Dr. Contreras graduated from the University of California, San Francisco School of Medicine in 1982. He works in Walnut Creek, CA and specializes in Orthopaedic Surgery. Dr. Contreras is affiliated with John Muir Medical Center Concord.
Name / Title
Company / Classification
Phones & Addresses
David Contreras
CONTRERAS FARMS, LLC
David Contreras Director of Finance
WOODCREST CHRISTIAN SCHOOL SYSTEM Elementary/Secondary School
18401 Van Buren Blvd, Riverside, CA 92508 18401 Wan Buren Blvd, Riverside, CA 92508
Nov 2009 to Present Outside Sales PersonalWoodcrest Christian School System Riverside, CA Jul 2004 to Nov 2009 Campus AideASR Construction
Aug 2008 to May 2009 Laborer
Education:
California Baptist University Riverside, CA 2003 to 2007 BA in History and Political Science
Skills:
I am a dependable, hard working individual who easily adapts to a changing environment and is trainable. Due to the experience I have in different industries, I have developed a strong character, work ethic and dedication that will benefit a growing and competitive company.
Aug 2011 to 2000 Behavioral InterventionistYucaipa Calimesa Joint Unified School District, Desert Sands Unified School District
Sep 2004 to 2000 Substitute TeacherSan Bernardino Elk's Lodge San Bernardino, CA Apr 1997 to Sep 2004 Bar ManagerFirst Bank of Beverly Hills Beverly Hills, CA Apr 1994 to Jan 1996 Compliance OfficerBroadway Federal Savings & Loan Association Los Angeles, CA 1991 to Apr 1994 Audit Manager / Compliance Officer
Education:
California State University San Bernardino Dec 2002 B.S. in Public AdministrationUniversity of California Riverside Riverside, CA Jun 1978 B.A. in Public Administration
Hope Family Dentistry Chino, CA Aug 2012 to Sep 2012 Dental Assistant (externship)Archibald Dental Practice Ontario, CA Apr 2012 to Apr 2012 Dental AssistantBright Now, Eastvale
Apr 2012 to Apr 2012 Dental Assistant
Education:
American Career College Ontario, CA Jun 2011 to Mar 2012 DiplomaOrange Grove High School Corona, CA
License Records
David Contreras
License #:
108951 - Expired
Category:
Nursing Support
Issued Date:
May 21, 2013
Effective Date:
May 8, 2015
Type:
Nurse Aide
Us Patents
Guided Problem Resolution In Deploying An Application
Brendan C. Bull - Durham NC, US David Contreras - Apex NC, US Robert C. Sizemore - Fuquay-Varina NC, US
Assignee:
International Business Machines Corporation - Armonk NY
International Classification:
G06F 9/44 G06F 9/445
US Classification:
717168, 717175, 717177
Abstract:
Techniques are disclosed for deploying an application. In one embodiment, a packaging tool determines that an error exists in a packaged application. The packaging tool may guide a user in fixing the error by updating the packaging tool and repackaging the application using the updated packaging tool. The packaging tool may guide the user via one or more notifications output for display to the user.
Identifying Semantic Relationships Using Visual Recognition
- Armonk NY, US David Contreras - Willow Spring NC, US Roberto Delima - Apex NC, US Corville O. Allen - Morrisville NC, US
International Classification:
G06F 17/27 G06T 11/20 G06N 20/00
Abstract:
Aspects of the present disclosure relate to identifying semantic relationships. Natural language content is received. A part of speech is determined for respective terms within the natural language content. A semantic type is determined for each of two or more terms within the natural language content. A parse tree representation containing a plurality of nodes is then generated based on the natural language content, each of the plurality of nodes corresponding to at least one term within the natural language content, wherein visual characteristics of respective nodes of the plurality of nodes within the parse tree representation depend on the part of speech and semantic type of the respective terms. A bounding box identifying a semantic relationship is then generated around a set of nodes on the parse tree representation, the set of nodes including the two or more terms.
