Publications (224)
Enhanced Random Subspace Local Projections for High-Dimensional Time Series Analysis
Eman Khalid, Moimma Ali Khan, Zarmeena Ali +3
High-dimensional time series forecasting suffers from severe overfitting when the number of predictors exceeds available observations, making standard local projection methods unst…
Security and Privacy in IoT Using Machine Learning and Blockchain: Threats & Countermeasures
Nazar Waheed, Xiangjian He, Muhammad Ikram +2
Security and privacy of the users have become significant concerns due to the involvement of the Internet of things (IoT) devices in numerous applications. Cyber threats are growin…
Understanding electric field control of electronic and optical properties of strongly-coupled multi-layer quantum dot molecules
Muhammad Usman
Strongly-coupled quantum dot molecules (QDMs) are widely deployed in the design of a variety of optoelectronic, photovoltaic, and quantum information devices. An efficient and opti…
Quantum Calculus-based Volterra LMS for Nonlinear Channel Estimation
Muhammad Usman, Muhammad Sohail Ibrahim, Jawwad Ahmad +2
A novel adaptive filtering method called -Volterra least mean square (-VLMS) is presented in this paper. The -VLMS is a nonlinear extension of conventional LMS and it is b…
A Robust Variable Step Size Fractional Least Mean Square (RVSS-FLMS) Algorithm
Shujaat Khan, Muhammad Usman, Imran Naseem +2
In this paper, we propose an adaptive framework for the variable step size of the fractional least mean square (FLMS) algorithm. The proposed algorithm named the robust variable st…
Adversarially Robust Quantum Transfer Learning
Amena Khatun, Muhammad Usman
Quantum machine learning (QML) has emerged as a promising area of research for enhancing the performance of classical machine learning systems by leveraging quantum computational p…
Leveraging Large Language Models for Multi-Class and Multi-Label Detection of Drug Use and Overdose Symptoms on Social Media
Muhammad Ahmad, Fida Ullah, Muhammad Usman +3
Drug overdose remains a critical global health issue, often driven by misuse of opioids, painkillers, and psychiatric medications. Traditional research methods face limitations, wh…
Calibrating the role of entanglement in variational quantum circuits
Azar C. Nakhl, Thomas Quella, Muhammad Usman
Entanglement is a key property of quantum computing that separates it from its classical counterpart, however, its exact role in the performance of quantum algorithms, especially v…
Interactive Diversity Optimization of Environments
Glen Berseth, Mahyar Khayatkhoei, Brandon Haworth +3
The design of a building requires an architect to balance a wide range of constraints: aesthetic, geometric, usability, lighting, safety, etc. At the same time, there are often a m…
A Givens-exchange ansatz for molecular variational eigensolvers
Azadeh Alavi, Fatemeh Kouchmeshki, Muhammad Usman +4
Molecular ground-state energies help determine conformer rankings, reaction energetics, and electronic effects in computational drug discovery, but accurate calculations become dif…
Quantum Cloud Computing: A Review, Open Problems, and Future Directions
Hoa T. Nguyen, Prabhakar Krishnan, Dilip Krishnaswamy +2
Quantum cloud computing is an emerging paradigm of computing that empowers quantum applications and their deployment on quantum computing resources without the need for a specializ…
Non-Clifford Crosstalk Noise in Surface Codes Using Hybrid Stabilizer-Tensor Network Methods
Ben Harper, Azar C. Nakhl, Martin Sevior +1
Scalable realisation of quantum computing is reliant on the development of fault tolerant devices. Analysis of quantum error correction protocols typically considers incoherent noi…
Bird Eye-View to Street-View: A Survey
Khawlah Bajbaa, Muhammad Usman, Saeed Anwar +2
In recent years, street view imagery has grown to become one of the most important sources of geospatial data collection and urban analytics, which facilitates generating meaningfu…
PENDULUM: A Benchmark for Assessing Sycophancy in Multimodal Large Language Models
A. B. M. Ashikur Rahman, Saeed Anwar, Muhammad Usman +2
Sycophancy, an excessive tendency of AI models to agree with user input at the expense of factual accuracy or in contradiction of visual evidence, poses a critical and underexplore…
Secure and Trustworthy Artificial Intelligence-Extended Reality (AI-XR) for Metaverses
Adnan Qayyum, Muhammad Atif Butt, Hassan Ali +6
Metaverse is expected to emerge as a new paradigm for the next-generation Internet, providing fully immersive and personalised experiences to socialize, work, and play in self-sust…
