This program will focus on the detailed characterization of the luminescence of a series of next-generation doped phosphors for lighting applications. These narrow-band-emitting, high-efficiency phosphors have demonstrated outstanding potential for use in phosphor-converted light emitting diodes. This technology is poised to replace traditional incandescent lights and it is expected to lead to an outstanding reduction […]

This program will focus on the detailed characterization of the luminescence of a series of next-generation doped phosphors for lighting applications. These narrow-band-emitting, high-efficiency phosphors have demonstrated outstanding potential for use in phosphor-converted light emitting diodes. This technology is poised to replace traditional incandescent lights and it is expected to lead to an outstanding reduction […]

My doctoral research work is based on the optoelectronic, and transport properties of layered two-dimensional (2D) and transition metal dichalcogenide (TMD) materials-based devices. Currently I am fabricating devices and studying their electron transport properties. The next target, to characterize the heat transportation in these devices, can’t be completed at my home institution because it requires […]

Positron Emission Tomography (PET) is a medical imaging modality enabling the detection of many physiological process, such as the uptake of specific molecule by cancer cells. Inside the patient, 511keV gamma produced by positron annihilation is detected and the annihilated point is mapped. Detecting the interaction time of each gamma-ray with a 10ps timing resolution […]

Iron-based nanoparticles can not only be used in sensitizers or absorbers but also retain excellent electrical conductivity, optical, electrical, and magnetic properties. So far, very few synthetic methods are known to implement stable Iron-based nanomaterials. We propose to develop novel synthesis routes to produce QDs. In addition, we plan to develop surface modification processes to […]

The proposed project investigates an approach to solve difficult physics problems, which are too computationally intensive for standard computers, using Xanadu’s near-term quantum computers. The goal of the project is to create a simulation tool that harnesses the exponential increase in efficiency offered by quantum computers to simulate the movement of particles and the subsequent […]

Manipulation and characterization of ultrafast optical signals are fundamental procedures for a wide range of applications, including telecommunications, biology, quantum information science, spectroscopy, and atomic and molecular physics. In this context, the so-called theory of space-time duality offers a powerful framework for the development of important optical signal processing functionalities. One of its key elements […]

We are witnessing an explosion in the use of machine learning (ML) algorithms with significant impacts on the world’s economic and social activities. The backbone of a machine learning algorithm is a deep neural network which is composed of hundreds to thousands of neurons. To make the neural networks (NNs) functional, they need to be […]

Vehicles that are able to autonomously move in the air, on the ground, or underwater must fuse various forms of sensor data together in order to ascertain the vehicles location relative to objects or a map. Typical sensor data includes inertial measurement unit data and some sort of positioning data, such as GPS data. However, […]

D-Wave Systems has designed processors based on a scalable architecture that aim to implement quantum annealing, an algorithm that can be used to solve a wide variety of optimization problems. A minimal requirement for a device to perform quantum annealing is that it maintains coherence throughout an appreciable fraction of the annealing protocol. In reality, […]

This internship will help SBQuantum move from an innovative scientific idea to a commercial venture. It supports a Canadian SME and Canada’s execution of quantum expertise as SBQuantum are a part of Canada’s nascent quantum industry. However, for this industry to be successful we need the help of business experts in order to navigate the […]

Unsupervised machine learning has recently been introduced into the field of quantum many-body physics. A strategy based on generative models has been particularly successful in the data-driven learning of quantum states. In this proposal, we aim to adapt this technology to applications in quantum chemistry. The primary focus of this research will be on the […]