TLDR: National Taiwan University of Science and Technology (NTUST) secured five awards at the 2025 Future Tech Award, recognizing its advancements in artificial intelligence, net-zero technology, and humanistic technology. Key innovations include electrochemical methane separation technology for hydrogen production and a sparse neural network accelerator for energy-efficient satellite and drone operations.
National Taiwan University of Science and Technology (NTUST) has achieved significant recognition at the prestigious 2025 Future Tech Award, clinching a total of five accolades. The university announced its success on Monday, October 13, highlighting its contributions across various technological domains.
The 2025 Future Tech Award, organized by a consortium of leading Taiwanese institutions including the National Science and Technology Council, Academia Sinica, the Ministry of Education, and the Ministry of Health and Welfare, is a highly competitive event. This year, it attracted over 500 entries from across the nation, with only 83 key technologies selected for awards. NTUST’s victories spanned artificial intelligence, net-zero technology, and humanistic technology divisions.
Professor Chen-Hao Wang led a team that developed an electrochemical methane separation technology. This innovation is designed for hydrogen production and renewable energy applications, characterized by its low-energy consumption, cost-effectiveness, and modular design.
Professor Pei-Jun Lee from the Department of Electronics spearheaded the creation of a sparse neural network accelerator. This technology significantly enhances energy efficiency for low Earth orbit satellites and drones, boasting a 43.2% improvement compared to existing architectures.
Professor Lee’s team also developed an edge intelligence computing platform. This platform utilizes a two-stage model compression technique to enable advanced capabilities such as cloud removal, farmland segmentation, and disaster monitoring. Its applications are diverse, serving smart agriculture, defense surveillance, environmental detection, and disaster warning systems.
Professor Chen-Hao Wang’s team was specifically noted for their electrochemical methane separation technology. Professor Pei-Jun Lee’s work on the sparse neural network accelerator and the edge intelligence computing platform underscores the university’s commitment to cutting-edge AI research.
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The Future Tech Award aims to promote innovative AI applications in smart cities, healthcare, education, and entertainment, emphasizing interdisciplinary collaboration and the integration of technology with culture. Winners receive a million New Taiwan Dollars in prize money and corporate technical support, with the goal of creating human-centered living laboratories.