Anatomy-Guided Representation Learning Using a Transformer-Based Network for Thyroid Nodule Segmentation in Ultrasound Images
Muhammad Umar Farooq, Abd Ur Rehman, Azka Rehman +3
Accurate thyroid nodule segmentation in ultrasound images is critical for diagnosis and treatment planning. However, ambiguous boundaries between nodules and surrounding tissues, s…
Automatizing the search for mass resonances using BumpNet
Jean-Francois Arguin, Georges Azuelos, Ãmile Baril +15
The search for resonant mass bumps in invariant-mass distributions remains a cornerstone strategy for uncovering Beyond the Standard Model (BSM) physics at the Large Hadron Collide…
VPN: Verification of Poisoning in Neural Networks
Youcheng Sun, Muhammad Usman, Divya Gopinath +1
Neural networks are successfully used in a variety of applications, many of them having safety and security concerns. As a result researchers have proposed formal verification tech…
A scalable and fast artificial neural network syndrome decoder for surface codes
Spiro Gicev, Lloyd C. L. Hollenberg, Muhammad Usman
Surface code error correction offers a highly promising pathway to achieve scalable fault-tolerant quantum computing. When operated as stabilizer codes, surface code computations c…
Real-Time Decoding for Fault-Tolerant Quantum Computing: Progress, Challenges and Outlook
Francesco Battistel, Christopher Chamberland, Kauser Johar +5
Quantum computing is poised to solve practically useful problems which are computationally intractable for classical supercomputers. However, the current generation of quantum comp…
Effect of shape on void growth: A coupled Extended Finite Element Method (XFEM) and Discrete Dislocation Plasticity (DDP) study
Muhammad Usman, Sana Waheed, Aamir Mubashar
Voids are one of the many material defects present at the microscopic length scale. They are primarily responsible for the formation of cracks and hence contribute to ductile fract…
Quantum Machine Learning
Muhammad Usman
The meteoric rise of artificial intelligence in recent years has seen machine learning methods become ubiquitous in modern science, technology, and industry. Concurrently, the emer…
A meshless numerical solution of the family of generalized fifth-order Korteweg-de Vries equations
Syed Tauseef Mohyud-Din, Elham Negahdary, Muhammad Usman
In this paper we present a numerical solution of a family of generalized fifth-order Korteweg-de Vries equations using a meshless method of lines. This method uses radial basis fun…
Time-adaptive single-shot crosstalk detector on superconducting quantum computer
Haiyue Kang, Benjamin Harper, Muhammad Usman +1
Quantum crosstalk which stems from unwanted interference of quantum operations with nearby qubits is a major source of noise or errors in a quantum processor. In the context of sha…
q-RBFNN:A Quantum Calculus-based RBF Neural Network
Syed Saiq Hussain, Muhammad Usman, Taha Hasan Masood Siddique +3
In this research a novel stochastic gradient descent based learning approach for the radial basis function neural networks (RBFNN) is proposed. The proposed method is based on the…
Spatiotemporal Pauli processes: Quantum combs for modelling correlated noise in quantum error correction
John F Kam, Angus Southwell, Spiro Gicev +2
Correlated noise is a critical failure mode in quantum error correction (QEC), as temporal memory and spatial structure concentrate faults into error bursts that undermine standard…
RBF-FD Method for Some Dispersive Wave Equations and Their Eventual Periodicity
Marjan Uddin, Hameed Ullah Jan, Muhammad Usman
In this paper, we approximate the solution and also discuss the periodic behavior termed as eventual periodicity of solutions of (IBVPs) for some dispersive wave equations on a bou…
Towards quantum enhanced adversarial robustness in machine learning
Maxwell T. West, Shu-Lok Tsang, Jia S. Low +5
Machine learning algorithms are powerful tools for data driven tasks such as image classification and feature detection, however their vulnerability to adversarial examples - input…
Spatial Metrology of Dopants in Silicon with Exact Lattice Site Precision
Muhammad Usman, Juanita Bocquel, Joe Salfi +6
The aggressive scaling of silicon-based nanoelectronics has reached the regime where device function is affected not only by the presence of individual dopants, but more critically…
Polarization Independent Ground State Optical Transitions in Closely Stacked InAs/GaAs Columnar Quantum Dots
Muhammad Usman