Relevancy As An Indicator For Determining Document Quality
- Armonk NY, US Andrew R. Freed - Cary NC, US Brien Muschett - Palm Beach Gardens FL, US Krishna Mahajan - Raleigh NC, US David Contreras - Willow Spring NC, US
International Classification:
G06F 17/27 G06F 17/24 G06N 5/02
Abstract:
A method, computer system, and a computer program product for relevancy-based document quality assessment is provided. The present invention may include computing a document quality score based on at least one container relevancy score determined based on at least one domain link to a domain knowledge base.
- Armonk NY, US Roberto Delima - Apex NC, US David Contreras - Willow Spring NC, US Krishna Mahajan - Raleigh NC, US
International Classification:
G06F 17/27 G06F 17/28 G06N 20/00
Abstract:
A method, system, and computer program product include providing a list of triggers, training the natural language processor with the list of triggers, providing to the natural language processor a text including one trigger, selecting nodes in the text to create an original potential span, predicting whether the original potential span includes another trigger, and adjusting, in response to predicting that the original potential span includes another trigger, the original potential span to exclude the another trigger to create a new potential span.
Aspects of the present disclosure relate to identifying spans within unstructured electronic text. Natural language content is received. A part of speech and slot name of each word within the natural language content is identified. A parse tree representation is then generated based on the natural language content, wherein visual characteristics of each node of a plurality of nodes within the parse tree representation depend on the part of speech and slot name of each word. A bounding box identifying a span category is then generated around a set of nodes on the parse tree representation by a machine learning model.
An approach is provided that receives a document and a document type of the document. The document type identifies a document category to which the received document belongs. A set of linguistic metrics are retrieved that correspond to the document type. A quality of the received document is automatically determined based on a set of linguistic features found in the document as compared to the retrieved set of linguistic metrics. The document is then ingested into a corpus that is utilized by a question-answering (QA) system. The ingestion of the document is based on the determined quality.
- Armonk NY, US Roberto Delima - Apex NC, US Chris Mwarabu - Holly Springs NC, US David Contreras - Willow Spring NC, US Kandhan Sekar - Durham NC, US Krishna Mahajan - Raleigh NC, US
International Classification:
G06F 17/27 G06F 17/16
Abstract:
A phrase may be received that includes a plurality of tokens in a natural language format. A plurality of levels relating to dependencies between tokens of the plurality of tokens within the phrase is determined. A matrix structure is generated for the phrase. The matrix structure utilizes a plurality of rows and a plurality of columns to store data of the phrase. The plurality of rows and the plurality of columns each indicate one of an order of tokens of the plurality of tokens or levels of the plurality of levels.
Classifying Text To Determine A Goal Type Used To Select Machine Learning Algorithm Outcomes
- Armonk NY, US David Contreras - Willow Spring NC, US Bob Delima - Apex NC, US Corville O. Allen - Morrisville NC, US
International Classification:
G06N 20/00 G06F 17/27 G06F 16/33
Abstract:
Provided are a computer program product, system, and method for classifying text to determine a goal type used to select machine learning algorithm outcomes. Natural language processing of text is performed to determine features in the text and their relationships. A classifier classifies the text based on the relationships and features to determine a goal type. The determined features and relationships from the text are inputted into a plurality of different machine learning algorithms to generate outcomes. For each of the machine learning algorithms, a determination is made of performance measurements resulting from the machine learning algorithms generating the outcomes. A determination is made of at least one machine learning algorithm having performance measurements that are highly correlated to the determined goal type. An outcome is determined from at least one of the outcomes.
News
Austin couple hopes to give back to health care community during COVID-19 pandemic
I know that the families that are struggling today in those very similar wayswere resilient and the fact that we can come in with the hope, from experience, we can share that hope with the community, said David Contreras to KXAN photojournalist Frank Martinez.
My name is David, my friends call me Dee, i...am... really really hungry, im cool like a penguin...in a tuxedo, so hook me up with my grilled stuffed burrito.
David Contreras
Education:
Universidad Cooperativa de Colombia - Ingenieria de sistemas