Company Filing History:
Years Active: 2024
Title: Cheuk Ying Tang: Innovator in Machine Learning and Genetic Information Processing
Introduction
Cheuk Ying Tang is a prominent inventor based in Cupertino, CA, known for his contributions to the fields of machine learning and genetic information processing. With a total of 2 patents, he has made significant strides in refining algorithms that enhance the diagnostic relevance of genetic data in cancer research.
Latest Patents
Tang's latest patents include innovative approaches to reducing the dimensionality of genetic information used for machine learning. One of his patents focuses on refining a set of locations that can serve as inputs to machine learning algorithms. These locations may refer to unique molecular positions in a reference human genome and/or unique mutations relevant in diagnosing cancer. The computing system he developed can determine the diagnostic relevance of each location and discard less relevant ones. Another patent introduces a system and method for text-based biological information processing with analysis refinement. This approach further refines an initial set of target locations that can serve as inputs to machine learning mechanisms, addressing issues such as overlapping patterns and insufficient data quality.
Career Highlights
Throughout his career, Cheuk Ying Tang has worked with notable companies such as Mujin, Inc. and Aionco, Inc. His work has been instrumental in advancing the application of machine learning in the medical field, particularly in cancer diagnostics.
Collaborations
Tang has collaborated with talented individuals in his field, including Gene Lee and Edmund Wong. These partnerships have contributed to the development of innovative solutions in genetic information processing.
Conclusion
Cheuk Ying Tang's work exemplifies the intersection of technology and healthcare, showcasing how innovations in machine learning can lead to significant advancements in cancer diagnosis. His contributions continue to influence the field and inspire future research.