陈婧

陈婧    在读博士,出生于1988年,工作在兰州大学UAIS实验室。

电话:15002530620

E-mail: sophic@163.com, chenj12@lzu.edu.cn

Full Name: Jing Chen

Mobile: (01)8599137247, (86)15002530620

E-mail: sophic@163.com, chenj12@lzu.edu.cn

Gender: Female

Date of Birth: Feb. 01, 1988

Place of Birth: Inner Mongolia, China

Marital Status: Single

Address: Room 533, Feiyun Building, Lanzhou University, No.222 South Tianshui Road, Chengguan District, Lanzhou 730000, China.

EDUCATIONAL QUALIFICATIONS AND PROFESSIONAL AFFILIATIONS:

Education:

Sep. 2015 – May. 2016 Visiting Scholar to the Department of Electrical Engineering and Computer Science, Case Western Reserve University, USA.

Supervior: Guo-Qiang Zhang.

Sep. 2012 – Jun. 2016   Ph.D. in Computer Science. Supervisor: Prof. Bin Hu.

School of Information Science and Engineering, Lanzhou University, Lanzhou, China.

Sep. 2010 – Jun. 2012   M.S. in Computer Science. Supervisor: Prof. Bin Hu.

School of Information Science and Engineering, Lanzhou University, Lanzhou, China.

Honors:

2013 – 2014   Excellent Student Leader, Lanzhou University.

2013         National Scholarship for Doctorate Students.

2012 – 2013   First Prize Scholarship for Graduate Students, Lanzhou University.

2012 – 2013   “Triple-A” Outstanding Student, Lanzhou University.

2011 – 2012   First Prize Scholarship for Graduate Students, Lanzhou University.

2011 – 2012   “Triple-A” Outstanding Student, Lanzhou University.

2010 – 2011   “Triple-A” Outstanding Student, Lanzhou University.

2010         First Prize, University-Wide Women’s Basketball Match, Lanzhou University.

Concurrent Appointments and Other Activities:

2015 Volunteer of the 2015 International Symposium on Computational Psychophysiology. Jinan, Shandong Province, China.

2013 Program committee of the Third International Workshop on Intelligent Context-Aware Systems (ICAS). Taiwan, China.

2013   Reviewer of the journal of Applied Soft Computing.

2012   Reviewer of the International Conference on Active Media Technology (AMT) and the International Conference on Brain Informatics (BI).

2012   Reviewer of the journal of Cluster Computing.

2012   Online marking of the National Computer Rank Examination of China.

2012 Volunteer of the 431st Xiangshan Science Conference in Lanzhou, China.

2011   Teaching assistant providing guidance to undergraduates on C Language.

2011   Examiner of the National Computer Rank Examination at Lanzhou University.

2011   Reviewer of the International Conference of Pervasive Computing and the Networked World (ICPCA).

2010   Teaching assistant providing guidance to undergraduates on Data Structure.

RESEARCH PUBLICATIONS:

