Google Singapore Jun 2014 to Sep 2014 MBA Marketing InternEMC CORPORATION Seattle, WA Jan 2014 to Mar 2014 MBA ConsultantTAYLOR NELSEN SOFRES SINGAPORE PTE LTD Singapore 2010 to 2013 Regional Market Research AnalystMARKET PROBE ASIA PACIFIC PTE LTD Singapore 2009 to 2009 Market Research Assistant (Intern)WATSON WYATT CONSULTING
2007 to 2007 Project Assistant (Intern)
Education:
NATIONAL UNIVERSITY OF SINGAPORE Singapore Jul 2010 MBA in Marketing AssociationFUDAN UNIVERSITY Jul 2008 Bachelor of Law in SociologyTHE MICHAEL G. FOSTER SCHOOL OF BUSINESS, UNIVERSITY OF WASHINGTON Seattle, WA Master of Business Administration in Marketing/Marketing Research
Skills:
Google AdWords Certification Advanced Market Research Certificates & Professional Member of United Kingdom Market Research Society Languages: English (fluent oral and written); Chinese (native); Cantonese (intermediate) Proficient with data analysis tools: e.g. Excel, MS Access, SPSS, SQL
Oct 2012 to Dec 2012 Consultant InternINGERSOLL RAND (CHINA) INVESTMENT CO., LTD
Jun 2012 to Sep 2012 Accounting InternKPMG (SGP)
Jan 2012 to Feb 2012 Audit InternPINGAN BANK Shenzhen, CN Aug 2011 to Sep 2011 Law and Compliance Department Intern
Education:
SHANGHAI INTERNATIONAL STUDIES UNIVERSITY Jul 2013 Bachelor of Art in English Language and LiteratureWASHINGTON UNIVERSITY, OLIN BUSINESS SCHOOL St. Louis, MO Master of Accounting
2013 to 2013Beijing Information Technology Center Embedded Engineering Group
Jul 2009 to Jan 2010 project manager to develop a portablePrimary developer 2008 to 2008Beijing E-Dragons Intelligent Network Limited Company
Jul 1997 to Jun 2002 a softwareHui Li
Jul 1994 to May 1997
Education:
College of Computer Science and Technology, Beijing University of Technology 2013 Ph. D. in Computer Application TechnologyActuator of this University-Enterprise 2006 doctoral in researchCollege of Computer Science and Technology Changchun, CN Sep 2001 to Jul 2004 Master of Science in Computer Application TechnologyCollege of Computer Science and Technology, Jinlin University Changchun, CN Sep 1990 to Jul 1994 B.S. in Computer Application TechnologyShouGang Research Institute cooperation
2013 to 2013Beijing Information Technology Center Embedded Engineering Group
Jul 2009 to Jan 2010 project manager to develop a portablePrimary developer 2008 to 2008Beijing E-Dragons Intelligent Network Limited Company
Jul 1997 to Jun 2002Changchun Sitong Electronic Communication Company
Jul 1994 to May 1997
Education:
College of Computer Science and Technology, Beijing University of Technology Sep 2004 to Jun 2009 Ph. D. in Computer Application TechnologyActuator of this University-Enterprise 2006 doctoral in researchCollege of Computer Science and Technology Changchun, CN Sep 2001 to Jul 2004 Master of Science in Computer Application TechnologyCollege of Computer Science and Technology, Jinlin University Changchun, CN Sep 1990 to Jul 1994 B.S. in Computer Application TechnologyShouGang Research Institute cooperation
Mar 2010 to 2000 Manager TraineeWilkes University Development Department Wilkes-Barre, PA Feb 2007 to Apr 2007 Technician PhonathonAmerican Education Center Fuzhou, Fujian Branch
Aug 2006 to Dec 2006 Manager AssistantFuzhou Trust & Investment Co
Feb 2004 to Mar 2004 Computer Technician (Intern)
Education:
Wilkes University Graduate School of Business Wilkes-Barre, PA Jan 2007 to Dec 2009 MBAFujian Agriculture and Forest University Sep 2004 to Jul 2006 Bachelor's in Computer ScienceFuzhou University Sep 2001 to Jul 2004 Associate in majored
Minglei Xu - Bellevue WA, US Avinash Pillai - Redmond WA, US Hui Li - Redmond WA, US Paul Trunley - Bellevue WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 9/44
US Classification:
703 20, 703 22, 714 42
Abstract:
Aspects of the subject matter described herein relate to simulating storage devices. In aspects, a test automation engine instructs a simulator to simulate a storage device having certain characteristics such as a storage area network. The test automation engine then tests an application against the simulated storage device. Tests may include storage management requests and storage access requests. A provider may translate a request to one or more operations suitable to perform the request on the underlying simulated device. Shadow copies and the results of other storage management-related operations may be shared across computers via aspects of a simulation framework described herein.
Tracking File System Namespace Changes During Transactions
Hui Li - Redmond WA, US Sarosh Cyrus Havewala - Kirkland WA, US Neal R Christiansen - Bellevue WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 17/30
US Classification:
707803, 707695
Abstract:
Aspects of the subject matter described herein relate to tracking file system namespace changes during transactions. In aspects, a filter monitors operations that may affect a tracked portion of a transactional file system's namespace. When an operation that affects the tracked portion is received, a data structure is modified to track the changes. Nodes within the data structure are marked to indicate whether they can be seen inside or outside of the transaction. If the transaction commits or rolls back, nodes within the data structure are deleted and made visible as appropriate.
