Prof. Md. Haidar SHARIF      

Effect of BCI Technologies on Our Lives and Existence

Abstract

Brain Computer Interface (BCI) technologies make available a world of options. BCI technologies use signals recorded from the brain (e.g., EEG: Electroencephalography) to apply miscellaneous controls and communications without using any external devices or muscle intervention. Their applications include but not limited to: (i) Brain to device control, (ii) Device to brain control, (iii) Brain to Internet communications with an infinite amount of information storage and retrieval, (iv) Mind to mind communication, (v) Memories and feelings transformation, and (vi) Brain to brain control. BCI technologies are still in its primitive stages. When the adulthood of these technologies will be attended, we will get all sensory information. Thus, we can do basically whatever we would think. In theory, we will have all lives from all other people. We will feel all people’s feelings. Virtually, we will be living in the Heaven on this Earth. But our minds would be manipulated by brain hackers, who would insert or delete our memories anytime and then we will have the feelings of the Hell on this Earth. It would be required to optimize between these two issues. To cut a long story short, we are on the cusp of the emerging BCI technologies which are extremely powerful and have very high potential to dramatically transubstantiate our lives and existence.

Data Science and Cybersecurity: Challanges and New Research Directions

Abstract

coming soon .....

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Advances in Computer Simulations of Macromolecular Systems

Abstract

Molecular dynamics (MD) simulations are often used to provide detailed insights into the dynamics of macromolecular systems, such as proteins, DNA/RNA, membranes, and their complexes. These dynamics involve transitions between various conformational states due to atomic motions. The main problem of standard MD simulation is the time and size scale limitations of the technique in studying slow conformational motions of macromolecular systems. Therefore, the considerable time and size scale physical and chemical phenomena will indeed require new statistical and computational approaches to be studied efficiently. In this talk, I will discuss different approaches suggested for enhancing the conformational search and sampling efficiency of MD simulations. In particular, I will focus on using these approaches to improve conformational sampling in computer simulations of peptide/protein folding and transition path sampling. Recently, artificial neural network methods are employed to build up a deep learning architecture for molecular modeling, and in particular, molecular dynamics. In this talk, I will focus on recent advanced methodological studies in the application of machine learning approaches in MD simulations and prediction of molecular properties, and in their role in enabling rational design technologies.

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Prof. Joan Lu      

Mobile Learning technology - Impact and inside stories

Abstract

Learning with technology is always debatable between traditional classroom and modern learning environment. For example, most institutes do not allow their students to use their smartphone in the classroom, because students need to concentrate on the lecturing. this talk may argue that the use of smartphone could be positively encouraging students to learn. It is no doubt that technology is developing so fast to push the methodology to catch up, to adopt and to disseminate the new outcome, discovery and inventions. The question is what opportunities we can give to the young generation in our classroom learning?