诸薇娜

教授
  • 脑与认知、数字图像处理、人工智能。
  • 联系方式：zhuweina.cn@gmail.com
  • 地址：

研究方向：

我的研究方向聚焦于人类视觉系统中的信息处理过程，具体涵盖简单几何图形、自然场景和人脸等属性的分析。研究方法上，我主要采用脑电（EEG）、眼动追踪和心理物理学，以深入探究视觉信息在何时、何地到达意识。我当前的研究重点在于理解人脑是否能够在无意识的情况下处理视觉信息。


主持的基金Grants and Funding


2022 – 2025    国家自然科学基金(62166049), 370,000 CNY

2015 – 2018    国家自然科学基金(61563056), 450,000 CNY

2015 – 2017    高端外专项目 (GDT20155300084) 170,000 CNY/year

2015 – 2017    云南省教育厅重点(2015Z010) 40,000 CNY

2013 – 2014    国家留学基金委访问学者(201307035003)

2013 – 2016    国家自然科学基金(61263042), 450,000 CNY

2010 – 2012    国家自然科学基金(61005087), 200,000 CNY

2010 – 2012    云南省教育厅重点(2010Z067) 40,000 CNY

2009 – 2011    云南省科技厅项目(2009CD018), 75,000 CNY

2008 – 2010    云南大学研究基金(KL080012), 20,000CNY

2008 – 2009    云南大学青年研究基金(030-WX069051), 20,000CNY


发表论文：

1.      Gao, M., W. Zhu* and J. Drewes* (2024). "The temporal dynamics of conscious and unconscious audio-visual semantic integration." Heliyon 10(13): e33828.

2.      Drewes J, Witzel C, & Zhu W* (2023). Feature-Based Interaction between Masks and Target in Continuous Flash Suppression. Scientific Reports 13, no. 1 (March 22, 2023): 4696.

3.      Huang, Q., J. Derwes, and W. Zhu*. Congruency Effects with Animal and Human Target Objects. in International Conference on Applied Psychology, Modern Education. 2023. Kunming, China.

4.      Zhao L, Zhou D, Jin X, Zhu W*. nn-TransUNet: An Automatic Deep Learning Pipeline for Heart MRI Segmentation. Life (Basel). 2022;12(10). Epub 2022/10/28.

5.      Peng W, Wang X, Lang D, Zhu W*, editors. Does gender affect the processing of object classification in natural scenes. The 3rd International Conference on Artificial Intelligence and Computer Engineering; 2022.11.13; Dalian, China

6.      Drewes J, Muschter E, Zhu W, & Melcher D (2022). Individual Resting-State Alpha Peak Frequency and within-Trial Changes in Alpha Peak Frequency Both Predict Visual Dual-Pulse Segregation Performance. Cerebral Cortex, February 8, 2022, 1-12.

7.      Drewes J, Zhu W(co-first author), & Melcher D (2020). The optimal spatial noise for continuous flash suppression masking is pink. Scientific Reports, 10(1), 1–11.

8.      Drewes, J., W. Zhu(co-first author), and D. Melcher (2018), The edge of awareness: Mask spatial density, but not color, determines optimal temporal frequency for continuous flash suppression. J Vis, 18(1): p. 12.

9.      Zhu, W., Drewes, J.,Peatfield, N.A. and Melcher, D. (2016). Differential Visual Processing of Animal Images, with and without Conscious Awareness. Frontiers in Human Neuroscience, 10, 513.

10.   Zhu, W., Drewes, J., and Melcher, D. (2016). Time for Awareness: The Influence of Temporal Properties of the Mask on Continuous Flash Suppression Effectiveness. PLoS One, 11, e0159206.

11.   Drewes, J., Goren, G., Zhu, W., and Elder, J.H. (2016). Recurrent Processing in the Formation of Shape Percepts. The Journal of Neuroscience, 36, 185-192.

12.   Drewes J, Zhu W*, Wutz A, and Melcher D (2015). Dense sampling reveals behavioral oscillations in rapid visual categorization. Nature: Scientific Reports, 5, 16290. *co-first author

13.   Drewes J, Zhu W, and Melcher D (2014). Dissociation between spatial and temporal integration mechanisms in Vernier fusion. Vision Research, 2014, 105, 21–28

14.   Drewes J, Zhu W, Hu Y, and Hu X (2014). Smaller Is Better: Drift in Gaze Measurements due to Pupil Dynamics. PLoS One, 9(10): p. e111197.

15.   Zhu W, and Zhang X, (2013). Face Perception: Concepts, issues and advance. Journal of Yunnan University (Science) 35(3): p. 302-314.

16.   Zhu W, Drewes J, and Gegenfurtner, KR (2013). "Animal detection in natural images: effects of color and image database." PLoS One 8(10): e75816.

