New cutting-edge research, led by Academy Professor Otso Ovaskainen of the University of Jyväskylä and David Dunson at Duke University, combines citizen bird observations with artificial intelligence and the computing power of supercomputers at CSC – IT Center for Science. The international and multidisciplinary research team has developed the world’s most accurate prediction model, capable of anticipating even small shifts in bird occurrence almost in real time. 

For the first time, researchers have experimentally discovered optical meron-antimeron pairs—a novel class of topological quasiparticles that were originally conceived in particle physics and later found in magnets, but had never been realized in optics. By employing group representation theory, the team not only generated these states in deep-subwavelength plasmonic systems but also established a complete symmetry classification that dictates their topological invariants. This framework reveals a fundamental chirality-parity locking effect and enables the creation of isolated merons. Harnessing the robustness of these symmetry-protected states, the work demonstrates an ultra-sensitive sensing application with a record λ/133 resolution, bridging abstract theory to practical photonic technology.

As an emerging branch of clinical medicine, microbiota medicine has attracted worldwide attention from clinicians, medical educators, patient communities, and industry. However, this developing field still lacks consensus on its fundamental principles as well as guidelines for clinical and educational practice. An expert panel was convened by the journal Microbiota Medicine Research at the 2025 CHINAGUT Conference to develop the principles and practice guidelines of microbiota medicine.

Researchers from the Faculty of Engineering at The University of Hong Kong (HKU) have developed two innovative deep-learning algorithms, ClairS-TO and Clair3-RNA, that significantly advance genetic mutation detection in cancer diagnostics and RNA-based genomic studies.

The School of Computing and Data Science (CDS) of the University of Hong Kong (HKU) has embarked on a new chapter, launching its first-ever dual-site semester across Hong Kong and Shanghai. As the 2025–2026 academic year enters its second semester, CDS students in the exclusive Tech Immersion Fellowship programme can now split their studies between HKU’s main campus and the newly opened HKU-CDS Teaching and Research Site in Shanghai—a strategic move that redefines cross-border tech education.

The University of Hong Kong (HKU) and the South China University of Technology (SCUT) formalised a partnership through a Strategic Collaboration Agreement to establish the Hong Kong Base of the State Key Laboratory of Subtropical Building and Urban Science (SKL-SBUS). A launch ceremony was held today (21 January) at the Convocation Room, HKU, marking a strengthened partnership between the two universities in the fields of architecture and urban science.

Talking to oneself is a trait which feels inherently human - but it’s not just humans who can reap the benefits of such self-talk. Published in Neural Computation, scientists from the Okinawa Institute of Science and Technology (OIST) have demonstrated the potential of inner speech to improve AI learning, showing how AI models can generalize across different tasks more easily when supported by both inner speech and short-term memory.

POSTECH, the University of Wisconsin–Madison, and the University of Tokyo control oxide electronic structures via local atomic arrangements at moiré interfaces.

Seeing chemistry unfold inside living cells is one of the biggest challenges of modern bioimaging. Raman microscopy offers a powerful way to meet this challenge by reading the unique vibrational “signatures” of molecules. However, cells are extraordinarily complex environments filled with thousands of biomolecules. To make specific molecules stand out, researchers often attach small chemical “probes,” such as alkyne tags, that produce signals in a so-called cell-silent spectral window where native cellular components do not scatter light. This allows Raman microscopes to selectively detect the tagged molecules against an otherwise crowded molecular background. Despite this advantage, the widespread adoption of Raman microscopy in biology has been limited by one fundamental problem: Raman signals are extremely weak. In a new study published in Angewandte Chemie International Edition, TIFR researchers report a molecular design strategy that dramatically amplifies Raman signals, enabling the development of Raman sensors that can detect biomolecules using standard spontaneous Raman microscopes. These new Raman sensors enable sensitive, ratiometric imaging of biological molecules and ions, such as hydrogen peroxide molecules, copper ions, and pH, inside living cells. The work is supported by the Department of Atomic Energy, Government of India, and the Japan Science and Technology Agency, with the research team comprising Prof. Ankona Datta and Sujit Das from the Tata Institute of Fundamental Research, Mumbai, and Heqi Xi, Itsuki Yamamoto, and Prof. Katsumasa Fujita from the University of Osaka, Japan.