Prof Reza Ebrahimpour
Computational-Cognitive Vision Group
Affiliation: Department of Electrical and Computer Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran and School of Cognitive Sciences (SCS), Institute for Research in Fundamental Sciences (IPM), Niavaran, Tehran, Iran.
Contact: ebrahimpour [at]ipm[dot]ir

I am Reza Ebrahimpour a professor at the department of computer engineering, Shahid Rajaee Teacher Training University, Tehran, Iran. I obtained Ph.D. degree in the field of Cognitive Neuroscience from the SCS, IPM, Tehran, Iran in July 2007. My research area is Cognitive and Systems Neuroscience. My research laboratory, the computational cognitive vision lab (CCVLab), is mainly focused on two are of research:

1- Mechanism of object/face recognition

How does our brain represent objects? My laboratory has focused to answer this question in several aspects. Using computational models we investigate the mechanisms underlying object representation in the cortex such as the role of feed-forward and recurrent connections and the transformation of visual information between cortical layers. We are interested to develop new computational models that increase the explanatory power of behavioral and neural data. By combining psychophysics and electroencephalography (EEG) techniques, we aim to understand the temporal dynamics of the object processing under challenging like occluded objects and non-challenging conditions and its influence on behavior.

2- The mechanism underlying making decision

Decision making is an integrative process that results in the commitment to a categorical proposition. Brain receives information from different sensory modalities and integrates them with his/her prior knowledge as well as the information about the cost of each choice. Finally, the brain commit to a choice after an amount of time and with a level confidence. Our research aims to shed more light on this process and the way it is implemented in the neural level. We applied different characteristics of real-world situations such as discretization of information, social influences etc. in our psychophysics experiments in order to investigate the process of decision making in more realistic situations. While human subjects are making decision during the experiment we record both behavioral and neural responses. Then, using computational-neural models we investigate the mechanism underlying decision making considering different aspect of real-world situations.

Group website:

Selected Publications

[1] Hamid Karimi-Rouzbahani, Nasour Bagheri, Reza Ebrahimpour (October, 2017) Invariant object recognition is a personalized selection of invariant features in humans, not simply explained by hierarchical feed-forward vision models, Scientific reports 7 (1), 14402.

[2] Shayan Moini, Bijan Alizadeh, Mohammad Emad, Reza Ebrahimpour (2017, October) A Resource-Limited Hardware Accelerator for Convolutional Neural Networks in Embedded Vision Applications, IEEE Transactions on Circuits and Systems II: Express Briefs, 64(10), 1217-1221.

[3] Hamid Karimi-Rouzbahani, Nasour Bagheri, Reza Ebrahimpour (May, 2017) Hard-wired feed-forward visual mechanisms of the brain compensate for affine variations in object recognition, Neuroscience, Vol. 349, pp. 48–63.

[4] Hamid Karimi-Rouzbahani, Nasour Bagheri, Reza Ebrahimpour ( March, 2017) Average activity, but not variability, is the dominant factor in the representation of object categories in the brain, Neuroscience, Vol. 346, pp. 14–28.

[5] Amirhossein Farzmahdi, Karim Rajaei, Masoud Ghodrati, Reza Ebrahimpour, Seyed-Mahdi Khaligh-Razavi (April, 2016) A specialized face-processing model inspired by the organization of monkey face pathes explains several face-specific phenomena observed in humans, Scientific Reports 6, 25025, doi:10.1038/srep25025.


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