This talk will introduce Loughborough University and show some of the Engineering research and facilities. The talk will then focus on the research of Dr. Whittow and his colleagues at Loughborough University. This will include wearable antennas, inkjet printing, RFID tags, 3d-printing and metamaterials. The work will include some results from SYMETA which is a $7 million project to develop RF-devices. 

Space-time conservation element and solution element (CESE) method is a unique finite-volume-type method for computational fluid dynamics (CFD). This approach has several attractive properties, including: (i) unified treatment of the space and time such that only one step is required to construct high-order schemes; (ii) a highly compact stencil regardless of the order of the accuracy; (iii) easiness of extension to any arbitrary shape of polygonal elements. Since its inception, the CESE method has achieved great success in different areas.

The idea behind this presentation is to give to the potential contributors/authors a general view about the Physical Review Family of Journals, and more specifically about Physical Review Applied journal.

In this course we consider multi-phase flows, i.e., flows of one substance which is present as liquid as well as vapor. We focus on models that resolve individual bubbles/droplets and that treat both phases as compressible. We will also discuss incompressible/low Mach limits, since in most applications the liquid is nearly incompressible. Understanding and simulating such small-scale models is important in order to obtain information which can be used in larger scale models for e.g. sprays which play important roles in processes of practical interest as diverse as combustion, chemical engineering, and cloud formation

I will provide an overview on recent researches on acoustic and elastic metamaterials and metasurfaces for controllable wave manipulation, we are developing in my group in the University of Lorraine. I first will present some advances related to low-frequency acoustic and vibration shielding/absorption making use of metamaterials1,2 and metasurfaces3,4, and describe the added value that such artificial engineered materials can bring to consider some innovative applications.

Machine learning has been extensively used in developing predictive models for a variety of bioinformatics tools. In many of these applications, to achieve the highest possible predictive performance, black box models (e.g., SVMs and Neural Networks) had been preferred over white box models (e.g., Decision Trees and Rule-based models). First, I argue that sacrificing interpretability for the sake of performance is a reasonable decision for many bioinformatics applications. However, I will demonstrate that uncareful utilization of black box models can lead to misinterpretations of the results.

In this course we consider multi-phase flows, i.e., flows of one substance which is present as liquid as well as vapor. We focus on models that resolve individual bubbles/droplets and that treat both phases as compressible. We will also discuss incompressible/low Mach limits, since in most applications the liquid is nearly incompressible. Understanding and simulating such small-scale models is important in order to obtain information which can be used in larger scale models for e.g. sprays which play important roles in processes of practical interest as diverse as combustion, chemical engineering, and cloud formation

Semiconductor-based terahertz (THz) devices such as photoconductive antennas (PCAs) and photomixers (PMs) are widely studied as promising candidates of THz source generation and signal detection. Recent experimental research has shown that using nanostructures in the design of these devices dramatically enhances their optical-to-THz conversion efficiency, possibly allowing their use in widespread industrial applications. However, the nanostructures also increase the complexity of design and fabrication.

The general idea of discrete differential geometry is to find and investigate discrete models that exhibit properties and structures characterisitic of the corresponding smooth geometric objects. This is a challenging problem, since equivalent points of view in the smooth setting may lead to a number of inequivalent treatments in the discrete setting. We will illustrate the paradigm of structure-preserving discretizations on the example of conformal maps by showing how simple definitions lead to surprisingly rich theories.

We analyze the photonic topological phases in dispersive metamaterials which satisfy the degenerate condition at a reference frequency, where the hybrid modes are decoupled and determined by two subsystems with degenerate eigenvalues. By introducing the pseudospin states as the eigenfield basis, the Hamiltonians of the hybrid modes represent the pesudospin-orbit interaction with spin 1, which result in nonzero spin Chern numbers that characterize the topological phases.

