AI innovation at UBC Okanagan helps shipping ports see what’s coming—literally
Peer-Reviewed Publication
This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 15-Dec-2025 20:11 ET (16-Dec-2025 01:11 GMT/UTC)
A UBC Okanagan research team has developed an innovative artificial intelligence system that can accurately predict where ships are heading and arriving, potentially helping Canadian ports better prepare for incoming vessels and respond more efficiently to global supply chain disruptions.
Dr. Zheng Liu, a Professor with UBCO’s School of Engineering, and doctoral student Chengkai Zhang have created TrajReducer, a framework that increases prediction accuracy and computational efficiency by analyzing ship trajectories through advanced spatial clustering and cross-dimensional metadata ranking.
International tech community to assess 20 years of using digital technologies for progress and chart future direction ahead of UN General Assembly review
A study published in PeerJ Computer Science reveals significant accuracy-bias trade-offs in artificial intelligence text detection tools that could disproportionately impact non-native English speakers and certain academic disciplines in scholarly publishing.
In the latest issue of Engineering, researchers from Donghua University and the University of British Columbia present a new design methodology for 3D rotary braiding machines. This innovative approach, based on an average cutting circle strategy, allows for the creation of complex geometric textile composites with enhanced flexibility and precision. The study details how varying the number of incisions on horn gears and combining different cut-circles can significantly expand the capabilities of 3D braiding technology. The findings offer a practical solution for producing intricate 3D braided structures, with potential applications in aerospace, automotive, medical, and emerging fields like nanogenerators and sensors.
Even the smartest machines can’t match young minds at language learning. Researchers share new findings on how children stay ahead of AI - and why it matters.
If a human learned language at the same rate as ChatGPT, it would take them 92,000 years. While machines can crunch massive datasets at lightning speed, when it comes to acquiring natural language, children leave artificial intelligence in the dust.
A newly published framework in Trends in Cognitive Sciences by Professor Caroline Rowland of the Max Planck Institute for Psycholinguistics, in collaboration with colleagues at the ESRC LuCiD Centre in the UK, presents a novel framework to explain how children achieve this remarkable feat.