Gladinet Inc since Sep 2008
Testing
Alcatel-Lucent Apr 1999 - Aug 2008
MTS
Lucent Technologies 1999 - 2008
MTS
Education:
University of Alabama 1997 - 1999
MS, Computer Science
China University of Mining and Technology 1993 - 1996
MS, Power Electronics
Xiamen University 1989 - 1993
BS, Computer Science
Bluware, Inc.
Senior Software Developer
Exxonmobil Apr 2018 - Mar 2019
Business Data Science Expert
Omni Ai, Inc. Feb 2017 - Mar 2018
Principal Research Scientist
Giant Gray, Inc. Mar 2016 - Feb 2017
Senior Research Scientist
Behavioral Recognition Systems, Inc. (Brs Labs) Jan 2013 - Mar 2016
Senior Research Scientist
Education:
Colorado State University 2002 - 2006
Doctorates, Doctor of Philosophy, Computer Engineering
Skills:
Machine Learning Linux Natural Language Processing Matlab C++ Algorithms Neural Networks Artificial Intelligence Perl Statistics Parallel Programming Programming Mpi Software Engineering Data Mining Image Processing Computer Vision Digital Image Processing Java Mysql Fortran C Pattern Recognition Signal Processing Distributed Systems Computer Science Latex Cuda/Gpu Lisp Hadoop High Performance Computing Mapreduce Software Development Keras Theano Python Haskell Mxnet Agile Environment Scrum Random Forest Boosting Trees Research Algorithm Design Statistical Modeling Javascript Sql Testing
Joseph R. Cavallaro - Pearland TX Gang Xu - Houston TX
Assignee:
Nokia Telecommunications, Oy
International Classification:
H04B 7216
US Classification:
370342, 375148, 375150
Abstract:
A multistage detector is disclosed that maximizes computation power while minimizing system delay. The differencing multistage detector receives signals from a plurality of users in a cell of a communications system and reduces the effect of multiple access interference to a signal from a desired user caused by interference from other users in the cell. The differencing multistage detector includes a plurality of stages, each stage including an interference canceller for removing intra-cell interference caused by the other users in the cell and producing an estimation output vector, wherein except for a first stage, the estimation output vector of a current stage is based on both a decision of the interference canceller of the current stage and the output from an interference canceller of a previous stage. The estimation output vector of a current stage is produced by combining the output from an interference canceller of a previous stage and the decision of the interference canceller of the current stage. Except for the first stage each interference canceller calculates an estimate of multi-user interference by computing a product of a cross-correlation of the received signals and a difference signal thereby reducing the number of multiplication operations required.
System And Method For Efficient Computation Of Simulated Thermodynamic Property And Phase Equilibrium Characteristics Using Comprehensive Local Property Models
David J. Van Peursem - Irvine CA, US Gang Xu - Corona CA, US
Assignee:
Invensys Systems, Inc. - Foxboro MA
International Classification:
G06F 9/455
US Classification:
703 9, 703 2, 73 2501, 137828
Abstract:
A method of estimating a thermophysical property of a fluid using a local model is disclosed herein. The method includes generating, for use within the local model, a series expansion of thermodynamic equations relating to the thermophysical property and one or more derivatives involving the thermophysical property. The method further includes evaluating, based upon a set of specified values of parameters of the fluid, a first order term of the series expansion and a second order term of the series expansion. The values of the first order term and the second order term are then compared. A value of the thermophysical property is then automatically updated when the values of the first order term and the second order term are found to differ by more than a predefined amount.
Dynamic And Adaptive Radar Tracking Of Storms (Darts)
Chandrasekaran Venkatachalam - Fort Collins CO, US Gang Xu - Houston TX, US Yanting Wang - Aurora CO, US
Assignee:
Colorado State University Research Foundation - Fort Collins CO
International Classification:
G01S 13/95
US Classification:
342 26R, 342 26 D, 342196
Abstract:
Methods and systems for estimating atmospheric conditions are disclosed according to embodiments of the invention. In one embodiment, a method may include receiving reflective atmospheric data and solving a flow equation for motion coefficients using the reflective atmospheric data. Future atmospheric conditions can be estimated using the motion coefficients and the reflective atmospheric data. In another embodiment of the invention, the flow equation is solved in the frequency domain. Various linear regression tools may be used to solve for the coefficients. In another embodiment of the system, a radar system is disclosed that predicts future atmospheric conditions by solving the spectral flow equation.