Sarosh Cyrus Havewala - Kirkland WA, US Hui Li - Redmond WA, US Neal R Christiansen - Bellevue WA, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 17/30
US Classification:
707826
Abstract:
Aspects of the subject matter described herein relate enforcing quotas in transactional file systems. In aspects, a filter monitors operations that may affect quota usage/charge of a file system object having a quota allotment. In doing so, the filter determines a quota value outside of any transaction for the object and a quota value associated with at least one transaction affecting the object. The filter receives a request that involves the use of additional quota. The filter then determines whether to allow or fail the request depending on whether enough quota is available to satisfy the request.
Sarosh C. Havewala - Kirkland WA, US Matthew S. Garson - Seattle WA, US Neal R. Christiansen - Bellevue WA, US Hui Li - Malden MA, US
Assignee:
MICROSOFT CORPORATION - Redmond WA
International Classification:
G06F 12/16 G06F 17/30
US Classification:
707203, 707E1701
Abstract:
In accordance with one or more aspects of the application-managed file versioning, a request to store a new version of a file is received from an application, the request having been generated by the application. A filename for the new version of the file is generated, derived from a standardized naming convention. The filename includes a first portion having at least a portion of a name of the file, and a second portion having data indicating that the new version of the file is a version of the file. A set of application programming interfaces (APIs) can be exposed that allow the application to manage file versions, such as creating a new version of a file, identifying one or more versions of the file, listing one or more versions of the file, and deleting one or more versions of the file.
Dosage Forms Of Elinogrel And Methods Of Injectable Administration Thereof
Hui Li - Sammamish WA, US Juan Wang - Foster City CA, US Joe Lambing - Burlingame CA, US Harry Tiemessen - Weil am Rhein, DE
Assignee:
Portola Phamaceuticals Inc. - South San Francisco CA
International Classification:
A61K 9/00
US Classification:
51426624
Abstract:
The present invention is concerned with a liquid delivery form of Elinogrel for the treatment of thrombosis which is notable for its improved dosage properties and stability. The dosage form is a liquid or a lyophilized form which is reconstituted for an injectable formulation comprising: a) at least about 3 mg/ml or up to about 15 mg/ml Elinogrel or a pharmaceutically acceptable salt thereof (post reconstitution or in liquid form), and b) at least one pharmaceutically acceptable excipient. Further aspects of the present invention concern the preparation and use of such a formulation.
Resource-Efficient Identification Of Relevant Topics Based On Aggregated Named-Entity Recognition Information
A topic-processing system processes topics in a set of documents in a two-stage manner. In the first stage, the system recognizes candidate topics in the set of documents using a machine-trained named-entity recognition (NER) model, to produce original NER information. In a second stage, the system aggregates the original NER information over the set of documents, to produce aggregated information. The system then ranks the candidate topics in the set of candidate topics based on the aggregated information using a machine-trained classification model, to produce a set of ranked topics. The system then selects a set of final topics from the set of ranked topics, e.g., by excluding ranked topics having scores below a prescribed threshold value. A production system presents supplemental information regarding selected final topics, where those final topics are identified by the topic-processing system.
Reinforcement Learning Simulation Of Supply Chain Graph
- Redmond WA, US Hui Qing LI - Seattle WA, US Vaishnavi NATTAR RANGANATHAN - Woodinville WA, US Lillian Jane RATLIFF - Seattle WA, US Ranveer CHANDRA - Kirkland WA, US Vishal JAIN - Bengaluru, IN Michael McNab BASSANI - Seattle WA, US Jeremy Randall REYNOLDS - Boulder CO, US
Assignee:
Microsoft Technology Licensing, LLC - Redmond WA
International Classification:
G06K 9/62 G06Q 10/08
Abstract:
A computing system including a processor configured to receive training data including, for each of a plurality of training timesteps, training forecast states associated with respective training-phase agents included in a training supply chain graph. The processor may train a reinforcement learning simulation of the training supply chain graph using the training data via policy gradient reinforcement learning. At each training timestep, the training forecast states may be shared between simulations of the training-phase agents during training. The processor may receive runtime forecast states associated with respective runtime agents included in a runtime supply chain graph. For a runtime agent, at the trained reinforcement learning simulation, the processor may generate a respective runtime action output associated with a corresponding runtime forecast state of the runtime agent based at least in part on the runtime forecast states. The processor may output the runtime action output.
Scaling Distributed Computing System Resources Based On Load And Trend
The described technology is generally directed towards automatically scaling distributed computing resources of a distributed computing system based on a system load measurement and a trend factor indicative of whether the system load is increasing or decreasing. If a computing resource load value is above a resource addition threshold value and the trend factor indicates that the computing resource load is increasing, a corresponding computing resource is added to the distributed computing system. If a computing resource load value is below a resource removal threshold value and the trend factor indicates that the computing resource load is decreasing, a corresponding computing resource is removed from the distributed computing system. The trend factor can be obtained using a moving average convergence divergence (MACD) direction indicator.
Isbn (Books And Publications)
Xian Dai Si Xiang Zheng Zhi Jiao Yu Huan Jing Yan Jiu