Related papers: Graphene-based Wireless Agile Interconnects for Ma…
The scientific community has witnessed an exponential increase in the applications of graphene and graphene-based materials in a wide range of fields. For what concerns neuroscience, the interest raised by these materials is two-fold. On…
Nanomachines promise to enable new medical applications, including drug delivery and real time chemical reactions' detection inside the human body. Such complex tasks need cooperation between nanomachines using a communication network.…
Graphene has unique properties paving the way for groundbreaking future applications. Its large optical nonlinearity and ease of integration in devices notably makes it an ideal candidate to become a key component for all-optical switching…
In this opening presentation we will first recall the main characteristics of graphene conductivity and electromagnetic wave propagation on graphene-based structures. Based on these observations and different graphene antenna simulations…
Graph neural networks have become a staple in problems addressing learning and analysis of data defined over graphs. However, several results suggest an inherent difficulty in extracting better performance by increasing the number of…
Graph neural networks (GNNs) have been shown promising in improving the efficiency of learning communication policies by leveraging their permutation properties. Nonetheless, existing works design GNNs only for specific wireless policies,…
The real-world networks often compose of different types of nodes and edges with rich semantics, widely known as heterogeneous information network (HIN). Heterogeneous network embedding aims to embed nodes into low-dimensional vectors which…
Optical computing has recently attracted a great deal of interest as it offers the ability to process data in a parallel manner. In this report, an optical computing system based on a metamaterial structure made of graphene is designed and…
Massive MIMO is a cornerstone of next-generation wireless communication, offering significant gains in capacity, reliability, and energy efficiency. However, to meet emerging demands such as high-frequency operation, wide bandwidths,…
Graphene is a very attractive material for broadband photodetection in hyperspectral imaging and sensing systems. However, its potential use has been hindered by tradeoffs between the responsivity, bandwidth, and operation speed of existing…
Interconnection networks, or `interconnects,' play a crucial role in administering the communication among computing units of high-performance computing (HPC) systems. Efficient provisioning of interconnects minimizes the processing delay…
Interface interactions in 2D vertically stacked heterostructures play an important role in optoe-lectronic applications, photodetectors based on graphene/InSe heterostructures had shown promising performance nowadays. However, nonlinear…
Modern microelectronic processors have migrated towards parallel computing architectures with many-core processors. However, such expansion comes with diminishing returns exacted by the high cost of data movement between individual…
Heterogeneous graph representation learning aims to learn low-dimensional vector representations of different types of entities and relations to empower downstream tasks. Existing methods either capture semantic relationships but indirectly…
Heterogeneous information network (HIN) has been widely used to characterize entities of various types and their complex relations. Recent attempts either rely on explicit path reachability to leverage path-based semantic relatedness or…
Now a day's Heterogeneous wireless network is a promising field of research interest. Various challenges exist in this hybrid combination like load balancing, resource management and so on. In this paper we introduce a reliable load…
The next generation wireless networks (i.e. 5G and beyond), which would be extremely dynamic and complex due to the ultra-dense deployment of heterogeneous networks (HetNets), poses many critical challenges for network planning, operation,…
Graph Neural Networks have emerged as the most popular architecture for graph-level learning, including graph classification and regression tasks, which frequently arise in areas such as biochemistry and drug discovery. Achieving good…
Hybrid Graphene/magnetic structures offer a unique playground for fundamental research, and opportunities for emerging technologies. Graphene-spaced ultrathin structures with antiferromagnetic exchange-coupling (AFC) seem a relevant…
The next generation of wireless networks is expected to tap into the terahertz (0.1--10 THz) band to satisfy the extreme latency and bandwidth density requirements of future applications. However, the development of systems in this band is…