Subject Award · Physical Sciences & Engineering · 2026
The ten finalist universities are the ten highest-ranked on the Engineering collaboration index, listed here alphabetically until the full index publishes on 15 September. Each finalist is represented by an academic whose recent work exemplifies why: a real project, drawn from the open scholarly record, cited so you can check it.
The finalists
Industry 5.0: Prospect and retrospect
Manufacturing thinking is already moving beyond Industry 4.0. The work surveys Industry 5.0, looking back at how the concept emerged and forward at where it may lead, offering both prospect and retrospect on this next phase of industrial development and the systems that will support it.
Innovations in earthquake risk reduction for resilience: Recent advances and challenges
Reducing casualties, physical damage and interruption to critical infrastructure from earthquakes depends on linking multidisciplinary research and technological innovation with policy and engineering practice. Framed by the Sendai Framework for Disaster Risk Reduction, the work shares knowledge and promotes discussion of recent advances, challenges and future directions in earthquake risk reduction for resilience.
Digitalization to achieve sustainable development goals: Steps towards a Smart Green Planet
Smart systems and big data could be steered towards a fairer, greener world. The work describes how digitalisation can help address the United Nations Sustainable Development Goals, envisioning smart technologies as game-changing tools for the food-water-energy nexus: sustainable food production, access to clean and safe water, and green energy generation and use.
Organoids are tissue-engineered models grown in the laboratory that reproduce much of the structure and function of real human tissue. Surveying the materials and methods used to culture, grow, differentiate and mature them, the work explains how these systems support fundamental studies of development, regeneration and repair, alongside diagnostics, disease modelling, drug discovery and personalised medicine.
Aerial additive manufacturing with multiple autonomous robots
Imagine 3D printing carried out in mid-air by machines that coordinate among themselves. The project explores aerial additive manufacturing with multiple autonomous robots, bringing together flight, autonomy and the deposition of material in a single manufacturing approach.
Polarisation optics for biomedical and clinical applications: a review
Polarised light carries vectorial information that biological tissue transforms in revealing ways, and such techniques have been harnessed in biological and clinical research for decades. The work draws together methodologies and applications in tissue polarimetry, with emphasis on the Stokes-Mueller formalism, and surveys recent breakthroughs, development trends and potential multimodal uses alongside other techniques.
Defects in perovskite nanocrystals stand in the way of high-efficiency light-emitting diodes. The work pursues comprehensive defect suppression in these nanocrystals to enable more efficient devices, an approach reported in Nature Photonics by collaborators across five countries working at the frontier of light-emitting materials.
FAST-LIO2: Fast Direct LiDAR-Inertial Odometry
Autonomous machines that navigate with laser scanners must fuse sensor data quickly and accurately. The project delivers a fast, robust LiDAR-inertial odometry framework that registers raw points directly to the map, avoiding hand-engineered feature extraction, and maintains the map with an incremental k-d tree, making precise navigation and mapping adaptable to emerging LiDAR sensors with different scanning patterns.
Ligand-engineered bandgap stability in mixed-halide perovskite LEDs
Reported in Nature, the work addresses the stability of the bandgap in light-emitting diodes made from mixed-halide perovskites. Through ligand engineering, the team, spanning five countries, pursued a way to keep that bandgap stable, a contribution to the wider effort to develop LEDs from these materials.
SpectralGPT: Spectral Remote Sensing Foundation Model
Most artificial intelligence models for imagery are built for ordinary photographs, not the rich spectral data captured from space. The team created SpectralGPT, the first universal remote sensing foundation model purpose-built for spectral imagery, using a three-dimensional generative pretrained transformer that accommodates images of varying sizes, resolutions, time series and regions.
Exclusive to partners
Partners verify their data, feature their academics, and are eligible for the Subject Awards. Finalists are identified from open data; winners are decided by our editorial team and announced on 15 September 2026.
Explore partnership →The wider slate
Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond
Integrating industry 4.0 for enhanced sustainability: Pathways and prospects
Integrated Sensing and Communications: Toward Dual-Functional Wireless Networks for 6G and Beyond