This work presents an analysis of the electronic and optical properties of InAs/GaAs columnar quantum dots (QDs) by performing multi-million-atom tight-binding simulations. The plo…
Radio Signal Classification by Adversarially Robust Quantum Machine Learning
Yanqiu Wu, Eromanga Adermann, Chandra Thapa +3
Radio signal classification plays a pivotal role in identifying the modulation scheme used in received radio signals, which is essential for demodulation and proper interpretation…
Heart Segmentation From MRI Scans Using Convolutional Neural Network
Shakeel Muhammad Ibrahim, Muhammad Sohail Ibrahim, Muhammad Usman +2
Heart is one of the vital organs of human body. A minor dysfunction of heart even for a short time interval can be fatal, therefore, efficient monitoring of its physiological state…
Volumetric Lung Nodule Segmentation using Adaptive ROI with Multi-View Residual Learning
Muhammad Usman, Byoung-Dai Lee, Shi Sub Byon +2
Accurate quantification of pulmonary nodules can greatly assist the early diagnosis of lung cancer, which can enhance patient survival possibilities. A number of nodule segmentatio…
Comparative analysis of error mitigation techniques for variational quantum eigensolver implementations on IBM quantum system
Shaobo Zhang, Charles D. Hill, Muhammad Usman
Quantum computers are anticipated to transcend classical supercomputers for computationally intensive tasks by exploiting the principles of quantum mechanics. However, the capabili…
Architectural Patterns for Designing Quantum Artificial Intelligence Systems
Mykhailo Klymenko, Thong Hoang, Xiwei Xu +4
Utilising quantum computing technology to enhance artificial intelligence systems is expected to improve training and inference times, increase robustness against noise and adversa…
Transversal CNOT gate with multi-cycle error correction
Younghun Kim, Martin Sevior, Muhammad Usman
A scalable and programmable quantum computer holds the potential to solve computationally intensive tasks that classical computers cannot accomplish within a reasonable time frame,…
Reflection Equivariant Quantum Neural Networks for Enhanced Image Classification
Maxwell T. West, Martin Sevior, Muhammad Usman
Machine learning is among the most widely anticipated use cases for near-term quantum computers, however there remain significant theoretical and implementation challenges impeding…
Experimental and Theoretical Study of Polarization-dependent Optical Transitions from InAs Quantum Dots at Telecommunication-Wavelengths (1.3-1.5μm)
Muhammad Usman, Susannah Heck, Edmund Clarke +4
The design of some optical devices such as semiconductor optical amplifiers for telecommunication applications requires polarization-insensitive optical emission at the long wavele…
Drastic Circuit Depth Reductions with Preserved Adversarial Robustness by Approximate Encoding for Quantum Machine Learning
Maxwell T. West, Azar C. Nakhl, Jamie Heredge +4
Quantum machine learning (QML) is emerging as an application of quantum computing with the potential to deliver quantum advantage, but its realisation for practical applications re…
SIT: A Lightweight Encryption Algorithm for Secure Internet of Things
Muhammad Usman, Irfan Ahmed, M. Imran Aslam +2
The Internet of Things (IoT) being a promising technology of the future is expected to connect billions of devices. The increased number of communication is expected to generate mo…
Attention Down-Sampling Transformer, Relative Ranking and Self-Consistency for Blind Image Quality Assessment
Mohammed Alsaafin, Musab Alsheikh, Saeed Anwar +1
The no-reference image quality assessment is a challenging domain that addresses estimating image quality without the original reference. We introduce an improved mechanism to extr…
Impact of alloy disorder on the band structure of compressively strained GaBiAs
Muhammad Usman, Christopher A. Broderick, Zahida Batool +4
The incorporation of bismuth (Bi) in GaAs results in a large reduction of the band gap energy (E) accompanied with a large increase in the spin-orbit splitting energy ($\bigtri…
RVP-FLMS : A Robust Variable Power Fractional LMS Algorithm
Jawwad Ahmad, Muhammad Usman, Shujaat Khan +2
In this paper, we propose an adaptive framework for the variable power of the fractional least mean square (FLMS) algorithm. The proposed algorithm named as robust variable power F…
Magic State Injection on IBM Quantum Processors Above the Distillation Threshold
Younghun Kim, Martin Sevior, Muhammad Usman
The surface code family is a promising approach to implementing fault-tolerant quantum computations. Universal fault-tolerance requires error-corrected non-Clifford operations, in…
