SEA

ITRI MMSL 2026 Next-Generation Intelligent Mobility & Manufacturing Online Forum (SEA)

About the Forum

ITRI MMSL 2026 Next-Generation Intelligent Mobility & Manufacturing Online Forum will explore how digitalization, automation, and AI-powered human–robot collaboration are accelerating the transition from Industry 4.0 to Industry 5.0 across Southeast Asia’s manufacturing sector.

Why Join

We welcome everyone to join us and discover the latest innovations driving industrial transformation. Explore the technologies shaping smarter manufacturing, advanced mobility, and intelligent electronics for a more connected and sustainable future!

agenda

About the Speakers

Bing-Shiang Yang

Received Ph.D. in Mechanical Engineering from the University of Michigan–Ann Arbor.
Expertise includes robotics, electromechanical integration, smart manufacturing, and medical technology innovation.
Recognized as ASME Fellow (2026); received the IEET Outstanding Teaching Award (2019), the Marquis Who's Who Lifetime Achievement Award (2017), and 3rd Place in the Stanford Design Challenge (2016).

Jyun-Kai Ciou

Received M.S. degree in Mechanical Engineering from National Taiwan University.
Expertise includes polymer molding technologies, flexible electronics, and electric vehicle powertrain development.
Recipient of the Chi Mei Award, HIWIN Thesis Award, and multiple ITRI awards including Outstanding Research, Service Promotion, Excellent Publication, and Quality Excellence.

Chun-Chieh Wang

Received Ph.D. in Mechanical Engineering from Chung Yuan Christian University.
Expertise includes smart manufacturing, PHM, artificial intelligence, and intelligent mechatronic systems.
Diagnostic technologies have been adopted across multiple industries, and his team has served more than 100 companies.

Pei-Ning Wang

Holds a Master’s degree in Mechanical Engineering from National Chung Hsing University.
Specializes in system integration and AI-driven manufacturing applications, including IIoT, digital management, AI, and Generative AI solutions.
Advances predictive maintenance, anomaly monitoring, and intelligent production assistants to enable data-driven smart manufacturing.