王婷，工学博士，副教授；
Email: wangting@cuit.edu.cn
科研和研究生招生方向：
1、自然语言处理
2、图像处理与计算成像
个人简介：
现为必威讲师，2016年获得四川大学医学信息工程专业博士学位。2019-2020在美国范德比特大学图像科学研究所（VUIIS, Vanderbilt University Institute of Imaging Science, Vanderbilt University）从事静息态功能磁共振血液动力学理论研究。目前主要研究方向为磁共振图像与自然语言处理。
王婷承担和参与包括国家自然科学基金、四川省教育厅等国家和省部级科研项目多项，发表科研论文近十篇，其中SCI检索7篇。
目前承担科研项目：
1.国家自然科学基金青年基金项目，“基于贝叶斯增强学习的自适应奖赏学习策略机制研究”(61806029）。
2.四川省教育厅重点项目，“长短期记忆神经网络模拟奖赏学习任务神经活性”（2018Z065）
目前授课：
《人工智能》，《数据库原理及应用》，《云计算导论》，本科.
近5年发表论文（*为通信作者）：
1.Yongqing Zhang,Siyu Chen,Wenpeng Cao, Peng Guo, Dongrui Gao, Manqing Wang, Jiliu Zhou,Ting Wang*. MFFNet: Multi-dimensional Feature Fusion Network Based on Attention Mechanism for sEMG Analysis to Detect Muscle Fatigue. Expert Systems With Applications, 2021, 185:115639.
2.Ting Wang,D. Mitchell Wilkes, Muwei Li, Xi Wu*, John C. Gore, Zhaohua Ding*. Hemodynamic response function in brain white matter in a resting state, Cerebral cortex communications, 2020, 1(1): tgaa056.
3.Ting Wang, Xi Wu, Jiefeng Jiang, Chang Liu, Ming Zhu*, Functional neural interactions during adaptive reward learning: An functional magnetic resonance imaging study, International Journal of Imaging System Technology (SCI, IF: 1.254), 2019, 30:92–103.
4.Ting Wang, Zhiyun Lian, Xi Wu, Yazhuo Kong, Hongyu Zhou*, Min Wei*, Subcortical structural abnormalities in female neuro myelitis optica patients with neuropathic pain, Multiple Sclerosis and Related Disorders (SCI, IF: 2.725), 2019, 37 (2020) 101432.
5.Xinfang Wang , Lianqing Hong , Xi Wu , Jia He,Ting Wang*, Hongbo Li, Shaoling Liu, Development of an Ultrasonic Nomogram for Preoperative Prediction of Castleman Disease Pathological Type, Computers, Materials & Continua (SCI, IF: 3.024), 2019,61(1), 141-154.
6.Xi Wu,Ting Wang, Chang Liu, Tao Wu, Jiefeng Jiang, Dong Zhou, Jiliu Zhou*, Functions of Learning Rate in Adaptive Reward Learning, Frontiers in Human Neuroscience (SCI, IF: 3.634), 2017, 11(5):1-15.
Curriculum Vitae
Dr. Ting Wang
Associate Professor
Department of Computer Science
Chengdu University of Information Technology
Contact:wangting@cuit.edu.cn
Dr. Ting Wang is an assistant professor of Department of Computer Science, Chengdu University of Information Technology. Shereceived the Ph.D. degree in Medical Information Engineering from the Sichuan University, Chengdu, China, in 2016. From 2019 to 2020, she wasa visiting schoolar at the Vanderbilt University Institute of Imaging Science, Vanderbilt University, USA.Her research interests include machine learning and MRI analysis.
Research interests:
1. Image processing and computational imaging
2. Natural language processing
Courses:
Artificial Intelligence, Principle and Application of Database, Cloud Computing for undergraduate students
Publications (past 5 years):
1.Yongqing Zhang, Siyu Chen, Wenpeng Cao, Peng Guo, Dongrui Gao, Manqing Wang, Jiliu Zhou,Ting Wang*. MFFNet: Multi-dimensional Feature Fusion Network Based on Attention Mechanism for sEMG Analysis to Detect Muscle Fatigue. Expert Systems With Applications, 2021, 185:115639.
2.Ting Wang,D. Mitchell Wilkes, Muwei Li, Xi Wu*, John C. Gore, Zhaohua Ding*. Hemodynamic response function in brain white matter in a resting state, Cerebral cortex communications, 2020, 1(1): tgaa056.
3.Ting Wang, Xi Wu, Jiefeng Jiang, Chang Liu, Ming Zhu*, Functional neural interactions during adaptive reward learning: An functional magnetic resonance imaging study, International Journal of Imaging System Technology (SCI, IF: 1.254), 2019, 30:92–103.
4.Ting Wang, Zhiyun Lian, Xi Wu, Yazhuo Kong, Hongyu Zhou*, Min Wei*, Subcortical structural abnormalities in female neuro myelitis optica patients with neuropathic pain, Multiple Sclerosis and Related Disorders (SCI, IF: 2.725), 2019, 37 (2020) 101432.
5.Xinfang Wang , Lianqing Hong , Xi Wu , Jia He,Ting Wang*, Hongbo Li, Shaoling Liu, Development of an Ultrasonic Nomogram for Preoperative Prediction of Castleman Disease Pathological Type, Computers, Materials & Continua (SCI, IF: 3.024), 2019,61(1), 141-154.
6.Xi Wu,Ting Wang, Chang Liu, Tao Wu, Jiefeng Jiang, Dong Zhou, Jiliu Zhou*, Functions of Learning Rate in Adaptive Reward Learning, Frontiers in Human Neuroscience (SCI, IF: 3.634), 2017, 11(5):1-15.