Quantum Serverless Paradigm and Application Development using the QFaaS Framework
Hoa T. Nguyen, Bui Binh An Pham, Muhammad Usman +1
Quantum computing has the potential to solve complex problems beyond the capabilities of classical computers. However, its practical use is currently limited due to early-stage qua…
AFP-CKSAAP: Prediction of Antifreeze Proteins Using Composition of k-Spaced Amino Acid Pairs with Deep Neural Network
Muhammad Usman, Jeong A Lee
Antifreeze proteins (AFPs) are the sub-set of ice binding proteins indispensable for the species living in extreme cold weather. These proteins bind to the ice crystals, hindering…
On some sharp spectral inequalities for Schrödinger operators on semi-axis
Pavel Exner, Ari Laptev, Muhammad Usman
In this paper we obtain sharp Lieb-Thirring inequalities for a Schrödinger operator on semi-axis with a matrix potential and show how they can be used to other related problems. A…
Atomistic tight binding study of quantum confined Stark effect in GaBiAs/GaAs quantum wells
Muhammad Usman
Recently, there has been tremendous research interest in novel bismide semiconductor materials (such as GaBiAs) for wavelength-engineered, low-loss optoelectronic devic…
Long-Range Surface-Assisted Molecule-Molecule Hybridization
Marina Castelli, Jack Hellerstedt, Cornelius Krull +4
Metalated phthalocyanines (Pc's) are robust and versatile molecular complexes, whose properties can be tuned by changing their functional groups and central metal atom. The electro…
Understanding Polarization Properties of InAs Quantum Dots by Atomistic Modeling of Growth Dynamics
Vittorianna Tasco, Muhammad Usman, Maria Teresa Todaro +2
A model for realistic InAs quantum dot composition profile is proposed and analyzed, consisting of a double region scheme with an In-rich internal core and an In-poor external shel…
Phonocardiographic Sensing using Deep Learning for Abnormal Heartbeat Detection
Siddique Latif, Muhammad Usman, Rajib Rana +1
Cardiac auscultation involves expert interpretation of abnormalities in heart sounds using stethoscope. Deep learning based cardiac auscultation is of significant interest to the h…
Atomic-level Characterisation of Quantum Computer Arrays by Machine Learning
Muhammad Usman, Yi Z. Wong, Charles D. Hill +1
Atomic level qubits in silicon are attractive candidates for large-scale quantum computing, however, their quantum properties and controllability are sensitive to details such as t…
MINT: Dynamic-Precision CNN Inference with MSDF Digit-Serial Arithmetic on FPGA
Muhammad Usman, Malik Zohaib Nisar, Florian Aschauer +1
We present MINT, a dynamic-precision CNN inference accelerator based on left-to-right (LR) arithmetic. LR arithmetic computes in most-significant-digit-first manner and exposes use…
Perturbation determinant and Levinson's formula for Schrödinger operators with generalized point interaction
M. Fazeel Anwar, Muhammad Usman, Muhammad Danish Zia
We consider the one dimensional Schrödinger operator with properly connecting generalized point interaction at the origin. We derive a trace formula for trace of difference of res…
Fourier analysis of quantum neural network with non-linear data embedding
Haiyue Kang, Martin Sevior, Muhammad Usman
Fourier analysis has become a crucial tool for understanding the expressivity of Variational Quantum Circuit (VQC) models, as well as an important indicator of barren plateaus (BP)…
Fully convolutional 3D neural network decoders for surface codes with syndrome circuit noise
Spiro Gicev, Lloyd C. L. Hollenberg, Muhammad Usman
Artificial Neural Networks (ANNs) are a promising approach to the decoding problem of Quantum Error Correction (QEC), but have observed consistent difficulty when generalising perf…
Fast and Noise-aware Machine Learning Variational Quantum Eigensolver Optimiser
Akib Karim, Shaobo Zhang, Muhammad Usman
The Variational Quantum Eigensolver (VQE) is a hybrid quantum-classical algorithm for preparing ground states in the current era of noisy devices. The classical component of the al…
Dark energy from non-degenerate Higgs-vacuum
Muhammad Usman, Asghar Qadir
Scalar fields are favorite among the possible candidates for the dark energy. Most frequently discussed are those with degenerate minima at . In this paper, a slightl…
An exchange-based surface-code quantum computer architecture in silicon
Charles D. Hill, Muhammad Usman, Lloyd C. L. Hollenberg