  • Principal Author
  • 1)Xiaowei Zhang, Bin Hu, Philip Moore, Jing Chen, Lin Zhou, “Emotiono: An Ontology with Rule-Based Reasoning for Emotion Recognition.” International Conference on Neural Information Processing, Shanghai, China, vol. 7063, 89-98, November 13-17, 2011.
  • 2)Xiaowei Zhang, Bin Hu, Jing Chen, Philip Moore, “Ontology-Based Context Modeling for Emotion Recognition in an Intelligent Web.” Journal of World Wide Web, pp. 1-17, 2012.
  • 3)Jing Chen, Bin Hu, Na Li, Chengsheng Mao, Philip Moore, “A Multimodal Emotion-Focused E-health Monitoring Support System.” The Seventh International Conference on Complex, Intelligent, and Software Intensive Systems, pp.505-510, 3-5 July 2013.
  • 4)Jing Chen, Bin Hu, Philip Moore, Xu Ma, “Electroencephalogram-Based Emotion Assessment System Using Ontology and Data Mining Techniques.” Applied Soft Computing, 30, pp. 663-674, 2015.
  • 5)Jing Chen, Bin Hu, Lixin Xu, Philip Moore, and Yun Su, “Feature-Level Fusion of Multimodal Physiological Signals for Emotion Recognition.” IEEE International Conference on Bioinformatics and Biomedicine, pp. 395-399, 9-12 Nov. 2015.
  • Co-Author
  • 1)Xiaowei Zhang, Daniel Cao, Philip Moore, Jing Chen, Lin Zhou, Yang Zhou, Xu Ma, “A Bayesian Network (BN) Based Probabilistic Solution to Enhance Emotional Ontology.” International Conference on Human Centric Technology and Service in Smart Space, 182, pp. 181-190, 2012.
  • 2)Xiaowei Zhang, Bin Hu, Lin Zhou, Philip Moore, Jing Chen, “An EEG Based Pervasive Depression Detection for Females.” International Conference on Pervasive Computing and the Networked World, 7719, pp. 848-861. 2013.
  • 3)Xiaowei Zhang, Bin Hu, Lin Zhou, Jing Chen, Philip Moore, “An XML Format for Electroencephalogram Data Presentation (eegML).” IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pp.584-588. 18-21 Dec. 2013.
  • 4)Na Li, Bin Hu, Jing Chen, Hong Peng, Qinglin Zhao, Mingqi Zhao, “Investigation of Chronic Stress Differences between Groups Exposed to Three Stressors and Normal Controls by Analyzing EEG Recordings.” International Conference on Neural Information Processing, Lee, A. Hirose, Z.-G. Hou & R. Kil (Eds.), vol. 8227, pp. 512-521, 2013.
  • 5)Xiaowei Zhang, Bin Hu, Xu Ma, Philip Moore, Jing Chen, “Ontology Driven Decision Support for the Diagnosis of Mild Cognitive Impairment.” Computer Methods and Programs in Biomedicine, 113, no. 3, pp. 781-791, 2014.
  • 6)Yun Su, Bin Hu, Lixin Xu, Hanshu Cai, Philip Moore, Xiaowei Zhang, Jing Chen, “EmotionO+: Physiological Signals Knowledge Representation and Emotion Reasoning Model for Mental Health Monitoring.” IEEE International Conference on Bioinformatics and Biomedicine (BIBM), 529-535, Nov. 2014.
  • 7)Yun Su, Bin Hu, Lixin Xu, Xiaowei Zhang, Jing Chen, “面向脑电数据的知识建模和情感识别.”(“EEG-Oriented Knowledge Modeling and Emotion Recognition.”) Science China Press, 60(11): 1002-1009, 2015.
  • 8)Yongqiang Dai, Bin Hu, Yun Su, Chengsheng Mao, Jing Chen, Xiaowei Zhang, Philip Moore, Hanshu Cai, and Lixin Xu, “Feature Selection of High-dimensional Biomedical Data using Improved SFLA for Disease Diagnosis.” IEEE International Conference on Bioinformatics and Biomedicine, pp. 458-463, 9-12 Nov. 2015.

RESEARCH EXPERIENCE:

2014-2018 Research on Alarming Theory of Potential Depression Risk and Key Technology of Bio-Sensing Based on Biological and Psychological Multimodal Information, funded by 973 Program Project of China. Project leader: Bin Hu.

2013-2017 Research on Key Problems of Pervasive Psychological Intervention Based on Biological Information Feedback, funded by International (Regional) Cooperation Projects of National Science Foundation of China. Project leader: Bin Hu.

2012-2014 Ontology-Based Emotional Context Modelling of Web Users, funded by Youth Foundation of Science and Technology Plan of Gansu Province, China. Project leader: Xiaowei Zhang.

2011-2013 Modelling and Reasoning of Human Emotions Based on Multimodal Bioelectrical-Signal Features in Pervasive Environment, funded by National Natural Science Foundation for Distinguished Young Scholars of China. Project leader: Xiaowei Li.

2011-2012 Emotion Recognition Based on Combining Multiple Physiological Characteristics, funded by the Fundamental Research Funds for the Central Universities, China. Project leader: Xiaowei Zhang.

2010-2012 OPTIMIOnline Predictive Tools for Intervention in Mental Illness, funded by the European Union’s 7th Framework Program, European Commission. Project leader of China: Bin Hu.

RESEARCH INTERESTS:

  • Ontology Modeling

Using Ontologies to represent EEG data and multiple EEG features extracted from raw EEG in a structured way. Reasoning can be performed on reasoning rules and the knowledge represented in ontological models to obtain the relationship between EEG and human emotions. The model can be further extended to support interdisciplinary research.

  • Affective Computing

Focusing on physiological signals-based emotion recognition. Evaluating arousal and valence (two dimensions in emotion space) by analyzing physiological signals, such as, electroencephalogram, electromyogram, respiration and skin temperature. Recognizing human emotions is based on combing multiple features extracted from bio-signals with classifiers.

  • Multimodal Information Fusion

Multimodal information fusion techniques are used on emotion recognition. My research is focused on two significant methods of multimodal fusion: feature-level fusion and decision-level fusion. In feature-level fusion, the features extracted from different modalities are integrated into a composite feature matrix and then input into a recognizer. In decision-level fusion, each modality is analyzed independently by the corresponding recognizer and the outputs of all recognizers are combined to yield the final decision.

  • Sleep Data Analysis

Gender differences are explored from adolescent sleep. I used EEG to find differences in adolescent girls’ and boys’ sleep. Gender differences were found not only in wake time, but also in difference sleep stages. Significant gender differences were found on sigma band. Within each gender group, spectral power performed well on distinguishing different sleep stages.

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