Healthfirst
Senior Technical Development Analyst  Enterprise Delivery  Data Analytics and Insights
J.p. Morgan Sep 2011 - Oct 2015
Senior Associate and Manager  Prime Brokerage  Sas Analytics and Reporting
Deutsche Bank Mar 2007 - Dec 2008
Associate  Loan Trading  Accounting and Control
Mar 2007 - Dec 2008
Senior Technical Development Analyst Enterprise Delivery
Skills:
Vba Prime Brokerage Sql Management Financial Reporting Financial Analysis P&L Management P&L Analysis Sas Programming Access Microsoft Excel Data Reconciliation Data Analysis Business Analysis Loans Loan Iq Enterprise Project Management Business Intelligence Data Analytics Kanban Agile Project Management Root Cause Analysis Process Improvement Business Analytics Tableau Python Visio Sas Enterprise Guide Sas Base Version One Excel Pivot Excel Models Excel Dashboards Reverse Engineering G/L Reconciliations Claims Analytics P&L Forecasting Product Control Kpi Dashboards
Interests:
Science and Technology Children Economic Empowerment Health
Hsbc Jan 2017 - Sep 2019
Co-Chair of Nyc Asian Pacific Islander Committee Employee Resource Group
Hsbc Global Banking and Markets Jan 2010 - Jan 2013
Release Project Manager
Jan 2010 - Jan 2013
Vice President
Hsbc Global Banking and Markets Jan 2010 - Apr 2012
Project Manager and Business Consultant - Business Development and Controls Division
Swiss American Securities Apr 2006 - Oct 2008
Institutional Administrator
Education:
Fordham University 2006 - 2009
Master of Business Administration, Masters, Business, Finance
Union College 1998 - 2002
Bachelors, Bachelor of Arts, East Asian Studies
Skills:
Business Analysis Financial Services Project Management Crm Banking Strategic Planning Operations Management Business Process Improvement Equities Business Development Microsoft Office Negotiation Product Management Process Improvement Analysis Management Risk Management Quality Assurance Project Planning Leadership Program Management Change Management Strategy Business Workflows Workflow Management Uat Coordination Release Management Kyc Business Process Mapping Business Process Integration Financial Literacy Training Community Networking Document Drafting Middle Office
Meister Seelig & Fein Llp
Patent Agent
Ostrow Kaufman Dec 2008 - Feb 2014
Technical Advisor and Patent Agent
Dreier Llp Jun 2008 - Dec 2008
Technical Advisor
Uspto Jun 2007 - Jun 2008
Patent Examiner
Brookhaven National Laboratory 2006 - 2007
Collaborative Researcher
Education:
Stony Brook University 2003 - 2007
Bachelor of Engineering, Bachelors, Computer Engineering
Newtown H.s
Jingkun Hu - Nyack NY Kwok Pun Lee - Yorktown Heights NY
Assignee:
Koninklijke Philips Electronics N.V. - Eindhoven
International Classification:
G06F 1730
US Classification:
707102, 707 1
Abstract:
A DICOM-to-XML conversion system is provided that converts the DICOM SR standard into a set of XML DTDs and Schemas. By providing a mapping between the DICOM SR standard and XML DTDs and Schemas, DICOM specific XML-based applications can be developed, via a larger field of XML-fluent application developers. Additionally, by providing standard XML DTDs and Schemas for containing DICOM data, other commonly available non-DICOM-related applications, such as accounting and mailing programs, can be structured to use information as required from DICOM reports that are converted to conform to these defined XML DTDs and Schemas. In a preferred embodiment, a two-phase conversion is employed. The DICOM SR specification is parsed and converted directly into a set of ârawâ XML documents. Thereafter, the ârawâ XML documents are transformed into the corresponding XML DTDs and Schemas, via an XSLT processor. Changes to the desired XML DTDs and Schemas, as standards develop, can thus be effected via changes in the corresponding XSLT stylesheets, without modification to the DICOM-to-raw-XML process.
The invention relates to a method of providing DICOM SR constraints within an XML document. An XML document is created containing DICOM SR constraints using declarative language. The document can then be accessed and displayed if desired.
Adaptive Sampling Technique For Selecting Negative Examples For Artificial Intelligence Applications
Artificial intelligence applications require use of training sets containing positive and negative examples. Negative examples are chosen using distributions of positive examples with respect to a dominant feature in feature space. Negative examples should share or approximately share, with the positive examples, values of a dominant feature in feature space. This type of training set is illustrated with respect to content recommenders, especially recommenders for television shows.