Phosphorus donor spins in silicon offer a number of promising characteristics for the implementation of robust qubits. Amongst various concepts for scale-up, the shared-control con…
A Quality Assessment Instrument for Systematic Literature Reviews in Software Engineering
Muhammad Usman, Nauman bin Ali, Claes Wohlin
Context: Systematic literature reviews (SLRs) have become standard practise as part of software engineering research, although their quality varies. To build on the reviews, both f…
Towards automated open source assessment -- An empirical study
Sai Pranav Koyyada, Denim Deshmukh Deepika Badampudi, Vida Ahmadi +1
The open source software (OSS) assessment has become important given the increased adoption of OSS in commercial product development. Researchers proposed many OSS assessment model…
3D Object Localization Using 2D Estimates for Computer Vision Applications
Taha Hasan Masood Siddique, Muhammad Usman
A technique for object localization based on pose estimation and camera calibration is presented. The 3-dimensional (3D) coordinates are estimated by collecting multiple 2-dimensio…
Crosstalk Attacks and Defence in a Shared Quantum Computing Environment
Benjamin Harper, Behnam Tonekaboni, Bahar Goldozian +2
Quantum computing has the potential to provide solutions to problems that are intractable on classical computers, but the accuracy of the current generation of quantum computers su…
Integrating Uncertainty Quantification into Computational Fluid Dynamics Models of Coronary Arteries Under Steady Flow
Muhammad Usman, Peter N. Castillo, Akil Narayan +1
Computational models are continuously integrated in the clinical space, where they support clinicians in disease diagnosis, prognosis, and prevention strategies. While assisting in…
DSLR-CNN: Efficient CNN Acceleration using Digit-Serial Left-to-Right Arithmetic
Malik Zohaib Nisar, Muhammad Sohail Ibrahim, Saeid Gorgin +2
Digit-serial arithmetic has emerged as a viable approach for designing hardware accelerators, reducing interconnections, area utilization, and power consumption. However, conventio…
Millimeter-Wave Communication Testbed Using Digital Coding Dynamic Metasurface Antenna: Practical Design and Implementation
Abdul Jabbar, Mostafa Elsayed, Jalil Ur-Rehman Kazim +7
Dynamic Metasurface Antennas (DMAs) are transforming reconfigurable antenna technology by enabling energy-efficient, cost-effective beamforming through programmable meta-elements,…
L2R-CIPU: Efficient CNN Computation with Left-to-Right Composite Inner Product Units
Malik Zohaib Nisar, Mohammad Sohail Ibrahim, Muhammad Usman +1
This paper proposes a composite inner-product computation unit based on left-to-right (LR) arithmetic for the acceleration of convolution neural networks (CNN) on hardware. The eff…
Automated Quantum Circuit Design with Nested Monte Carlo Tree Search
Pei-Yong Wang, Muhammad Usman, Udaya Parampalli +2
Quantum algorithms based on variational approaches are one of the most promising methods to construct quantum solutions and have found a myriad of applications in the last few year…
NEUROSPF: A tool for the Symbolic Analysis of Neural Networks
Muhammad Usman, Yannic Noller, Corina Pasareanu +2
This paper presents NEUROSPF, a tool for the symbolic analysis of neural networks. Given a trained neural network model, the tool extracts the architecture and model parameters and…
A Meshless method of lines for the numerical solution of Coupled Drinfeld's-Sokolov-Wilson System
Sirajul Haq, Nagina Hassan, S. I. A. Tirmizi +1
This paper applies meshless method of lines, which uses radial basis functions (RBFs) as a spatial collocation scheme to solve the Coupled Drinfeld's-Sokolov-Wilson System. Runge-K…
Dark energy via multi-Higgs doublet models: accelerated expansion of the Universe in inert doublet model scenario
Muhammad Usman
Scalar fields are among the possible candidates for dark energy. This paper is devoted to the scalar fields from the inert doublet model, where instead of one as in the standard mo…
InspectionV3: Enhancing Tobacco Quality Assessment with Deep Convolutional Neural Networks for Automated Workshop Management
Yao Wei, Muhammad Usman, Hazrat Bilal
The problems that tobacco workshops encounter include poor curing, inconsistencies in supplies, irregular scheduling, and a lack of oversight, all of which drive up expenses and wo…
Constraints on Two Higgs Doublet Model Parameters in the light of rare -Decays
Mureed Hussain, Muhammad Usman, Muhammad Ali Paracha +1
We established the allowed parameters of two-Higgs doublet model(2HDM) from flavor physics observables, precisely from rare meson decays. In our analysis most formidable constr…
