In this case study, we hear from Benjamin Jenkins (EngD Formulation Eng FT), who has been making use of BlueBEAR to enable his research into powder simulation and issues surrounding calibration. You probably don’t think about how we use powders in manufacturing on a day-to-day basis and I wouldn’t blame you! They are however, the second most … Continue reading “How BlueBear is Helping us Solve Problems in One of the Hardest Areas of Physics – Powders?”
Author: Aslam Ghumra
Leveraging computational resources to simulate small molecule–protein dynamics
In this case study, we hear from Dr Alan Jones (Pharmacy), who has been making use of BlueBEAR to enable his research in drug discovery. My name is Alan Jones. I am an Associate Professor based in the School of Pharmacy. My research interests are linked to drug discovery in the widest sense (making, optimising, and developing … Continue reading “Leveraging computational resources to simulate small molecule–protein dynamics“
Unraveling the Secrets of Viscous Fluids: Harnessing the Power of Research Computing
In this case study, we hear from Roberto Hart-Villamil (EngD student in Chemical Engineering), who has been making use of BlueBEAR to enable his research into temperature sensitivity and how it affects everyday products. Ever packed your favourite cream for a vacation in a tropical paradise, only to discover it’s turned into an unrecognizable goo? You’re … Continue reading “Unraveling the Secrets of Viscous Fluids: Harnessing the Power of Research Computing”
Computational Fluid Dynamics (CFD) – Special Interest Group rebooted
Computational Fluid Dynamics (CFD) is used in a variety of engineering disciplines, including civil, railway, river, coastal, tidal, meteorological, and chemical engineering. There are a variety of CFD packages commercially available including ANSYS CFX, ANSYS FLUENT and the open source software OpenFoam. Bruno Fraga, the chair of the CFD Special Interest Group is inviting you to be part of this group. Bruno has organised … Continue reading “Computational Fluid Dynamics (CFD) – Special Interest Group rebooted”
Statistical modelling to map and measure crimes against women and children
In this case study, we hear from Dr. Rowland Seymour (Mathematics), who has been making use of help from the BEAR software group to enable his research into safeguarding women. I’m an Assistant Professor in Mathematics and my research involves developing statistical tools to map and measure crimes, such as human trafficking and violence against women … Continue reading “Statistical modelling to map and measure crimes against women and children”
Baskerville pushes the boundaries
In this case study, we hear from Christos Baziotis, from Edinburgh, who has been making use of Baskerville to enable his research in text generation using machine learning models. I am a (3rd) final year Ph.D. candidate at the ILCC at the University of Edinburgh and a member of EdinburghNLP under the supervision of Barry Haddow and Alexandra Birch, in collaboration with Biao Zhang. In … Continue reading “Baskerville pushes the boundaries”
Street-scale resolution air quality modelling for the West Midlands
In this case study, we hear from Dr Jian Zhong (Geography, Earth and Environmental Science), who has been making use of BlueBEAR to enable his research in air quality modelling. I am a Research Fellow in Urban Air Quality Modelling in the Geography, Earth & Environmental Science. My research has focused on urban air quality modelling, urban … Continue reading “Street-scale resolution air quality modelling for the West Midlands”
Crystal structures in the BEAR Cloud
In this case study, we hear from Professor Andrew Morris (School of Metallurgy and Materials), whose research group has been making use of BEAR Cloud to aid discovery. My research group predicts the crystal structure of materials. Experimental discovery of new functional materials can be slow, difficult and expensive. Computational Structure Prediction allows us to … Continue reading “Crystal structures in the BEAR Cloud”
Measuring Brexit Uncertainty: A Machine Learning and Textual Analysis Approach
Duiyi Dai (Claire), a PhD student from the Department of Economics, describes below how BlueBEAR is essential for her research into quantifying Brexit uncertainty, reducing the time spent running her analysis from two months on her own device to just one day! What is your research about? The term “Brexit” was first used in May … Continue reading “Measuring Brexit Uncertainty: A Machine Learning and Textual Analysis Approach”
High-resolution medical scans & Baskerville
In this case study, we hear from Xi Jia, who is doing a Ph.D. in the School of Computer Science. Xi has been making use of BEAR’s Baskerville GPU cluster to dramatically reduce the time it takes to train deep-learning models for medical image registration. I am a fourth-year PhD student, from the School of … Continue reading “High-resolution medical scans & Baskerville”