The following blog post has been written by Yaru Zhou, who is from the organising committee of the BEAR Conference 2026. The 15th Annual BEAR PGR Conference brought together postgraduate researchers from across the University of Birmingham for a day of interdisciplinary discussion centred around this year’s theme: AI x Integrity. Sponsored by Lenovo and NVIDIA, … Continue reading “Reflections from the 15th BEAR Conference 2026 “
Category: PGR students
Using AI to Bring Indigenous Storytelling Character Figures into Chemistry Education
In this blog, we hear from Dina, a second-year Ph.D. student in Chemical Education, School of Chemistry, who won the best short talk at the BEAR conference 2026. Dina, conducted research that intersects chemistry education, technology, and ethnochemistry. Ethnochemistry is a multidisciplinary field that explores the relationship between chemistry and the traditional wisdom, practices, and … Continue reading “Using AI to Bring Indigenous Storytelling Character Figures into Chemistry Education”
Learning from Nature: Using HPC to Design Efficient Jet Propulsion
In this case study, we hear from Yukesh Karki, a doctoral student from Aerospace Engineering in the School of Metallurgy and Materials, who used BlueBEAR to identify the optimal three-dimensional nozzle geometry for hydrodynamic jet propulsion. He is also the winner of ‘best talk’ at the BEAR Conference 2026. Nature has already evolved highly efficient methods … Continue reading “Learning from Nature: Using HPC to Design Efficient Jet Propulsion “
Understanding multi-agent learning through large-scale simulations
In this case study we hear from Tuo Zhang, a researcher working in Machine Learning, who has been using BlueBEAR to run large-scale simulations of multi-agent reinforcement learning (MARL) algorithms. His research focuses on understanding how learning agents behave when interacting with each other in complex and changing environments. In many real-world systems, decision-making is not performed … Continue reading “Understanding multi-agent learning through large-scale simulations”
Modelling Birmingham’s Cultural Ecology and Urban Oral History Using BlueBEAR
In this case study, we hear from Jack (Wei-Chieh Tsai), a doctoral student from History of Art and Geography who used BlueBEAR to examine how cultural intermediaries, including artists, curators, and cultural organisations, have contributed to urban development. My PhD research examines the role of artistic interventions in transforming post-industrial Birmingham between 1986 and 2016. The project … Continue reading “Modelling Birmingham’s Cultural Ecology and Urban Oral History Using BlueBEAR”
Binary classification of lung tissue immunofluorescence images by deep learning
In this case study we hear from Ellen Jenkins, a postdoctoral student from the Institute of Inflammation and Ageing. Ellen is looking into developing a deep learning model to automatically differentiate the tissue from the air space. There is an ongoing project in the respiratory research group (CMH, IIA) which utilises samples of human lung … Continue reading “Binary classification of lung tissue immunofluorescence images by deep learning”
Bayesian Modelling of Rising Decision Thresholds in DDMs using BlueBEAR
In this case study we hear from Sophie Wetz, a Masters student in Psychology, who has been using BlueBEAR to investigate whether a dynamic, rising boundary improved the fit of the full Drift Diffusion Model (DDM) to Random Dot Kinematogram (RDK) task data. I’m a Master’s student on the Computational Neuroscience stream in the School … Continue reading “Bayesian Modelling of Rising Decision Thresholds in DDMs using BlueBEAR”
Atomic Simulation to Build Better Batteries
In this case study we hear from Oskar Soulas, a PhD student in Chemistry, who has been using BlueBEAR to investigate lithium–sulphur–nitrogen solid electrolytes for next-generation battery technologies. I am a second year PhD student in the Scanlon Materials Theory Group (SMTG) based at the University of Birmingham. The group uses powerful computational tools to understand … Continue reading “Atomic Simulation to Build Better Batteries”
Bio-inspired FSI and HPC-driven aerodynamic optimisation
In this case study we hear from Hibah Saddal, a PhD student in Aerospace Engineering, who is using BlueBEAR to optimise aerodynamic performance. At the 14th BEAR Conference 2025, I had the opportunity to present my research carried out with my PhD advisor, Dr Chandan Bose, on bio-inspired fluid-structure interaction (FSI) problems, where we leveraged … Continue reading “Bio-inspired FSI and HPC-driven aerodynamic optimisation”
High-resolution soil hydrology analysis enabled by BlueBEAR
In this case study, we hear from Guilin Luo, a PhD student in the School of Geography, who has been harnessing BEAR’s advanced computing resources to investigate how temperate forest soils respond to climatic change. By integrating high-resolution environmental monitoring data from the Birmingham Institute of Forest Research (BIFoR) site, and using workflows in R … Continue reading “High-resolution soil hydrology analysis enabled by BlueBEAR”