17.   Zhu W, Zhang J, and Zhou C (2013). The time course of the perceptual processing of “hole” and “no-hole” figures: An ERP study. Neuroscience Bulletin 29(1): p. 47-57

18.   Zhu W, Zhang J, Ding X, Zhou C, and Ma Y (2010). Face Capture more Attentional Resource than No-face Object: An ERP study. The 6th International Conference on Natural Computation (ICNC'10), p. 1953-1957.

19.   Zhu W, Zhang J, Ding X, Zhou C, Ma Y, and Xu D. (2009). Crossmodal Effect of Guqin Music and Piano music on Selective attention: an event-related potential study. Neuroscience Letters 466: 21-26

20.   Zhang J, Zhu W, Ding X, Zhou C, and Ma Y (2009). Different Masking Effects on “hole” and “no-hole” Figures. Journal of Vision 9(9):6 1-14

21.   Zhang J, Zhu W, Liu H, Zhou C, and Ma Y (2009). Configural Processing of Different Topological Structure Figures: an ERP Study. Science in China Series C: Life Sciences. 39(9): 898-903.

22.   Zhu W, Zhao L, Zhang J, Ding X, Liu H, Ni E, Ma Y, and Zhou C (2008). The Influence of Mozart’s Sonata K.448 on Visual Attention: An ERPs Study. Neuroscience Letters 434(1): 35-40.

23.   Zhu W, Zhang J, Liu H, Ding X, Ma Y, and Zhou C (2008). Differential cognitive responses to guqin music and piano music in Chinese subjects: an event-related potential study. Neuroscience Bulletin 24(1): 21-28.

24.   Zhu W, Zhou C, Xu D, and Xu J (2006). A Multi-feature CBIR Method Using in the Traditional Chinese Medicine Tongue Diagnosis. International Symposium on Pervasive Computing and Applications at Xinjiang, China, August 2006: 831-837.

25.   Zhu W, Xu D, and Zhou C (2005). Application of Multi-feature Content-based Image Retrieval in the Traditional Chinese Medicine Tongue Diagnosis. Journal of Image and Graphics 10(8): 992-998. (in Chinese)

26.   Zhu W, Xu D, and Zhou C (2004). Combining Color and Texture for Image Retrieval in the Traditional CMTD. 10th JICC, Proceedings of the Tenth Joint International Computer Conference, at Kunming, China, November 2004:165-172.

27.   Zhu W, Xu D, and Zhou C (2004). How to Combine Different Features for Image Retrieval in the Traditional CMTD. 13th National Conference of Multimedia Technology at Ningbo, China, October 2004:112-118. (in Chinese)

28.   Zhu W, Xu D, and Zhou C (2004). The Application of Content-based Image Retrieval in the Traditional Chinese Medicine Tongue Diagnosis. Journal of Yunnan University: Natural Sciences Edition. 26(5A): 138-143. (in Chinese)

29.   Zhu W and Xu D (2003). Review of Content-based Image Retrieval. Journal of Yunnan University: Natural Sciences Edition. 25(6A): 29-34. (in Chinese)

 


背景介绍：

脑与认知，是目前非常热门的一个研究领域。从1997年美国提出“人类脑计划”发展至今，对脑与认知的研究取得了巨大的进展。中国国家自然科学基金委也制定了“视听觉信息的认知计算”重大研究计划，国家对认知研究的发展越加重视。做为一个多学科交叉的新兴领域，认知科学必然是未来计算机科学和神经科学领域的重要研究方向。

脑科学和信息学是当今国际科学研究的两大热点，将这两大热点进行相互结合研究已经发展成了一门新兴的研究方向。而认知科学就是一门包括心理学、神经科学、人工智能模式识别等学科的新兴科学，其研究对象为人类和人工智能机制的理解和认知。与人类视听觉感知密切相关的图像、语音（语言、音乐）信息在社会经济的各个领域中扮演着重要角色，并一直保持迅猛增长。这类信息可被人类直接感知和理解，也可用计算机进行处理，但计算机的处理能力和效率远逊于人类。如何借鉴人类的认知机理和相关计算机科学的最新研究成果，建立新的计算模型和方法，从而大幅度提高计算机对这类信息的理解能力与处理效率，正是认知计算研究主要解决的问题。本人的研究正是以此为背景，开展的视听觉认知研究，具体从四个方面开展：
(1) 意识下的面孔认知研究（国家自然科学基金支持项目）
(2) 基于情绪认知机制的音乐情绪分类检索关键技术研究（国家自然科学基金支持项目）
(3) 基于复杂场景快速目标识别机制的图像信息快速提取关键技术研究（国家留学基金委支持与德国合作项目、国家自然科学基金支持项目）
(4) 基于感觉信息的时空融合的认知神经机制研究（国家外专局支持与意大利合作项目）


合作实验室：

德国Giessen大学和意大利Trento大学的脑与认知研究实验室；

厦门大学智能科学系和中科院生物物理所国家重点实验室。