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Mario A. Aoun
Montreal, Canada

Mario Aoun received his bachelor’s degree in computer science from Notre Dame University (NDU), Lebanon, in 2003. His final-year project, a location-based service for Windows mobile phones, won the Microsoft Competition for Universities in Lebanon that year. In parallel to his university studies, Mario developed complex database applications ranging from client-server applications to mobile and multi-tier applications.

In 2007, after fulfilling his master’s (MS) degree in computer science from NDU, he was accepted for a PhD scholarship at the University of Twente, with training at Philips Research Center. Unfortunately, he was struck by a neurological disorder called transverse myelitis (TM). TM is an inflammation of a segment of the spinal cord, making him paraplegic; he was forced to cancel the scholarship.

In 2009, he reviewed a book for ACM Computing Reviews (CR), Computational Intelligence: a Compendium, which revived his personal research goals in artificial intelligence and neural networks. Consequently, in 2010, he wrote a research paper based on his MS thesis—“STDP within NDS Neurons”—which he submitted to and presented at the International Symposium on Neural Networks (ISNN 2010) in Shanghai, China.

At the end of 2010, he immigrated to Canada, and is now in his fourth year as a PhD research student in cognitive informatics at the Université du Québec à Montréal (UQAM).

His research interests include chaos theory, chaos control, reservoir computing, computational neuroscience, neurocognition, and the limits of intelligence. He investigates and approaches the exploit of the theory of chaotic nonlinear dynamics in order to emulate cognitive processes, like memory and perception, which are explained and elucidated by the theory of chaotic neurodynamics. The latter favors the role of chaos in the brain as an essential ingredient that makes the brain distinct from any artificial intelligent machine. The impact of this research will help us understand and delineate the limitations of both natural and artificial intelligence. He presented his latest research paper, “Learning algorithm and neurocomputing architecture for NDS neurons, ” in August 2014 at the IEEE International Conference on Cognitive Informatics and Cognitive Computing (ICCI*CC 2014) in London, England; he received the Best Paper Award. Also, in the same trip, he was invited to do a seminar at Oxford Brookes University to discuss the potential implication of his research work.

Mario’s review of The universal machine was selected as one of the best CR reviews of 2013.


Assessing neural network scene classification from degraded images
Tadros T., Cullen N., Greene M., Cooper E.  ACM Transactions on Applied Perception 16(4): 1-20, 2019. Type: Article, Reviews: (2 of 2)

One of the major problems faced by deep learning techniques--for example, deep convolutional neural networks (CNNs)--is uncontrolled behavior due to glitches in the input. For example, you can modify just a few pixels in a photo’s ...


Artificial intelligence: looking through the Pygmalion lens
Gill K.  AI & Society 33(4): 459-465, 2018. Type: Article

This paper reminds me of early nuclear energy “control” advocacy. In fact, the discovery of uranium, and specifically the widespread global knowledge of a significant inventive process that allows the release of a huge amount of energy...


Computational memory: a stepping stone to non-von Neumann computing?
Abu Sebastian. YouTube, 01:20:34, published on Mar 8, 2018, stanfordonline, Type: Video

The topic of this video presentation is computational memory (CM), a seemingly fascinating new paradigm in computing. The presenter’s approach to the topic is captivating; when you start the video, you just want to proceed forward and see wh...


Life 3.0: being human in the age of artificial intelligence
Tegmark M.,  Vintage Books, New York, NY, 2018. 384 pp. Type: Book (978-1-101970-31-7)

We should finally admit that technology and specifically artificial intelligence (AI) drive our lives. This has become a fact that we can never neglect or consider to be happening in the future. AI is shaping our present, so how should we cope wit...


Fast and accurate time-series clustering
Paparrizos J., Gravano L.  ACM Transactions on Database Systems 42(2): 1-49, 2017. Type: Article

Clustering temporal data, namely time series, is a challenging and expensive computational task in terms of accuracy and speed. Despite the fact that a wide variety of time-series clustering algorithms exist in the literature, they remain unsatisf...


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