Wai Keat Tan

Title: Innovations of Wai Keat Tan

Introduction

Wai Keat Tan is a notable inventor based in Vancouver, Canada. He has made significant contributions to the field of machine learning and database management. His work focuses on improving the efficiency of database queries through innovative methods.

Latest Patents

Wai Keat Tan holds a patent for "Automated query predicate selectivity prediction using machine learning models." This invention provides a method, a computer system, and a computer program product for cardinality estimation. The invention involves accessing database relations to collect a random sample from each relation. Training data is generated from this random sample, which is then used to build a cumulative frequency function (CFF) model. The CFF model provides cardinality estimation for outputs of SQL operators. He has 1 patent to his name.

Career Highlights

Wai Keat Tan is currently employed at International Business Machines Corporation, commonly known as IBM. His role involves leveraging his expertise in machine learning to enhance database functionalities. His innovative approach has positioned him as a valuable asset in the tech industry.

Collaborations

Wai Keat Tan has collaborated with several professionals in his field, including Mohamad F Kalil and Calisto Paul Zuzarte. These collaborations have contributed to the advancement of his research and innovations.

Conclusion

Wai Keat Tan is a distinguished inventor whose work in machine learning and database management has led to significant advancements in the field. His patent demonstrates his commitment to improving technology and efficiency in data processing.