People Background Check
Find People:

Shi Zhong, Age 56Dublin, CA

Get Report
Known as:
Zhong Shi
Related to:
Hongying Shi 55 Minsik Sik Cho 47 Jinwei Shi 42

Shi Zhong Phones & Addresses

Dublin, CA

Fremont, CA

Austin, TX

Troy, NY

Ann Arbor, MI

Stockton, CA

Mentions for Shi Zhong

Resumes & CV records

Resumes

Shi Zhong Photo 12

Chief Scientist At Adometry

Position:
Chief Scientist at Adometry
Location:
Austin, Texas Area
Industry:
Internet
Work:
Adometry - Austin, Texas Area since Oct 2011
Chief Scientist Adometry (formerly Click Forensics) - Austin, Texas Area Jul 2010 - Oct 2011
Director of Research Adometry (formerly Click Forensics) - Austin, Texas Area Nov 2009 - Jul 2010
Principal Scientist Zilliant - Austin, Texas Area Nov 2007 - Oct 2009
Senior Pricing Scientist Yahoo! Inc. - Sunnyvale, CA Dec 2005 - Nov 2007
Senior Data Mining Research Scientist Florida Atlantic University - Boca Raton, FL Aug 2003 - Dec 2005
Assistant Professor IBM - Austin, Texas Apr 2003 - Jul 2003
Summer Intern
Education:
The University of Texas at Austin 1999 - 2003
PhD, Computer Engineering University of Minnesota-Twin Cities 1997 - 1999
PhD Candidate, Computer Engineering Tsinghua University 1994 - 1997
MSEE, Signal and Image Processing Huazhong University of Science and Technology 1990 - 1994
BSEE, Information Engineering
Interests:
Data Mining, Machine Learning, Internet Advertising, Ad Targeting, Soccer, Go chess, Movies
Honor & Awards:
US Patent 8, 374, 906 "Method and system for generating pricing recommendations" February 2013 US Patent 8, 364, 627 "Method and system for generating a linear machine learning model for predicting online user input actions" January 2013 US Patent 7, 921, 069 "Granular data for behavioral targeting using predictive models" April 2011 US Patent 8, 201, 132 "System and method for testing pattern sensitive algorithms for semiconductor design" June 2012 US Patent 7, 685, 544 "Testing pattern sensitive algorithms for semiconductor design" March 2010 US Patent 7, 353, 472 "System and method for testing pattern sensitive algorithms for semiconductor design" April 2008 IBM Faculty Award, 2004. Outstanding Prize (1st place) in China Mathematical Contest in Modeling, 1992.

Publications & IP owners

Us Patents

Testing Pattern Sensitive Algorithms For Semiconductor Design

US Patent:
7685544, Mar 23, 2010
Filed:
Nov 29, 2007
Appl. No.:
11/947254
Inventors:
David L. DeMaris - Austin TX, US
Timothy G. Dunham - South Burlington VT, US
William C. Leipold - Enosburg Falls VT, US
Daniel N. Maynard - Craftsbury Common VT, US
Michael E. Scaman - Goshen NY, US
Shi Zhong - Austin TX, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 17/50
US Classification:
716 4, 716 5, 716 7
Abstract:
A computer program product for generating test patterns for a pattern sensitive algorithm. The program product includes code for extracting feature samples from a layout design; grouping feature samples into clusters; selecting at least one area from the layout design that covers a feature sample from each cluster; and saving each pattern layout covered by the at least one area as test patterns.

Granular Data For Behavioral Targeting Using Predictive Models

US Patent:
7921069, Apr 5, 2011
Filed:
Jun 28, 2007
Appl. No.:
11/770413
Inventors:
John Canny - Berkeley CA, US
Shi Zhong - Santa Clara CA, US
Scott Gaffney - San Francisco CA, US
Chad Brower - Campbell CA, US
Pavel Berkhin - Sunnyvale CA, US
George H. John - Redwood City CA, US
Assignee:
Yahoo! Inc. - Sunnyvale CA
International Classification:
G06F 17/00
G06N 5/02
US Classification:
706 47
Abstract:
A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the pre-processed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive mode. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.

System And Method For Testing Pattern Sensitive Algorithms For Semiconductor Design

US Patent:
8201132, Jun 12, 2012
Filed:
Dec 7, 2009
Appl. No.:
12/631899
Inventors:
David L. DeMaris - Austin TX, US
Timothy G. Dunham - South Burlington VT, US
William C. Leipold - Enosburg Falls VT, US
Daniel N. Maynard - Craftsbury Common VT, US
Michael E. Scaman - Goshen NY, US
Shi Zhong - Austin TX, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 17/50
US Classification:
716136, 716105, 716106
Abstract:
A system and method for generating test patterns for a pattern sensitive algorithm. The method comprises the steps extracting feature samples from a layout design; grouping feature samples into clusters; selecting at least one area from the layout design that covers a feature sample from each cluster; and saving each pattern layout covered by the at least one area as test patterns.

Method And System For Generating A Linear Machine Learning Model For Predicting Online User Input Actions

US Patent:
8364627, Jan 29, 2013
Filed:
Jan 31, 2011
Appl. No.:
13/018303
Inventors:
John Canny - Berkeley CA, US
Shi Zhong - Santa Clara CA, US
Scott Gaffney - San Francisco CA, US
Chad Brower - Campbell CA, US
Pavel Berkhin - Sunnyvale CA, US
George H. John - Redwood City CA, US
Assignee:
Yahoo! Inc. - Sunnyvale CA
International Classification:
G06F 17/00
G06N 5/02
US Classification:
706 47
Abstract:
A method of targeting receives several granular events and preprocesses the received granular events thereby generating preprocessed data to facilitate construction of a model based on the granular events. The method generates a predictive model by using the preprocessed data. The predictive model is for determining a likelihood of a user action. The method trains the predictive model. A system for targeting includes granular events, a preprocessor for receiving the granular events, a model generator, and a model. The preprocessor has one or more modules for at least one of pruning, aggregation, clustering, and/or filtering. The model generator is for constructing a model based on the granular events, and the model is for determining a likelihood of a user action. The system of some embodiments further includes several users, a selector for selecting a particular set of users from among the several users, a trained model, and a scoring module.

