This project aims to improve the transparency and trustworthiness of AI systems in healthcare by using quantum-inspired agent-based modeling (ABM). By combining this with AI-based medical forecasting, the project will help create more reliable and ethical AI models that can handle complex medical data. The participating institutions will benefit by advancing their expertise in AI […]

Quantum entropy inequalities fundamentally limit how information can be distributed in a quantum system. However, it is an open problem to list and show all the entropy inequalities for the quantum setting beyond 3-party systems, which has proven extremely challenging both numerically and analytically. As the number of qubits we can experimentally initiate and control […]

Image processing principles and techniques represent a significant advancement in modern technology, offering invaluable contributions to numerous sectors. Despite their efficacy, conventional AI and ML-based image processing algorithms encounter inherent limitations that obstruct their scalability and performance. The main aim of the proposed research project is to develop image processing algorithm based on quantum computing […]

Molybdenum disulfide (MoS2) Quantum Dots (QDs) are being developed for use in areas from optoelectronics to energy storage and conversion, but synthetic protocols have yet to be developed to prepare high quality 0-dimensional (0D) material. A key challenge in efforts to develop synthetic protocols is a lack of rapid characterization technique that can unambiguously identify […]

Our group develops advanced tools that allow us to observe and understand materials operating within the realm of quantum physics, particularly those that emit light at the smallest scales. Quantum materials, often regarded as the superheroes of the science world, possess unique properties that can revolutionize technology—from ultra-fast computers to highly secure communication systems. To […]

Nearly 90% of drug candidates fail during the drug design and development process, resulting in exorbitant costs to bring a new drug to market. Our technology, LigandQI, addresses the critical shortcomings in current computational drug design programs by leveraging ab initio quantum chemistry to quantify ligand-receptor interactions with unprecedented accuracy. Unlike traditional methods, our program […]

This project aims to quantify defects in the probability framework for 2-dimensional (2D) materials with superior performance using optical techniques, primarily focusing on molybdenum disulfide (MoS2). Additionally, defects are an important factor influencing the performance of single-photon emitters (SPEs), a type of quantum device. This project will directly relate the SPE performance with defect concentration. […]

Graphene is a promising new nanomaterial, single layers of graphite, with superior physical and electrical properties making it an ideal candidate for electrical applications; however, current graphene production methods are expensive and complicated. As a result, new materials that have similar properties to graphene, but are more amenable to high-yield production are currently being investigated. […]

Computational chemistry is a powerful tool in the development of new pharmaceuticals, materials, and batteries. With accurate and fast computational methods, one can predict the physical and chemical properties of a molecule without having to prepare it in a laboratory and perform experiments, which can yield dramatic time and cost savings. However, the chemistry of […]

Graphene is an ultra-thin material with unprecedented chemical and mechanical properties. It is highly desirable for use in technological applications such as biosensors for disease detection and electrodes for energy storage devices, but expensive and energy-intensive synthesis methods have hindered it from widespread commercialization. New, more affordable ways of making graphene have thus been a […]

The electronic structure problem is the key for material and drug designs. Solving it accurately using quantum mechanical methods on regular classical computers leads to algorithms whose execution time grows exponentially with the system size (e.g., number of electrons and nuclei in molecules). Emerging technology of quantum computing recently provided a new hope to solve […]

In this project, the intern student is expected to investigate the post quantum cryptography (PQC) algorithms for QUIC protocol RFC and integrate them into the QUIC open source code. The student is expected to evaluate the performance of QUIC with the PQC algorithms integrated using a set of criteria.