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Associate Professor Nina Tahmasebi | A new approach for detecting changes in word meaning over time
Words change their meanings over time, but tracking these changes has traditionally required painstaking manual analysis by linguists. In recent years, researchers have been using computational models to automatically detect when semantic change happens, and how much of a change has occurred. Recent research led by Associate Professor Nina Tahmasebi and her colleagues in the Change is Key! program introduces innovative computational methods for detecting qualitative features of semantic change, opening new possibilities for understanding language evolution at scale.
Do Security and Regulation Failures Put Women’s Health Data, Their Privacy and Even Their Safety at Risk?
Recent research from Professor Maryam Mehrnezhad at the Information Security Department, Royal Holloway University of London and a team of researchers reveals widespread privacy, security and regulatory failings in female-oriented health technologies (also known as FemTech). The researchers’ comprehensive analysis demonstrates how current practices leave sensitive health information vulnerable, while highlighting an urgent need for reform across technical, legal and social dimensions of digital healthcare.
Dr. Luc Raijmakers | Comparing Simplified Physics-Based Models for Lithium-Ion Batteries
In order to operate safely and efficiently, lithium-ion batteries rely on battery management systems to monitor their state and to control their operation. An essential part of this process is modelling battery behaviour under different conditions to predict performance and prevent failures. To do this efficiently, it is crucial to simplify the underlying physical processes, while sacrificing as little accuracy as possible. Through their research, Dr. Luc Raijmakers and colleagues at the Jülich Research Centre, Germany, compare various different approaches to simplifying simulations. Their results could make it easier for battery operators to decide which approach is best suited to their requirements for accuracy and computational efficiency.
Dr Patrick O’Neill | Revolutionising Pharmaceutical Synthesis with Continuous Flow Chemistry
Dr Patrick O’Neill of Pfizer, Ireland, and Professor Jie Wu of the National University of Singapore, and their team, have made groundbreaking advancements in the synthesis of 1,2,3-triazole – a key building block in the manufacture of a life-saving antibiotic. Replacing traditional batch processes, they developed a safer, more efficient method using continuous flow chemistry, which addresses potential global supply chain vulnerabilities. This innovative approach eliminates hazardous intermediates, improves reaction safety, and ensures a stable supply of 1,2,3-triazole for global pharmaceutical production.
Dr Ramtin Zand | A Hybrid System for Real-Time Sign Language Translation
Neuromorphic computing is a powerful tool for identifying time-varying patterns, but is often less effective than some AI-based techniques for more complex tasks. Researchers at the iCAS Lab directed by Ramtin Zand at the University of South Carolina, work on an NSF CAREER project to show how the capabilities of neuromorphic systems could be improved by blending them with specialized machine learning systems, without sacrificing their impressive energy efficiency. Using their approach, the team aims to show how the gestures of American Sign Language could be instantly translated into written and spoken language.
Dr. Mingjun Xie | A Blueprint for Life: Creating Blood Vessels in Bioprinted Tissues
A future where injured or diseased organs can be removed and replaced with new lab-printed tissues that are customized specifically for each patient is not as far away as you might think. These functional and living tissues could grow naturally within the body, and repair and sustain themselves over time. While these concepts were once in the realm of science fiction, advances in bioprinting, which is a form of 3D printing using biological “inks” (known as bioinks) loaded with living cells, are bringing them closer to reality. Among the researchers advancing this field is Dr. Mingjun Xie of Zhejiang University, China, and colleagues, who are performing work that addresses a significant challenge in bioprinting. This involves creating large portions of tissues that have a functional vasculature, thereby mimicking the complexity of native tissues and organs.
Professor Christophe Ley | Spotting relationships in complex angular datasets
Data involving angles can be found across a diverse array of scientific fields, but so far, the mathematical tools used to study them have often proved insufficient to detect the complex relationships between different angles within large datasets. Through its research, a team consisting of Professor Christophe Ley and Sophia Loizidou from the University of Luxembourg, Professor Shogo Kato from the Institute of Statistical Mathematics in Tokyo, and Professor Kanti Mardia from the University of Leeds, has developed a new model which overcomes many of these challenges: allowing the researchers to study relationships between three angles at once, as well as mixtures of angles and classical measurements on the line.
Dr. Chance Glenn | Could extreme electric fields make the warp drive a reality?
For decades, works of science fiction have explored how the universe’s most fundamental speed limit could be broken by warping the fabric of spacetime. Through his experiments, Dr. Chance Glenn, founder of Morningbird Space Corporation, believes he may have discovered how spacetime can be distorted by extreme electric fields, which can be easily created in the lab. If his theory is correct, it would mean that the concept of ‘warp drives’ which allow us to travel at faster than the speed of light could be more feasible than we once thought.
Dr Sandra Goritschnig – Dr Pasquale Tripodi | The Science of Greens: Using Genetic Insights to Cultivate Better, Stronger Lettuce
In recent years, rapid advancements in techniques for genetic analysis and manipulation have enhanced our potential to understand and improve crop diversity. An innovative project led by Dr. Pasquale Tripodi of the Italian Council for Agricultural Research and Economics and Dr Sandra Goritschnig of the European Cooperative Programme for Plant Genetic Resources marks a significant advance in the study of lettuce genetics. Their recently published research platforms a highly sophisticated technique to analyse genetic diversity within lettuces called Single Primer Enrichment Technology, or SPET for short. This approach provides a highly detailed view of lettuce genetics and also has significant implications for agricultural resilience and crop selection and breeding.
Dr. Robert Tomkowski | Investigating How Dimpled Surfaces Can Minimise Friction
Dimpled surfaces offer a useful and easily implementable way to reduce friction between lubricated surfaces as they slide over each other. Through cutting-edge simulations, Dr. Robert Tomkowski and colleagues at the KTH Royal Institute of Technology in Sweden explore how the microscale structures of surface dimples can be optimized to minimize friction. Their findings could help to reduce wear in mechanical systems, while also making them more energy efficient.
Professor Suzanne Scarlata – Dr. Nima Rahbar | How a Biological Enzyme Could Help Concrete to Heal Itself
As an inherently brittle material, concrete often needs to be replaced after just a few decades: driving a demand which incurs significant costs for Earth’s climate. Through their research, Professors Suzanne Scarlata and Nima Rahbar at Worcester Polytechnic Institute, Massachusetts, introduce a new mechanism that allows concrete to quickly repair itself, with the help of an enzyme vital to the function of living cells. This approach could help to reduce the world’s insatiable demand for concrete.
Lixiang Zhang | Seeing the Full Picture: The CPS-Merge Approach to Assess Complex Datasets
In the age of big data, and particularly in specialisations such as artificial intelligence, biology, and medicine, researchers often generate large and complex datasets that are challenging to analyse. This is particularly true for multi-view data, otherwise known as multimodal data, which are data that encompass multiple perspectives concerning a single entity or phenomenon. In the case of single-cell genomics, for instance, researchers can measure a huge range of different characteristics concerning an individual cell, such as RNA expression levels or protein levels. While multi-view datasets provide vast amounts of information, they are difficult to analyse because looking at each type of data within them provides only a small part of the overall picture. A new computational approach called Covering Point Set-merge analysis, or CPS-merge analysis for short, has been developed by Lixiang Zhang of Pennsylvania State University and colleagues, and it aims to assist researchers to merge the different types of data present in multi-view datasets into one coherent and meaningful set of results, without misrepresenting the individual contributions of each type of data.
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