Computer Science System

Zhong Zhang

Phone: 817-***-**** Email: *****.*****@****.***.***

LinkedIn: www.linkedin.com/in/zhong.zhang

Homepage: http://vlm1.uta.edu/~zhangzhong/

Career Objective:

Looking for an internship and full-time position as a software developer/engineer.

Summary:

7 published papers in journals and conferences.

Three years in the Ph.D. program, doing research in gesture and action recognition, hand detection and

machine learning.

Excellent programming skills in C++, C, Java and Matlab.

Strong background in machine learning, including Adaboost, SVM, Hidden Markov Model, Bayesian

Network, Conditional Random Field etc.

Strong background in computer vision, including SIFT, Canny edge, LBP descriptor, HOG descriptor

etc.

Education/Academic Background:

University of Texas at Arlington, USA: 2009-2013 (expected)

Ph.D. in Computer Science, GPA: 3.89/4.0

Wuhan University, China 2007-2009

Masters in Computer Science, GPA: 3.5/4.0

Chongqing University, China 2003-2007

Bachelors in Computer Science, GPA: 78/100

Technical Skills:

Programming Languages C, C++, Matlab, Java, C#, Python

Tools Visual Studio, Matlab, Cygwin

SDK OpenCV, MS Kinect SDK, OpenNI

Database MySQL

Web Development: HTML

Publications:

Zhong Zhang, Weihua Liu, Vangelis Metsis, and Vassilis Athitsos. Fall Detection Using a Single Depth

Camera and Automatic External Calibration. (journal paper, in preparation)

Zhong Zhang, Weihua Liu, Vangelis Metsis, and Vassilis Athitsos. A Viewpoint-Independent Statistical

Method for Fall Detection. ICPR 2012, November 2012.

Zhong Zhang, Rommel Alonzo, Vassilis Athitsos. Experiments with computer vision methods for hand

detection. Conference on Pervasive Technologies Related to Assistive Environments (PETRA), May 2011.

Jianhui Zhao, Zhong Zhang, Shizhong Han, Chengzhang Qu, Zhi-Yong Yuan, Dengyi Zhang. SVM based

forest fire detection using static and dynamic features. Computer Science and Information Systems, Vol.

8, No. 3, 821-841. (2011)

Zhong Zhang, Eric Becker, Roman Arora, Vassilis Athitsos. Experiments with computer vision methods

for fall detection. Conference on Pervasive Technologies Related to Assistive Environments (PETRA), June

2010.

Dengyi Zhang, Chengzhang Qu, Jianhui Zhao, Zhong Zhang, Youwang Ke, Shizhong Han, Mingqi Qiao,

Huiyun Zhang, Extraction and Parameterization of Eye Contour from Monkey Face in Monocular

Image, Lecture Notes in Electrical Engineering, Vol. 56, 2009, Page(s): 182-189

Zhong Zhang, Jianhui Zhao, Dengyi Zhang, Chengzhang Qu, Youwang Ke, Bo Cai. Contour Based

Forest Fire Detection Using FFT and Wavelet. CSSE(1) 2008:760-763.

Dengyi Zhang, Shizhong Han, Jianhui Zhao, Zhong Zhang, Chengzhang Qu, Youwang Ke, Xiang Chen:

Image Based Forest Fire Detection Using Dynamic Characteristics with Artificial Neural Networks:

JCAI2009:290-293.

Research Projects:

American Sign Language (ASL) Dictionary Search Project (NSF Funding):

Designed and implemented a system that lets users search dictionaries of ASL that would help look up the

meaning of unknown signs. The system uses several algorithms for feature extraction, dynamic space time

warping, large-scale multiclass recognition and classification. The system GUI supports video segmentation,

annotation and analysis for video data preprocessing.

Hand Detection System (NFS Funding):

Designed and implemented a system that localizes hands in videos automatically for gesture and sign language

recognition. The system uses several algorithms for feature extraction including temporal motion, skin color,

gradient norms and motion residue. The system GUI supports annotation and analysis for video data

preprocessing.

Fall Detection System (NSF Funding):

Designed and implemented a system that detects human falls in videos automatically. A natural application of

such a system is in home monitoring of patients and elderly persons. The system uses several algorithms for

feature extraction and calibration. And a native Bayesian classifier is employed to classify falls and non-falls.

Face Detection System:

Designed and implemented face detection system using rectangle features and AdaBoost learning algorithm

which can be used in conjunction with many other learning algorithms to improve their performance.

Forest Fire Detection System:

Designed and implemented a fire monitoring system that can help prevent forest fire effectively by detecting

fire in videos. 11 static and 12 dynamic features feed to a classifier trained by SVM algorithm to classify

whether there is fire or not in the current frame of a video. The core algorithm is 10,000 lines c++ code.

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