Singapore, Singapore

David Lo


Average Co-Inventor Count = 4.0

ph-index = 1

Forward Citations = 3(Granted Patents)


Company Filing History:


Years Active: 2012

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1 patent (USPTO):Explore Patents

Title: David Lo - Innovator in Data Mining Technologies

Introduction

David Lo is a prominent inventor based in Singapore, known for his contributions to the field of data mining. He has developed innovative methods that enhance the efficiency and effectiveness of data analysis. His work is particularly significant in the realm of abstracting events for data mining, which has implications for various industries.

Latest Patents

David Lo holds a patent titled "Abstracting events for data mining." This patent describes a method where an event is represented by a quantified abstraction. The event includes at least one predicate, which has a corresponding constant symbol. An instance of this constant symbol is identified and replaced by a free variable to create an abstracted predicate. The process culminates in a quantified abstraction of the event, which is utilized in a data mining algorithm to determine correlations between events. He has 1 patent to his name.

Career Highlights

David Lo is currently employed at Microsoft Technology Licensing, LLC, where he applies his expertise in data mining technologies. His role involves developing innovative solutions that leverage data for better decision-making processes. His contributions have been instrumental in advancing the capabilities of data analysis tools.

Collaborations

David has collaborated with notable colleagues such as Ganesan Ramalingam and Venkatesh-Prasad Ranganath. These collaborations have fostered a creative environment that encourages the exchange of ideas and the development of cutting-edge technologies.

Conclusion

David Lo is a significant figure in the field of data mining, with a focus on abstracting events to improve data analysis. His innovative patent and collaborations highlight his commitment to advancing technology in this area. His work continues to influence the landscape of data mining and its applications.

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