With the increasing frequency of natural disasters and health emergencies, wearable infrared thermal imaging devices have gained widespread use in the firefighting and medical fields. However, such devices tend to have poor imaging performance and often suffer from low contrast, dark areas, high noise and blurred boundaries, which greatly hinder practical applications.

The Blavatnik Awards for Young Scientists today announced the Finalists for the 2026 Blavatnik Awards for Young Scientists in the United Kingdom. The Awards recognise scientific advances by UK researchers across Life Sciences, Chemical Sciences, and Physical Sciences & Engineering. Now in its ninth year, each Blavatnik Awards Laureate will receive an unrestricted £100,000 (US$135,000) prize, while the remaining six Finalists will be awarded £30,000 (US$40,400) each. 

This year’s Finalists include:

Chemical Sciences Finalists

Michael J. Booth, PhD – University College London (UCL)

Mathew H. Horrocks, PhD – The University of Edinburgh

Maxie M. Roessler, DPhil – Imperial College London

Life Sciences Finalists

Nicholas R. Casewell, PhD – Liverpool School of Tropical Medicine

Thi Hoang Duong (Kelly) Nguyen, PhD – MRC Laboratory of Molecular Biology

Pontus Skoglund, PhD – The Francis Crick Institute

Physical Sciences & Engineering Finalists

Radha Boya, PhD – The University of Manchester

Paola Pinilla, PhD – University College London (UCL)

Iestyn Woolway, PhD – Bangor University

Researchers at Qingdao University have developed a novel algorithm, Microbiome Elastic Feature Extraction (MEFE), that significantly improves the identification of microbiome biomarkers by incorporating phylogenetic, taxonomic, and functional relationships among microbes. This advancement addresses longstanding challenges in microbiome research, such as data sparsity and sequencing errors, potentially leading to more accurate disease diagnostics and personalized medicine. The findings were published on 15 January 2026 in Frontiers of Computer Science.

A research team from Soochow University has developed a novel artificial intelligence (AI) method to improve emotion cause extraction in conversations, enabling machines to better understand the nuanced triggers behind human emotions. Published in Frontiers of Computer Science, this breakthrough addresses key challenges in identifying fine-grained emotional causes within complex dialogues, offering potential applications in mental health support, customer service chatbots, and human-computer interaction systems.