Intel Corporation
Principal Engineer and Venture Lead, New Business Initiatives
Intel Corporation 2009 - 2011
Product Development Manager, Independent Living Platforms, Digital Health Group
Intel Corporation 2005 - 2009
Research Scientist, Manager Health Systems Research Lab, Digital Health Group
Galois, Inc. Jan 2005 - Jul 2005
Cryptol Program Manager
Iovation Inc. Jun 2004 - Jan 2005
Program Manager
Education:
Portland State University
Doctorates, Doctor of Philosophy, Computer Engineering, Philosophy
Rensselaer Polytechnic Institute
Masters, Electrical Engineering, Engineering
Rensselaer Polytechnic Institute
Bachelors, Bachelor of Science, Electrical Engineering
Skills:
Signal Processing Embedded Systems Software Engineering Product Management R&D Software Development Debugging Embedded Software Algorithms Agile Methodologies C System Architecture C++ Engineering Management Software Design Machine Learning Pattern Recognition Digital Signal Processors Testing Computer Architecture Simulations Biomedical Engineering Perl Sensors Linux Technical Leadership Research and Development Disruptive Innovation Wireless Patents Digital Signal Processing Medical Software Disruptive Technologies Wireless Technologies
Us Patents
Very-Large-Scale Automatic Categorizer For Web Content
Daniel P. Lulich - Portland OR Farzin G. Guilak - Beaverton OR
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F 1730
US Classification:
707102, 707 7
Abstract:
A method and apparatus for efficiently classifying and categorizing data objects such as electronic text, graphics, and audio based documents within very-large-scale hierarchical classification trees is provided. In accordance with one embodiment of the invention, a first node of a plurality of nodes of a subject hierarchy is selected. Previously classified data objects corresponding to a selected first node of a subject hierarchy as well as any associated sub-nodes of the selected node are aggregated to form a content class of data objects. Similarly, data objects corresponding to sibling nodes of the selected node and any associated sub-nodes of the sibling nodes are then aggregated to form an anti-content class of data objects. Features are then extracted from each of the content class of data objects and the anti-content class of data objects to facilitate characterization of said previously classified data objects.
Method And Apparatus For Automatically Determining Salient Features For Object Classification
Daniel P. Lulich - Portland OR, US Farzin G. Guilak - Beaverton OR, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06N005/02
US Classification:
706 45, 707 1
Abstract:
A method and apparatus for automatically determining salient features for object classification is provided. In accordance with one embodiment, one or more unique features are extracted from a first content group of objects to form a first feature list, and one or more unique features are extracted from a second anti-content group of objects to form a second feature list. A ranked list of features is then created by applying statistical differentiation between unique features of the first feature list and unique features of the second feature list. A set of salient features is then identified from the resulting ranked list of features.
Personal Status Physiologic Monitor System And Architecture And Related Monitoring Methods
James P. Welch - Tigard OR, US Steven D. Baker - Beaverton OR, US Farzin G. Guilak - Beaverton OR, US Anand Sampath - Streamwood IL, US Daniel L. Williams - Norwell MA, US
A system for actively monitoring a patient includes at least one body-worn monitoring device that has at least one sensor capable of measuring at least one physiologic parameter and detecting at least one predetermined event. At least one intermediary device is, linked to the body-worn monitoring device by means of a first wireless network and at least one respondent device is linked to said at least one intermediary device by a second wireless network wherein the respondent device is programmed to perform a specified function automatically when the at least one predetermined event is realized. The monitoring device operates to periodically transmit patient status data to the intermediary device but the system predominantly operates in a quiet state, providing very low power consumption.
Personal Status Physiologic Monitor System And Architecture And Related Monitoring Methods
James P. Welch - Tigard OR, US Steven D. Baker - Beaverton OR, US Farzin G. Guilak - Beaverton OR, US Anand Sampath - Streamwood IL, US Daniel L. Williams - Norwell MA, US
A method for communicating data using at least one network linking at least one respondent device with at least one monitoring device, said method comprising the steps of: continuously measuring at least one physiologic parameter for purposes of detecting a predetermined event using said at least one monitoring device; operating said network in an off state in which said network is off except for the periodic transmission of patient status data while said network is in a first operative state wherein said predetermined event has not occurred and transmitting said measured data along said at least one said network in a second state when said predetermined event has occurred.
Personal Status Physiologic Monitor System And Architecture And Related Monitoring Methods
James P. Welch - Tigard OR, US Steven D. Baker - Beaverton OR, US Farzin G. Guilak - Beaverton OR, US Anand Sampath - Streamwood IL, US Daniel L. Williams - Norwell MA, US
A method for performing context management, said method comprising the steps of: producing a continuous physiologic signal, as detected by a monitoring device; associating at least one unique hardware identifier to said continuous physiologic signal and binding a unique patient identifier to said continuous signal wherein a change in said physiologic signal in which said signal is no longer continuous will cause the unique patient identifier to unbind from said signal.
Self-Improving System And Method For Classifying Pages On The World Wide Web
Farzin Guilak - Beaverton OR, US Daniel Lulich - Portland OR, US Paul Rehfuss - Seattle WA, US
Assignee:
Microsoft Corporation
International Classification:
G06F007/00
US Classification:
707/007000
Abstract:
A self-improving system and method for classifying a plurality of digital documents such as web pages into one or more categories. Textual features and contextual features are extracted from a digital document and submitted to a committee machine. The committee machine assigns a rating to the digital document as a function of the extracted features and provides the location such as a URL for the digital document and its rating to an output data store. The output data store stores a list of locations for the plurality of digital documents. The output data store further segregates the locations of the digital document into categories based on the content of each document as indicated by the assigned rating.
Very-Large-Scale Automatic Categorizer For Web Content
Daniel Lulich - Portland OR, US Farzin Guilak - Beaverton OR, US
Assignee:
Microsoft Corporation - Redmond WA
International Classification:
G06F017/00
US Classification:
707100000
Abstract:
A method and apparatus for efficiently classifying and categorizing data objects such as electronic text, graphics, and audio based documents within very-large-scale hierarchical classification trees is provided. In accordance with one embodiment of the invention, a first node of a plurality of nodes of a subject hierarchy is selected. Previously classified data objects corresponding to a selected first node of a subject hierarchy as well as any associated sub-nodes of the selected node are aggregated to form a content class of data objects. Similarly, data objects corresponding to sibling nodes of the selected node and any associated sub-nodes of the sibling nodes are then aggregated to form an anti-content class of data objects. Features are then extracted from each of the content class of data objects and the anti-content class of data objects to facilitate characterization of said previously classified data objects.
Apparatus For Monitoring Physiological, Activity, And Environmental Data
Margaret Morris - Portland OR, US Terry Dishongh - Portland OR, US Farzin Guilak - Beaverton OR, US
International Classification:
A61B 5/00
US Classification:
600300
Abstract:
The invention relates to an earpiece form factor including technology to monitor physiological, activity and environmental data on a user. The device includes a pulse oximeter unit to provide blood oxygenation level and beat-to-beat timing, a three-axis accelerometer to provide orientation and activity level, and a temperature sensor to provide a subject's skin temperature. The device may also capture other forms of data for the user and the user's surroundings. Captured data are transmitted wirelessly to a mobile phone, PDA or other device that supports wireless transmission, and enables monitoring form another location.