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Di You

from Palatine, IL
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Connected to:
Boo C You, 105Chanda You, 34Chul J You, 48Colleen A You, 65Gao D You, 85Guofang You, 61Jennifer B You, 46Jimmie You, 36Johnson F You, 61Ju U You, 50

Di You Phones & Addresses

  • Palatine, IL
  • Grayslake, IL
  • Columbus, OH
  • Dublin, OH
  • Princeton, OH

Work

Company: Computational biology and cognitive science lab Sep 2007 Position: Research associate

Education

School / High School: The Ohio State University- Columbus, OH Jan 2007 Specialities: PhD in Electrical and Computer Engineering

Skills

Machine learning • pattern recognition • computer vision • statistical approaches

Awards

- People's Scholarship, HIT, 2003 – 2007 • - Outstanding Student, HIT, 2003 - 2007 • - ZyXEL Scholarship, 2005

Industries

Computer Software

Resumes

Resumes

Di You Photo 1

Data Mining Researcher At Motorola Mobility

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Position:
Senior Staff Research Engineer at Motorola Mobility
Location:
Greater Chicago Area
Industry:
Computer Software
Work:
Motorola Mobility since Jan 2012
Senior Staff Research Engineer
The Ohio State University Sep 2007 - Dec 2011
Research Associate
Harbin Institute of Technology - Harbin, China Sep 2005 - Jul 2007
Research Assistant
Education:
The Ohio State University 2007 - 2011
PhD, Machine Learning, Computer Vision The Ohio State University 2007 - 2010
MS, Machine Learning, Computer Vision Harbin Institute of Technology 2003 - 2007
BS, Electrical Engineering
Honor & Awards:
- People's Scholarship, HIT, 2003 – 2007 - Outstanding Student, HIT, 2003 - 2007 - ZyXEL Scholarship, 2005
Di You Photo 2

Di You Columbus, OH

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Work:
Computational Biology and Cognitive Science Lab

Sep 2007 to 2000
Research Associate
The Ohio State University
Columbus, OH
Sep 2008 to Dec 2010
Teaching Associate
Dept. of EE, Harbin Institute of Technology

Jun 2006 to Jul 2007
Research Assistant
Dept. of EE, Harbin Institute of Technology

Jun 2006 to Jul 2006
Intern
Education:
The Ohio State University
Columbus, OH
Jan 2007 to Jan 2011
PhD in Electrical and Computer Engineering
The Ohio State University
Columbus, OH
Jan 2007 to Jan 2010
M.S. in Electrical and Computer Engineering
Harbin Institute of Technology
Harbin, China
Jan 2003 to Jan 2007
B.S. in Electrical Engineering
Skills:
Machine learning, pattern recognition, computer vision, statistical approaches

Publications

Wikipedia References

Di You Photo 3

Di You

About:
Born:

26 November 1983 • Baoding , Hebei ,China

Work:
Position:

Manager

Skills & Activities:
Sport:

Chinese football player • Bayi Football Team player • Wuhan Guanggu player • Jiangsu Sainty player • Pudong Zobon player • Football • Club

Skill:

Professional

Di You Photo 4

Di You

Us Patents

Drawing An Inference Using Multiple Sensors

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US Patent:
20150317565, Nov 5, 2015
Filed:
Jul 23, 2014
Appl. No.:
14/338622
Inventors:
- Chicago IL, US
Paul C. Davis - Arlington Heights IL, US
James A. Rumpler - Chicago IL, US
Di You - Palatine IL, US
International Classification:
G06N 5/04
G06N 5/02
Abstract:
Disclosed are techniques () and apparatuses () for drawing an inference using multiple sensors. These techniques and apparatuses enable a computing device to choose () a set of sensors that are capable of providing information for an inference, invoke () the chosen set of sensors to provide the information, receive () the information from at least a subset of the chosen sensors, and draw (), based on the received information, the inference. In some cases, the set of sensors are chosen such that time or resources of the computing device can be conserved.

