Chancellor's Fellowships awarded

A total of 40 academics have been announced as the latest Chancellor’s Fellows, a five-year tenure track that invests in researchers delivering cutting-edge interdisciplinary research and innovation. Half of this latest cohort will work at schools and units from the College of Science and Engineering.

The College of Science and Engineering awardees are grouped below by our three priority research thematic areas: Health and Life, Climate and Environmental Science and AI and Data Science.

Dr Crosby will use a combination of cell biology and biochemistry approaches to understand how single cells align their circadian rhythm with the outside world.

Dr Mair is interested in the factors shaping immune regulation at barrier sites such as the gut or the skin which are constantly exposed to outside influences including microbial diversity, infections and seasonal changes. 

Dr Calder’s research will focus on developing chemical tools based on molecules known as cyclic peptides, to investigate the enzymes involved in the modulation of ubiquitin-like proteins. He aims to collaborate with researchers across the University to develop tools to aid research in areas including cancer, neurodegeneration, and inflammatory diseases.

Dr Grant’s research focuses on creating advanced 3D cellular models of human organs to provide insight into biological questions and tools for researchers to test new materials and pharmaceuticals more accurately.

Dr Owen will be integrating numerical modelling into machine-learning frameworks in order to develop diagnostic devices capable of early-stage cancer detection from blood samples.

Dr Kudryashova works in the field of NeuroAI, and will apply her research to understanding the mechanisms underlying neurological conditions and enabling effective decoding of movement for developing prosthetic devices and human-machine interfaces.

Dr Nicholson will build mathematical models to characterise the origin of mutations that are observed in cancer genomes. Through integrating the models with modern genomics datasets, he will provide insights on how cancer mutations occur, and what the consequences of the mutations are.

Dr Wimberley works in medical imaging physics and her fellowship will focus on the development of novel methods for the quantification of Positron Emission Tomography (PET) imaging data, an imaging method used to study diseases such as cancer and dementia.

Dr Simmond’s work will push the boundaries of ecological forecasting of population changes, allowing us to plan for the future. She will explore which factors cause uncertainty in our predictions, determine how to reduce this uncertainty, then work with population managers to create predictions that can be used with confidence to reduce biodiversity loss.  

Dr Kong’s research seeks to generate industrially important molecules from molecules such as carbon monoxide and carbon dioxide using multi-metallic cooperativity. His research will use a combination of synthetic, spectroscopic, and computational techniques to develop design principles and structure-activity relationships for novel catalysts.

Dr Panidi’s research aims to develop sustainable electronics for energy harvesting and optoelectronic applications. Focus will be given to the careful consideration of raw materials and solvents to enable environmentally friendly manufacturing processes.

Dr Malik’s research plan is to understand the mechanisms by which soil microbiomes and other interacting factors influence the carbon balance in different terrestrial ecosystems. This knowledge will permit informed manipulation of microbial processes to sequester carbon in soil, that will aid climate mitigation, ecosystem restoration, and sustainable agriculture.  

Dr Miles’ research will focus on assessing the vulnerability of Antarctic ice shelves to future extremes in climate and weather events. To achieve this, he will use satellite imagery to monitor iceberg calving events over the past decade.

Dr Rugheimer’s research models the climate and photochemistry of early Earth and Earth-like planets to better understand habitability and how we could detect and characterise habitable worlds with future telescopes like the Habitable Worlds Observatory and LIFE – the Large Interferometer for Exoplanets. 

Dr King-Smith’s research harnesses advances in deep learning and AI, with an emphasis on experimental validation, to build practical and robust predictive models that deepen our understanding about the reactivity of small organic compounds.

Dr Filgueira will be conducting research at the intersection of natural language processing (NLP), data science, and distributed computing. Her work aims to enhance software understanding through semantic code techniques, optimise code search and reuse efficiency, develop scalable application abstractions, and pioneer new methodologies for seamless adoption of advanced data science and AI techniques in collaboration with domain scientists.

Dr Malkin’s research will develop the algorithmic foundations of machine reasoning and their applications in mathematical and scientific discovery, empowering AI systems to explore and explain the world in ways that are understandable to humans. His research will contribute to the creation of safe, reliable intelligent systems that augment human cognitive abilities, opening new possibilities for understanding patterns in nature and society.

Dr Allaway’s research will develop interpretable neuro-symbolic methods to improve defeasible reasoning in computational systems. These methods will incorporate theoretically-grounded components into deep learning models in order to provide interpretability. Using these methods, her research will improve computational defeasible reasoning in real-world texts, focusing on dialogues, argumentation, and text-based games.

Dr Lee’s research focuses on establishing novel tools for studying functional data, such as time series and images, by leveraging connections at the interface between geometry, analysis, and category theory. His aim is to develop the theory and computational methodology behind these tools, while collaborating with domain experts to bring these tools into practice.

Dr Kanwar’s research focuses on the development of generative AI methods and the advancement of fundamental physics using these tools. He is particularly interested in generative models capable of precisely sampling fluctuations of the quantum fields believed to describe all matter in our universe.