Dr. Wu graduated from the Natl Taiwan Univ Coll of Med, Taipei, Taiwan (385 02 Prior 1/71) in 1972. He works in Crystal Lake, IL and specializes in Internal Medicine and Endocrinology, Diabetes & Metabolism. Dr. Wu is affiliated with Advocate Sherman Hospital and Centegra Hospital Mchenry.
Dr. Wu graduated from the Creighton University School of Medicine in 2004. He works in Honolulu, HI and specializes in Pediatric Pulmonology. Dr. Wu is affiliated with Kaiser Permanente Moanalua Medical Center and Kapiolani Medical Center For Women & Children.
Name / Title
Company / Classification
Phones & Addresses
Brian Wu President
Kbba, Inc
230 E Vly Blvd, San Gabriel, CA 91776
Brian Pak Wu President
BW ONE, INC Nonclassifiable Establishments
655 N Broadway, Los Angeles, CA 90012
Brian Wu
Elemental Capital Partners LLC Consulting · Management Consulting · Investor
58 W Portal Ave, San Francisco, CA 94127
Brian Pak Wu
B.I.G. Group, LLC
415 W Vly Blvd, San Gabriel, CA 91776 619 S Sierra Vis Ave, Alhambra, CA 91801
Us Patents
Methods And Systems For Generating Multimedia Content Based On Processed Data With Variable Privacy Concerns
- Hillsborough CA, US Brian Wu - Hillsborough CA, US
Assignee:
GGWP, Inc. - Hillsborough CA
International Classification:
A63F 13/79 G06N 20/00
Abstract:
Methods and systems for cross-platform user profiling based on disparate datasets using machine learning models. Specifically, the system may monitor native asset data of an asset corresponding to a cross-platform profile, wherein the cross-platform profile comprises a profile linked to an account, for a user, that is used across multiple assets. The system may detect, using a machine learning model, an incident of the user based on telemetry data extracted from the native asset data. The system may update a status of the cross-platform profile based on the incident. The system may generate for presentation, in a user interface for the account, the status of cross-platform profile and reconstructed asset data based on the incident.
Inferential Analysis Using Feedback For Extracting And Combining Cyber Risk Information
Inferential analysis includes: assessing risk of a cyber security failure in a computer network of an entity, using a computer agent configured to collect information from at least one accessible Internet elements; automatically determining, based on the assessed risk, a change or a setting to at least one element of policy criteria of a cyber security policy; and automatically recommending, based on the assessed risk, a computer network change to reduce the assessed risk.
Inferential Analysis Using Feedback For Extracting And Combining Cyber Risk Information
- Foster City CA, US Brian Wu - San Francisco CA, US Ming Yang - San Mateo CA, US Paul Yang - San Mateo CA, US Fernando Tancioco - San Ramon CA, US
International Classification:
H04L 29/06 G06N 99/00 G06Q 30/00 G06Q 40/06
Abstract:
Various embodiments of the present technology include methods of assessing risk of a cyber security failure in a computer network of an entity. Some embodiments involve using continual or periodic data collecting to improve inferential analysis, as well as obtaining circumstantial or inferential information from social networks. Machine learning may be used to improve predicitive capabilities. Some embodiments allow for identification of an entity from circumstantial or inferential information based on the machine learning and comparative analyses.
Inferential Analysis Using Feedback For Extracting And Combining Cyber Risk Information
- San Mateo CA, US Brian Wu - San Francisco CA, US Ming Yang - San Mateo CA, US Paul Yang - San Mateo CA, US Fernando Tancioco, JR. - San Ramon CA, US
International Classification:
H04L 29/06 G06Q 30/00 G06N 99/00
Abstract:
Various embodiments of the present technology include methods of assessing risk of a cyber security failure in a computer network of an entity. Some embodiments involve using continual or periodic data collecting to improve inferential analysis, as well as obtaining circumstantial or inferential information from social networks. Machine learning may be used to improve predicitive capabilities. Some embodiments allow for identification of an entity from circumstantial or inferential information based on the machine learning and comparative analyses.