Taipei, Taiwan

Ming-Wei Chang

This inventor holds 1 USPTO granted patent. Top assignee: Synaptics Corporation. Active years: 2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Ming-Wei Chang. Retrieved from https://idiyas.com/inventor/ming-wei-chang-x6h3law2

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

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Company Filing History:


Years Active: 2026

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1 patent (USPTO):Explore Patents

Title: The Innovations of Ming-Wei Chang

Introduction

Ming-Wei Chang is a notable inventor based in Taipei, Taiwan. He has made significant contributions to the field of touch data classification. His innovative work has led to the development of a unique system that enhances user interaction with touch devices.

Latest Patents

Ming-Wei Chang holds a patent for "Adaptive accidental contact mitigation for touch data classification." This patent describes a system that includes a plurality of sensing elements and a processing system. The processing system is designed to receive touch data from a current user through the sensing elements. It determines a first set of classifier parameters based on the user's usage data, which includes the touch data. Subsequently, it applies these parameters to classify future touch data.

Career Highlights

Ming-Wei Chang is currently employed at Synaptics Corporation, where he continues to innovate in the field of touch technology. His work focuses on improving the accuracy and efficiency of touch data classification systems.

Collaborations

Ming-Wei collaborates with Mohamed Sheik-Nainar, contributing to advancements in their shared field of expertise.

Conclusion

Ming-Wei Chang's contributions to touch data classification demonstrate his innovative spirit and commitment to enhancing user experience. His patent reflects the potential for improved technology in everyday devices.

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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