The wireless communication technology has been evolved from 1G to 5G networks. The next 6G era will bring about higher demands for bandwidth and speed. Visible light communication (VLC) shows great potential in providing high speed and secure communication link by utilizing the unregulated visible light spectrum to carry the data. In this seminar, the overview of VLC will be presented first. The devices and components developed for VLC network will then be reviewed and discussed in details. I will also briefly talk about the application of underwater communication application by using visible light at the end of the seminar.

Dynamic treatment regimes are a set of decision rules and each treatment decision is tailored over time according to patients’ responses to previous treatments as well as covariate history. There is a growing interest in development of correct statistical inference for optimal dynamic treatment regimes to handle the challenges of nonregularity problems in the presence of nonrespondents who have zero-treatment effects, especially when the dimension of the tailoring variables is high.

Implantable medical devices (IMD) and neuroprostheses are finding applications in new therapies thanks to advancements in microelectronics, sensors, RF communications, and medicine, which have resulted in embedding more functions in IMDs that occupy smaller spaces down to millimeters and consume less power, while offering therapies for more complex diseases and disabilities. I will address the latest developments in key building blocks for state-of-the-art IMDs.

There is an increasing growth in the amount of electronic health records (EHRs) being collected by healthcare facilities. Data mining techniques hold great potential to systematically use such data for identifying not only inefficiencies but also best practices that improve care and reduce costs. However, due to the complexity of EHR data, directly applying traditional machine learning techniques may yield unsatisfactory predictive performance. Recent advances in deep learning-based methods provide unprecedented ability to predict patients’ future health status, but they still suffer from the sparsity issue of EHR data.

With the end of the Moore’s law, it became imperative to find new principles for computing that can avoid the current physical limitations. Among the promising approaches is Quantum Computing which has resulted in substantial national investments in research and development in this area by many nations. This first tutorial is designed to target scientists, engineers and mathematicians who are interested in this rapidly growing field but have not yet invested enough time in learning about it.

In this talk we propose a Flux Corrected Transport (FCT)-like stabilization suitable for high-order Discontinuous Galerkin (DG) finite element discretizations. As a model problem we consider the multi-dimensional transport equation. The method guarantees that the solution satisfies a local Discrete Maximum Principle (DMP). A solution is said to satisfy a DMP locally if any degree of freedom is bounded with respect to the solution at the previous time step in some defined neighborhood.

In this talk, I will present my research on designing multi-agent robotic systems and developing theory and algorithms for system control. The first part of the talk will present my research on designing an animal-borne remote imaging system and developing theory and algorithm for distributed sensor fusion that enables estimation and detection of animal group movements using the system. I will explain data collection capability of the system and share system deployment experiences in monitoring a wild life of African animals In the second part, I will describe my current work on developing a fleet of autonomous robotic vessels.

The talk will concern the role of statistical thinking in the search for Truth. This will bring us to a discussion of P-values, which has been, and still is, a central concept in Statistics and is a critical and highly controversial tool of scientific research. Recently it has elicited much, sometimes heated, debates and discussions. The American Statistical Association (ASA) was even compelled to release an official statement in early March 2016 regarding this issue, and a psychology journal gone to the extreme of banning the use of P-values in articles appearing in its journal!

In this talk, I will start with an overview of my research to date. Then, I will address in more detail the study of the asymptotic behavior of a two-dimensional variational model within finite crystal plasticity for high-contrast bilayered composites. More precisely, we consider materials arranged into periodically alternated thin horizontal strips of an elastically rigid component and a softer one with one active slip system. The energies arising from our modeling assumptions are of integral form, featuring linear growth and non-standard differential constraints.

The Cahn-Hilliard equation is a fourth order parabolic partial differential equation (PDE) that is widely used as a phenomenological model to describe the evolution of interfaces in many practical problems, such as, the microstructure formation in materials, fluid flow, etc. It has been observed in the engineering literature that the stochastic version of the Cahn-Hilliard equation provides a better description of the experimentally observed evolution of complex microstructure.

Promoter is a key region that is involved in differential transcription regulation of protein-coding and RNA genes. The gene-specific architecture of promoter sequences makes it extremely difficult to devise the general strategy for their computational identification.