Swinburne Sarawak win multiple awards at InTEX23

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Swinburne team at the InTEX23

KUCHING: Researchers from Swinburne University of Technology Sarawak (Swinburne Sarawak) secured an impressive array of awards at the recent Innovation Technology Exposition (InTEX23). 

The event, held at Raia Hotel and Convention Centre here from Aug 23 to 24, serves as an annual platform to promote the research and innovation ecosystem, with this year’s theme centered on “Research and Discovery”.

“A total of 12 teams from Swinburne Sarawak participated in this prestigious event, achieving remarkable success by clinching five gold, six silver, and one bronze,” Swinburne Sarawak said in a press release.

In the statement, Swinburne Sarawak also expressed immense pride in the accomplishments of their staff and Higher Degree by Research (HDR) students at InTEX2023. 

The university attributed these achievements to a longstanding commitment to research excellence, multidisciplinary practice, and education.

One notable gold-awarded innovation was ‘Teach, Innovate, Guide, Experience, Execute, and Reflect (TIGEE-R)’, developed by Dr Jee Teck Weng, director of the Business and Social Innovation Centre. 

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TIGEE-R serves as a catalyst for active engagement, critical thinking, reflection, and practical application in education and training.

“Embracing the TIGEE-R framework enables educators and trainers to design learner-centred journeys that effectively prepare individuals for the demands of the contemporary professional landscape. 

“This initiative fosters a dynamic ecosystem where learners, educators, trainers, and investors collaboratively acquire invaluable skills and knowledge, facilitating holistic growth and development.”

Other gold medal-winning innovations included ‘Dynamic Connectedness Among Clean and Dirty Energies: New Insight from Hydrogen Energy’, led by Dr Yii Kwang Jing; ‘Detection and Identification of Mycobacterium tuberculosis via Computer Vision’, led by Associate Professor Dr Chua Hong Siang; and ‘Edge Computing Solution for Plant Disease Identifications with Deep Learning Models’, led by Dr Tay Fei Siang and Dr Lee Sue Han.

“These achievements reflect Swinburne’s continuous commitment to research and education excellence. 

“Swinburne is dedicated to producing internationally recognised and impactful research with a focus on transforming industries, shaping lives and creating positive change,” the statement added.

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