8 May 2023
Workshop
HKUST Big Data Institute Workshop on Big Data and Biomedical & Chemical Science
Jointly organized by the HKUST Big Data Institute and Division of Life Science, the workshop aims to discuss the most advanced progress in the area of adapting AI & Data techniques in Biomedicine and Biochemistry.
8 May 2023
Seminar, Lecture, Talk
Physics Department - Towards Quantum-enhanced Sensing and Imaging
8 May 2023
Seminar, Lecture, Talk
Physics Department - Nonreciprocal Interactions - Drops of Activeliquids and Arrested Coarsening
5 May 2023
Seminar, Lecture, Talk
Department of Mathematics - Seminar on Statistics - Embedded Model problems with applications to modelling environmental extremes
Modelling Hydrological extremes is an important issue in hydrology and water resources research. In Statistics, there are two types of extreme value theory.
5 May 2023
Seminar, Lecture, Talk
Department of Mathematics - Seminar on Statistics - Big data challenges in hydro-climate-Agriculture research
Big data has been becoming a popular and hot research topic in many research fields and has attracted many industrial investments.
5 May 2023
Seminar, Lecture, Talk
OCES Departmental Seminar: Mechanistic dissection of alga recognition and uptake in coral-algal endosymbiosis
Corals form an endosymbiotic relationship with the dinoflagellate algae Symbiodiniaceae, but ocean warming can trigger alga loss, coral bleaching and death, and the degradation of ecosystems. Mitigation of coral death requires a mechanistic understanding of coral-algal endosymbiosis.
5 May 2023
Seminar, Lecture, Talk
Department of Mathematics - Seminar on PDE - Leapfrogging for Euler equations
We consider the Euler equations for incompressible fluids in 3-dimension. A classical question that goes back to Helmholtz is to describe the evolution of vorticities with a high concentration around a curve.
5 May 2023
Seminar, Lecture, Talk
Department of Mathematics - Scientific Computation Concentration Seminar - A closure model for computational fluid dynamics accurate across multiple flow regimes