Kwok Pun Lee - Flushing NY, US Jingkun Hu - Nyack NY, US
Assignee:
Koninklijke Philips Electronics N.V. - Eindhoven
International Classification:
G06F 15/00
US Classification:
715523, 715513, 715530
Abstract:
A conversion system converts DICOM SR information from a DICOM-formatted file into an XML representation. By providing a mapping between DICOM SR and XML, the DICOM SR content material can be more easily processed by application programs that are DICOM-specific, such as medical analysis programs, as well as by application programs that are not DICOM-specific, such as routine clerical or data-management programs. In a preferred embodiment, a two-phase conversion is employed. The DICOM information is parsed and Fig converted directly into a “raw” XML data set. Thereafter, the “raw” XML is transformed into a proper XML output form, via an XSLT processor. Changes to the desired XML output form can thus be effected via changes in the corresponding XSLT stylesheets.
False Positive Reduction In Computer-Assisted Detection (Cad) With New 3D Features
Lilla Boroczky - Mount Kisco NY, US Kwok Pun Lee - Flushing NY, US Luyin Zhao - White Plains NY, US
Assignee:
Koninklijke Philips Electronics, N.V. - Eindhoven
International Classification:
G06K 9/00 G01N 23/04
US Classification:
382159, 382224, 378 62
Abstract:
A method for computer aided detection (CAD) and classification of regions of interest detected within HRCT medical image data includes post-CAD machine learning techniques applied to maximize specificity and sensitivity of identification of a region/volume as being a nodule or non-nodule. The regions are identified by a CAD process, and automatically segmented. A feature pool is identified and extracted from each segmented region, and processed by genetic algorithm to identify an optimal feature subset, which subset is used to train the support vector machine to classify candidate region/volumes found within non-training data.
System And Method For Automated Detection And Segmentation Of Tumor Boundaries Within Medical Imaging Data
Luyin Zhao - White Plains NY, US Kwok Pun Lee - Flushing NY, US
Assignee:
Koninklijke Philips Electronics N.V. - Eindhoven
International Classification:
G06K 9/00
US Classification:
382128, 700182
Abstract:
A method for segmenting regions within a medical image includes evaluating a set of candidate segmentations generated from an initial segmentation. Based on distance calculations for each candidate using derivative segmentations, the best candidate is recommended to clinician if it is better than the initial segmentation. This recommender realizes a most stable segmentation that will benefit follow-up computer aided diagnosis (i. e. classifying lesion to benign/malignant).
Luyin Zhao - Briarcliff Manor NY, US Jin Lu - Croton-on-Hudson NY, US Kwok Lee - Flushing NY, US
Assignee:
Koninklijke Philips Electronics N.V.
International Classification:
G06F015/173 G06F015/16 G06F015/177
US Classification:
709/221000, 709/219000, 709/225000
Abstract:
A method for obtaining service information over the Internet. The method including: at least one service provider registering a service and corresponding service status with a server and storing the same in a database; a user requesting a service from the server; searching the database for the requested service; and informing the user of the results of the search. If the requested service is found in the database, the user is informed of the corresponding service status of the requested service. Similarly, if the requested service is not found in the database, the user is informed of the same. If the requested service is not found in the database, or the service status for the requested service is unavailable, the request is stored and the user is informed when the service becomes registered or the service status is changed to available.
Stratification Method For Overcoming Unbalanced Case Numbers In Computer-Aided Lung Nodule False Positive Reduction
Luyin Zhao - White Plains NY, US Kwok Pun Lee - Flushing NY, US Lilla Boroczky - Mount Kisco NY, US
Assignee:
KONINKLIJKE PHILIPS ELECTRONICS, N.V. - EINDHOVEN
International Classification:
G06K 9/00 G06K 9/62
US Classification:
382128, 382159
Abstract:
A method for computer aided detection (CAD) and classification of regions of interest detected within HRCT medical image data. The method includes post-CAD machine learning techniques applied to maximize specificity and sensitivity of identification of a region/volume as being a nodule or non-nodule. The regions are identified by a CAD process, and automatically segmented. A feature pool is identified and extracted from each segmented region, and processed by genetic algorithm to identify an optimal feature subset, wherein a data stratification method is used to balance the number of cases in different classes. The subset determined by GA is used to train the support vector machine to classify candidate region/volumes found within non-training data.
Medicine Doctors
Dr. Kwok C Lee, Fremont CA - DC (Doctor of Chiropractic)
Kwok Lee (1979-1983), Jonathan Deiss (1978-1980), Marjorie Alexander (1967-1973), Karen Swanson (1966-1972), David Price (1967-1971), Anousheh Sayah (1984-1987)
Lee Kwok (1978-1982), Alvin Goo (1967-1971), Wesley Chung (1972-1976), Andrew Dauz (1969-1973), Roselyn Yagi (1957-1961), Harold Same Aka Leino (1964-1968)