve shown me that, regardless of where you come from, you can make meaningful contributions to science, represent your community with pride, and inspire others to believe in their own potential.

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