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Xun Li, 56724 Boonewood Ct, San Jose, CA 95120

Xun Li Phones & Addresses

724 Boonewood Ct, San Jose, CA 95120    408-9977652   

6185 Camino Verde Dr, San Jose, CA 95119    408-2274038   

5752 Lilac Blossom Ln, San Jose, CA 95124    408-9783263   

West Lafayette, IN   

Santa Clara, CA   

Work

Position: Craftsman/Blue Collar

Education

Degree: Associate degree or higher

Mentions for Xun Li

Xun Li resumes & CV records

Resumes

Xun Li Photo 36

Coordinator

Location:
Sioux Falls, SD
Work:
Maersk Line
Coordinator
Xun Li Photo 37

Senior Software Engineer

Location:
San Jose, CA
Industry:
Computer Software
Work:
Ibm
Senior Software Engineer
Education:
Purdue University 1997 - 2000
Master of Science, Masters
University of Notre Dame 1995 - 1997
Master of Science, Masters, Civil Engineering
Skills:
Java Enterprise Edition, Shell Scripting, C, Linux, Software Development, Agile Methodologies, Distributed Systems, Java, Unix, Sql, Software Engineering, Xml, Db2, Soa, Websphere, Web Services, Performance Tuning, Mainframe, Ibm Mainframe, Enterprise Architecture, Spring Framework
Xun Li Photo 38

Xun Li

Publications & IP owners

Us Patents

High Performance Predicate Push-Down For Non-Matching Predicate Operands

US Patent:
7299225, Nov 20, 2007
Filed:
Nov 26, 2002
Appl. No.:
10/304220
Inventors:
Brian T. Tran - San Jose CA, US
Hsiuying Y. Cheng - Fremont CA, US
Shuanglin Guo - San Jose CA, US
Patrick M. Malone - Campbell CA, US
Thomas A. Beavin - Milpitas CA, US
Xiazhen Wang - San Jose CA, US
Xun Li - San Jose CA, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 17/30
US Classification:
707 5, 707 2, 707 3, 707 4
Abstract:
A method, apparatus, and article of manufacture for improving the performance of evaluating predicates with non-matching operands by aggressively casting the input value to the data type of the target column before the data of the target column is accessed.

Query Transformation For Masking Data Within Database Objects

US Patent:
2013008, Apr 4, 2013
Filed:
Oct 3, 2011
Appl. No.:
13/251448
Inventors:
Eric L. Alton - Markham, CA
Thomas A. Beavin - Milpitas CA, US
Harley W. Boughton - Mississauga, CA
Yao-Ching S. Chen - Saratoga CA, US
Curt L. Cotner - Gilroy CA, US
Yuping Ding - Markham, CA
Dengfeng Gao - San Jose CA, US
Gerald G. Kiernan - San Jose CA, US
Xun Li - San Jose CA, US
Irene C. Liu - San Jose CA, US
Walid Rjaibi - Markham, CA
Gregory R. Stager - Markham, CA
Joyce A. Taylor - San Jose CA, US
Timothy J. Vincent - Toronto, CA
Liyan Zhou - San Jose CA, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 17/30
US Classification:
707754, 707792, 707E17005, 707E17055
Abstract:
According to one embodiment of the present invention, a system processes a database query, and comprises a computer system including at least one processor. The system identifies one or more expressions within the database query utilizing a database object with value masking. Masking requirements are determined for each identified expression and the database object utilized by that identified expression is replicated to provide masked and actual versions of that database object in response to the masking requirements for that expression including masked values and actual values of that database object. The value masking of the database object is applied to the identified expressions within the database query based on the determined masking requirements to produce search results with masked values for the database query. Embodiments of the present invention further include a method and computer program product for processing a database query in substantially the same manner described above.

Dynamic Device Clustering

US Patent:
2019005, Feb 21, 2019
Filed:
Aug 21, 2017
Appl. No.:
15/682268
Inventors:
- Menlo Park CA, US
Xun Li - Foster City CA, US
Kumar Rangarajan - Cupertino CA, US
Michael McKenzie Magruder - Carnation WA, US
Zheng Mi - Palo Alto CA, US
International Classification:
G06F 11/36
Abstract:
A cluster of devices can be identified where results from executing a test by any cluster devices can be considered as being from the same device. Thus, instead of waiting for a single device to produce comparable results, multiple devices from the same cluster can simultaneously perform the test and obtain the needed set of test results more quickly. The technology can identify clusters of devices that are all similar to a primary cluster device. A device pair can be considered similar when (1) a mean each of a set of test results from each device are within a first threshold of each other, (2) a measurement of the consistency of each test result set are within a second threshold of each other, and (3) a measurement of the consistency of a combination of the test results sets is between the consistency measurements of the individual test result sets.

Isbn (Books And Publications)

Proletarian Power: Shanghai In The Cultural Revolution

Author:
Xun Li
ISBN #:
0813321654

Proletarian Power: Shanghai In The Cultural Revolution

Author:
Xun Li
ISBN #:
0813321662

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