System And Method For Efficient Computation Of Simulated Thermodynamic Property And Phase Equilibrium Characteristics Using Comprehensive Local Property Models
David J. Van Peursem - Irvine CA, US Gang Xu - Corona CA, US
Assignee:
Invensys Systems, Inc. - Foxboro MA
International Classification:
G06F 9/455
US Classification:
703 9, 73 2501
Abstract:
A method of estimating a thermophysical property of a fluid using a local model is disclosed herein. The method includes generating, for use within the local model, a series expansion of thermodynamic equations relating to the thermophysical property and one or more derivatives involving the thermophysical property. The method further includes evaluating, based upon a set of specified values of parameters of the fluid, a first order term of the series expansion and a second order term of the series expansion. The values of the first order term and the second order term are then compared. A value of the thermophysical property is then automatically updated when the values of the first order term and the second order term are found to differ by more than a predefined amount.
John Eric Eaton - Houston TX, US Wesley Kenneth Cobb - The Woodlands TX, US Ming-Jung Seow - Houston TX, US David Samuel Friedlander - Houston TX, US Gang Xu - Houston TX, US
A long-term memory used to store and retrieve information learned while a video analysis system observes a stream of video frames is disclosed. The long-term memory provides a memory with a capacity that grows in size gracefully, as events are observed over time. Additionally, the long-term memory may encode events, represented by sub-graphs of a neural network. Further, rather than predefining a number of patterns recognized and manipulated by the long-term memory, embodiments of the invention provide a long-term memory where the size of a feature dimension (used to determine the similarity between different observed events) may grow dynamically as necessary, depending on the actual events observed in a sequence of video frames.
Detecting Anomalous Events Using A Long-Term Memory In A Video Analysis System
Techniques are described for detecting anomalous events using a long-term memory in a video analysis system. The long-term memory may be used to store and retrieve information learned while a video analysis system observes a stream of video frames depicting a given scene. Further, the long-term memory may be configured to detect the occurrence of anomalous events, relative to observations of other events that have occurred in the scene over time. A distance measure may used to determine a distance between an active percept (encoding an observed event depicted in the stream of video frames) and a retrieved percept (encoding a memory of previously observed events in the long-term memory). If the distance exceeds a specified threshold, the long-term memory may publish the occurrence of an anomalous event for review by users of the system.
John Eric Eaton - Houston TX, US Wesley Kenneth Cobb - Woodlands TX, US Dennis Gene Urech - Katy TX, US Bobby Ernest Blythe - Houston TX, US David Samuel Friedlander - Houston TX, US Rajkiran Kumar Gottumukkal - Houston TX, US Lon William Risinger - Katy TX, US Kishor Adinath Saitwal - Houston TX, US Ming-Jung Seow - Houston TX, US David Marvin Solum - Houston TX, US Gang Xu - Houston TX, US Tao Yang - Houston TX, US
Assignee:
BEHAVIORAL RECOGNITION SYSTEMS, Inc. - Houston TX
International Classification:
G06K 9/00
US Classification:
382103, 382155, 3405731
Abstract:
Embodiments of the present invention provide a method and a system for analyzing and learning behavior based on an acquired stream of video frames. Objects depicted in the stream are determined based on an analysis of the video frames. Each object may have a corresponding search model used to track an object's motion frame-to-frame. Classes of the objects are determined and semantic representations of the objects are generated. The semantic representations are used to determine objects' behaviors and to learn about behaviors occurring in an environment depicted by the acquired video streams. This way, the system learns rapidly and in real-time normal and abnormal behaviors for any environment by analyzing movements or activities or absence of such in the environment and identifies and predicts abnormal and suspicious behavior based on what has been learned.
Thermodynamic Process Control Based On Pseudo-Density Root For Equation Of State
Gang Xu - Irvine CA, US David Bluck - Yorba Linda CA, US David J. Van Peursem - Irvine CA, US Ian H. Boys - Vista CA, US
Assignee:
Invensys Systems, Inc - Foxboro MA
International Classification:
G06F 9/455
US Classification:
703 12
Abstract:
A system for thermodynamic modeling is provided. The system comprises a computer having a processor, a thermodynamic process simulation application, and a thermodynamic equation of state application. When executed by the processor, the thermodynamic equation of state application determines a density root based on a first and second point of departure from an equation of state and based on a first and a second extrapolation equation. The first departure point satisfies the equation.