Each month, we provide up to £2,000 in grant money to early career researchers in quantitative disciplines.
Our aim is to support and assist PhD students and postdocs conducting research, particularly with costs that may be difficult to get funding for elsewhere, for example, travel for those who are caring for children, or expenses for volunteer work related to research.
Learn more about our grant programme, including how you can apply and the work we support.
Read on to hear from our latest winners, their research and how our grants will aid their work.
May grant winners
Tibor Dome (University of Cambridge)
“I am an astroparticle physicist specialising in the study of dark matter, a mysterious substance that comprises the majority of matter in the Universe and interacts primarily through gravity.
“My research focuses on utilising advanced computer simulations to explore the behaviour of galaxies and dark matter halos, which are massive structures responsible for holding galaxies together. Through these simulations, I aim to unravel the hidden properties of dark matter on non-linear scales that cannot be easily accessed through analytical methods.
“I am thrilled to have been awarded the prestigious G-Research grant, which will support my participation in the esteemed PASCOS conference in the United States. This conference provides an exceptional platform for disseminating my findings and collaborating with leading experts in the field. By exchanging ideas and insights with fellow researchers, I hope to further deepen our understanding of dark matter and contribute to the collective effort of unravelling its enigmatic nature.”
Ben Boyd (University of Cambridge)
“I am a PhD student at the University of Cambridge, where my research lies at the intersection of astrophysics and machine learning.
“My research focuses on the Bayesian hierarchical modelling of Type Ia supernovae. These models are very well understood and can be used to infer distances to galaxies, as well as cosmological parameters such as the age, expansion and dark energy density of the Universe. The next generation of surveys are providing unprecedented amounts of high-resolution supernovae data for analysis, meaning our models need to be scalable in order to keep up. Supernovae are perfect for machine learning as they vary in time as well as wavelength, meaning they are high-dimensional. I am interested in using simulation-based inference and other machine learning techniques to allow our models to scale with the demands of the large datasets.
“I am grateful to G-Research for awarding me their grant to help purchase a new laptop for my research. A professional laptop will allow me to run trial supernovae machine learning models and simulations locally, making my research portable and increasing my productivity.”
Aras Selvi (Imperial College London)
“I am a penultimate-year PhD student at Imperial College London as a member of the Models and Algorithms for Decision-Making under Uncertainty research group, and a placement student at The Alan Turing Institute. I work on designing optimisation and machine learning models that are robust against uncertainty.
“In my recent work I worked on differential privacy, a framework that allows using sensitive data (for example, in machine learning) while promising a statistically quantifiable level of privacy to the individuals contributing to such data. I show that the design of optimal differentially private mechanisms can be formulated and solved as a distributionally robust optimisation problem. We are hoping that this work heralds in a new stream of research in this area that is of industrial and societal interest.
“Thanks to the generous G-Research grant, I will be able to present my work at the INFORMS Annual Meeting (October 2023, Phoenix, USA), which is the largest conference in my field.”
Maria-Romina Ivan (University of Cambridge)
“I am a pure mathematician working in the area of combinatorics. More precisely, I focus on poset saturation and Ramsey theory.
“As a consequence of my work, I have been invited to the CanaDAM 2023 Conference, one of the biggest in the world, to give a talk as part of their Ramsey Theory Minisymphosia. There I will be talking about my latest results on an old question in the field: ‘Suppose we colour the rational numbers with finitely many colours. Must there exist an infinite set such that all its pairwise sums and products have the same colour?’. This is joint work with Neil Hindman and Imre Leader, and is one of the few new results on this question in the last 20 years.
“Thanks to the G-Research Grant I will have the possibility to not only present my work, but most likely form new collaborations that will ultimately lead to answering this question fully.”
Haitz Sáez de Ocáriz Borde (University of Oxford)
“I am a PhD student at the University of Oxford working on Machine Learning, in particular, on Geometric Deep Learning and Generative Models.
“I would like to thank G-Research for this research grant, which supported my attendance at the International Conference on Learning Representations (ICLR 2023) in Kigali, Rwanda, where I presented my paper ‘Latent Graph Inference using Product Manifolds’. The paper explores leveraging Riemannian Geometry and Product Manifolds to infer latent graphs for Graph Neural Networks.”
Congratulations to our grant winners.