Context Demographic Determination System

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US Patent:
20140280138, Sep 18, 2014
Filed:
Mar 13, 2013
Appl. No.:
13/798391
Inventors:
- Horsham PA, US
Mir F. Ali - Rolling Meadows IL, US
Paul C. Davis - Arlington Heights IL, US
Dale W. Russell - Palatine IL, US
Di You - Grayslake IL, US
Assignee:
GENERAL INSTRUMENT CORPORATION - Horsham PA
International Classification:
G06F 17/30
US Classification:
707737
Abstract:
Systems, methods, and devices for determining contexts and determining associated demographic profiles using information received from multiple demographic sensor enabled electronic devices, are disclosed. Contexts can be defined by a description of spatial and/or temporal components. Such contexts can be arbitrarily defined using semantically meaningful and absolute descriptions of time and location. Demographic sensor data is associated with or includes context data that describes the circumstances under which the data was determined. The demographic sensor data can include demographic sensor readings that are implicit indications of a demographic for the context. The sensor data can also include user reported data with explicit descriptions of a demographic for the context. The demographic sensor data can be filtered by context data according a selected context. The filtered sensor data can then be analyzed to determine a demographic profile for the context that can be output to one or more users or entities.

Context Emotion Determination System

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US Patent:
20140280529, Sep 18, 2014
Filed:
Mar 13, 2013
Appl. No.:
13/798367
Inventors:
- Horsham PA, US
Mir F. Ali - Rolling Meadows IL, US
Jianguo Li - Chicago IL, US
Dale W. Russell - Palatine IL, US
Di You - Grayslake IL, US
Assignee:
General Instrument Corporation - Horsham PA
International Classification:
H04L 29/08
US Classification:
709204
Abstract:
Systems, methods, and devices for determining contexts and determining associated emotion profiles using information received from multiple emotion sensor enabled electronic devices, are disclosed. Contexts can be defined by a description of spatial and/or temporal components. Such contexts can be arbitrarily defined using semantically meaningful and absolute descriptions of times and locations. Emotion sensor data is associated with or includes context data that describes the circumstances under which the data was determined. The emotion sensor data can include emotion sensor readings that are implicit indications of an emotion for the context. The sensor data can also include user reported data with explicit descriptors of an emotion for the context. The emotion sensor data can be filtered by context data according a selected context. The filtered sensor data can then be analyzed to determine an emotion profile for the context that can be output to one or more users or entities.

Displaying A Statistically Significant Relation

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US Patent:
20140200906, Jul 17, 2014
Filed:
Jan 15, 2013
Appl. No.:
13/741616
Inventors:
- Libertyville IL, US
Paul C. Davis - Arlington Heights IL, US
Jianguo Li - Chicago IL, US
Di You - Grayslake IL, US
Assignee:
MOTOROLA MOBILITY LLC - Libertyville IL
International Classification:
G06F 19/00
G06Q 50/22
US Classification:
705 2
Abstract:
The present disclosure teaches techniques for aggregating observations across multiple sensor-data streams and for presenting the results to users in meaningful ways. Available data are analyzed using a variety of statistical techniques. Significant correlations are presented to users to help them to identify any underlying informative patterns. The presented results help people gain insight into their habits as those habits affect their health and wellness. Users can then make informed decisions about their health, wellness, and environment.

System And Method For Activity Recognition

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US Patent:
20140161322, Jun 12, 2014
Filed:
Dec 20, 2012
Appl. No.:
13/723141
Inventors:
- Horsham PA, US
- Pittsburg PA, US
Jianguo Li - Chicago IL, US
Di You - Grayslake IL, US
Assignee:
CARNEGIE MELLON UNIVERSITY - Pittsburgh PA
GENERAL INSTRUMENT CORPORATION - Horsham PA
International Classification:
G06T 7/20
US Classification:
382107
Abstract:
A method for automatic recognition of human activity is provided and includes the steps of decomposing human activity into a plurality of fundamental component attributes needed to perform an activity and defining ontologies of fundamental component attributes from the plurality of the fundamental component attributes identified during the decomposing step for each of a plurality of different targeted activities. The method also includes the steps of converting a data stream captured during a performance of an activity performed by a human into a sequence of fundamental component attributes and classifying the performed activity as one of the plurality of different targeted activities based on a closest match of the sequence of fundamental component attributes obtained during the converting step to at least a part of one of the ontologies of fundamental component attributes defined during the defining step. A system for performing the method is also disclosed.
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