ClusterTech welcomed students and faculty from The Chinese University of Hong Kong's (CUHK) Earth and Environmental Sciences (EES) Department on July 24, 2025, as part of their Academic Leadership Camp programme. The visit provided students with valuable insights into industry applications of environmental technology.
ClusterTech presented cutting-edge atmospheric modeling research at the workshop "Navigating the Turbulence Grey Zone in Numerical Weather Prediction" organized by the University of Exeter (Exeter, 23-25 June 2025). Mr. Chris Cheung, Senior Director of Technology, showcased a technical poster titled: "Numerical weather prediction at 200 m local resolution based on the unstructured grid CPAS model" - highlighting unprecedented capabilities of the ClusterTech Platform for Atmospheric Simulation (CPAS).
ClusterTech recently exhibited in the 19th Eco Expo Asia, which opened at AsiaWorld-Expo from October 30 to November 2. This premier event, jointly organised by the Hong Kong Trade Development Council (HKTDC) and Messe Frankfurt (HK) Ltd, gathered over 300 exhibitors from 11 countries and regions, all committed to advancing sustainable practices and technologies. Under the theme of “Fostering Green Innovations for Carbon Neutrality”, Eco Expo Asia 2024 once again brought together leading companies from various green sectors to collaborate on creating a more sustainable future.
As a premier provider of High-Performance Computing (HPC), Artificial Intelligence (AI), analytics, and big data solutions in Hong Kong, ClusterTech was once again invited to exhibit at SmartHK.
ClusterTech, a leading provider of innovative technology solutions, proudly announces its successful participation in the Asia Climate Forum 2024 held in Singapore.
The "LOGTECH Expo 2024", organised by the Transport and Logistics Bureau of HKSAR with the Hong Kong Productivity Council (HKPC) as the Executive Partner, was officially held on 12 -13 June at the Hong Kong Productivity Council (HKPC). The two-day expo brought together over 300 local business leaders, SME representatives, industry partners and logistics technology providers to share the latest technology trends in the industry, and to explore how to make the best use of government subsidies for upgrading and restructuring towards smart and green logistics, and enhancing efficiency and productivity. As a leading innovator in weather-based predictive analytics, ClusterTech demonstrated how its state-of-the-art technology is poised to revolutionise the way mobility and logistics operations are planned and executed.
Marintec China 2023, opened in Shanghai on Tuesday, 5 December, 2023. The exhibition attracted over 2,200 renowned companies from more than 30 countries and regions. ClusterTech Limited, the leading provider of High Performance Computing, exhibited at Marintec China 2023 and showcased the ClusterTech Platform for Atmospheric Simulation (CPAS).
ClusterTech was invited to present at the Worldwide Universities Network (WUN) workshop on the theme of "Investigating Global Warming and Urbanisation Impacts on Megacity Environment: Observations and Multi-scale Modelling." The workshop took place in the campus of the Chinese University of Hong Kong and also online virtually on 1 Dec 2023. The presentation specifically focused on the topic of "Applications of the Multi-scale CPAS Model to Megacities."
ClusterTech was honoured to be invited to the Hong Kong Polytechnic University's (PolyU) lecture to deliver an enlightening speech on its groundbreaking Atmospheric Model - CPAS (ClusterTech Platform for Atmospheric Simulation). The sharing showcased ClusterTech's expertise in atmospheric modelling and highlighted its commitment to driving innovation in the field.
ClusterTech, a leading provider of HPC, AI & analytics, and big data solutions, exhibited at SmartHK and showcased its new and unique variable-resolution global weather model - ClusterTech Atmospheric Simulation Platform (CPAS) and scalable atmospheric environment quality simulation platform – Online Platform for Emission Reduction (OPER).