Method And System For Generating Pricing Recommendations

US Patent:
8374906, Feb 12, 2013
Filed:
Sep 30, 2008
Appl. No.:
12/241782
Inventors:
Loren Williams - Decatur GA, US
Xingchu Liu - Austin TX, US
Reetabrata Mookherjee - Austin TX, US
Shi Zhong - Austin TX, US
Assignee:
Zilliant Incorporated - Austin TX
International Classification:
G06Q 99/00
US Classification:
705 735, 705 731, 705 10, 705400
Abstract:
To determine pricing recommendations for goods and service products in a business-to-business environment, a set of transaction data corresponding to a set of products are processed to generate a set of pricing recommendations optimized according to an objective. Furthermore, a set of product segments may be determined, transaction data may be associated with one or more of the product segments and a demand model and associated price elasticity may be formulated for one or more of the product segments based upon the transaction data associated with the segment. Using these formulated price elasticities, pricing recommendations for each product may be determined for each of a set of customers. Using an optimization process, price elasticities are used to determine price dependent entity goals for any combination of products, customers and sets of prices, using a mathematical objective function.

System And Method For Testing Pattern Sensitive Algorithms For Semiconductor Design

US Patent:
2007003, Feb 15, 2007
Filed:
Aug 12, 2005
Appl. No.:
11/202591
Inventors:
David DeMaris - Austin TX, US
Timothy Dunham - South Burlington VT, US
William Leipold - Enosburg Falls VT, US
Daniel Maynard - Craftsbury Common VT, US
Michael Scaman - Goshen NY, US
Shi Zhong - Austin TX, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 17/50
US Classification:
716004000, 716005000
Abstract:
A system and method for generating test patterns for a pattern sensitive algorithm. The method comprises the steps extracting feature samples from a layout design; grouping feature samples into clusters; selecting at least one area from the layout design that covers a feature sample from each cluster; and saving each pattern layout covered by the at least one area as test patterns.

Method To Tag Advertiser Campaigns To Enable Segmentation Of Underlying Inventory

US Patent:
2009022, Sep 3, 2009
Filed:
Feb 28, 2008
Appl. No.:
12/039566
Inventors:
Raghav Boinepalli - Santa Clara CA, US
Brad Smallwood - Palo Alto CA, US
Madhu Vudali - Santa Clara CA, US
Shi Zhong - Austin TX, US
Assignee:
Yahoo!, Inc. - Sunnyvale CA
International Classification:
G06Q 10/00
G06Q 30/00
US Classification:
705 10, 705 7, 705 14
Abstract:
A method and system for enabling segmentation of advertising inventory for an advertisement campaign includes capturing a plurality of requirements for an advertisement campaign. The campaign requirements include a descriptive tag that uniquely identifies the advertisement campaign. The requirements include a plurality of campaign attributes that define the requirements of the advertisement campaign including target audience and advertisement campaign objective. A tag inventory, with a plurality of descriptive tags and a plurality of advertisement bookings associated with one or more of the descriptive tags, is analyzed based on the captured advertisement campaign requirements. A recommended suggestion of bookings based on the analysis is presented. The recommended suggestion of bookings matches at least a portion of the campaign attributes. A media plan is finalized for the advertisement campaign based on a response received for the recommended suggestion of bookings, the response defines the relevancy of the recommended suggestion of bookings.

Finding Similar Campaigns For Internet Advertisement Targeting

US Patent:
2010025, Oct 7, 2010
Filed:
Apr 7, 2009
Appl. No.:
12/419923
Inventors:
Jinlin Wang - Mountain View CA, US
Xia Wan - Saratogo CA, US
Weiguo Liu - Dublin CA, US
Shi Zhong - Austin TX, US
International Classification:
G06Q 30/00
G06F 17/30
G06F 17/27
US Classification:
705 10, 704 9, 705 1441, 705 1473
Abstract:
Disclosed are methods and apparatus for analyzing campaigns in order to identify similar campaigns are disclosed. In one embodiment, an ad campaign associated with an advertiser is identified. Ad campaign information associated with ad campaigns previously booked by an online publisher is analyzed to identify one or more of the ad campaigns previously booked by the online publisher that are similar to the ad campaign. The ad campaign information for each of the ad campaigns identifies one or more products of the online publisher. The ad campaign information may be processed by applying natural language processing (NLP) to at least a portion of the ad campaign information associated with the ad campaigns previously booked by the online publisher. At least one of the products of the online publisher to recommend to the advertiser are ascertained from the ad campaign information for the one or more ad campaigns previously booked by the online publisher that are similar to the ad campaign.

Possible Relatives

Dong P Zhong  Elaine Y Zhong  Feng R Zhong  Hairang R Zhong  Hua Zhong  Jin T Zhong  Lin J Zhong  Shi P Sun  Shi Y Tang  Shi Q Wu 

NOTICE: You may not use PeopleBackgroundCheck or the information it provides to make decisions about employment, credit, housing or any other purpose that would require Fair Credit Reporting Act (FCRA) compliance. PeopleBackgroundCheck is not a Consumer Reporting Agency (CRA) as defined by the FCRA and does not provide consumer reports.