LUCI on IBM Hardware: Error Suppression with Almost Half Syndrome Density
Younghun Kim, Spiro Gicev, Martin Sevior +1
Long-lived logical qubits are essential for fault-tolerant quantum computation. However, the practical performance of traditional error correction protocols relies on performing sp…
Improving Semiconductor Device Modeling for Electronic Design Automation by Machine Learning Techniques
Zeheng Wang, Liang Li, Ross C. C. Leon +4
The semiconductors industry benefits greatly from the integration of Machine Learning (ML)-based techniques in Technology Computer-Aided Design (TCAD) methods. The performance of M…
Automating Motion Correction in Multishot MRI Using Generative Adversarial Networks
Siddique Latif, Muhammad Asim, Muhammad Usman +2
Multishot Magnetic Resonance Imaging (MRI) has recently gained popularity as it accelerates the MRI data acquisition process without compromising the quality of final MR image. How…
Polarization Response in InAs Quantum Dots: Theoretical Correlation between Composition and Electronic Properties
Muhammad Usman, Vittorianna Tasco, Maria Teresa Todaro +4
III-V growth and surface conditions strongly influence the physical structure and resulting optical properties of self-assembled quantum dots (QDs). Beyond the design of a desired…
Classical Autoencoder Distillation of Quantum Adversarial Manipulations
Amena Khatun, Muhammad Usman
Quantum neural networks have been proven robust against classical adversarial attacks, but their vulnerability against quantum adversarial attacks is still a challenging problem. H…
Pragmatic Comparison Analysis of Alternative Option Pricing Models
Natasha Latif, Shafqat Ali Shad, Muhammad Usman +5
In this paper, we price European Call three different option pricing models, where the volatility is dynamically changing i.e. non constant. In stochastic volatility (SV) models fo…
Accelerated expansion of the Universe and the Higgs true vacuum
Muhammad Usman, Asghar Qadir
Scalar fields which are favorite among the possible candidates for the dark energy usually have degenerate minima at . In the presented work, we discuss a two Higgs d…
A hardware efficient quantum residual neural network without post-selection
Amena Khatun, Akib Karim, Muhammad Usman
We propose a hardware efficient quantum residual neural network which implements residual connections through a deterministic mixture of the identity operation and variational unit…
Influence of sample momentum space features on scanning tunnelling microscope measurements
Maxwell T. West, Muhammad Usman
Theoretical understanding of scanning tunnelling microscope (STM) measurements involve electronic structure details of the STM tip and the sample being measured. Conventionally, th…
The Diabetic Buddy: A Diet Regulator andTracking System for Diabetics
Muhammad Usman, Kashif Ahmad, Amir Sohail +1
The prevalence of Diabetes mellitus (DM) in the Middle East is exceptionally high as compared to the rest of the world. In fact, the prevalence of diabetes in the Middle East is 17…
Donor hyperfine Stark shift and the role of central-cell corrections in tight-binding theory
Muhammad Usman, Rajib Rahman, Joe Salfi +5
Atomistic tight-binding (TB) simulations are performed to calculate the Stark shift of the hyperfine coupling for a single Arsenic (As) donor in Silicon (Si). The role of the centr…
Dual-Encoder Transformer-Based Multimodal Learning for Ischemic Stroke Lesion Segmentation Using Diffusion MRI
Muhammad Usman, Azka Rehman, Muhammad Mutti Ur Rehman +2
Accurate segmentation of ischemic stroke lesions from diffusion magnetic resonance imaging (MRI) is essential for clinical decision-making and outcome assessment. Diffusion-Weighte…
Atomistic tight-binding study of electronic structure and interband optical transitions in GaBiAs/GaAs quantum wells
Muhammad Usman, Eoin P. O'Reilly
Large-supercell tight-binding calculations are presented for GaBiAs/GaAs single quantum wells (QWs) with Bi fractions of 3.125% and 12.5%. Our results highlight s…
Provably Trainable Rotationally Equivariant Quantum Machine Learning
Maxwell T. West, Jamie Heredge, Martin Sevior +1
Exploiting the power of quantum computation to realise superior machine learning algorithmshas been a major research focus of recent years, but the prospects of quantum machine lea…
Multilingual Hate Speech Detection in Social Media Using Translation-Based Approaches with Large Language Models
Muhammad Usman, Muhammad Ahmad, M. Shahiki Tash +3
Social media platforms are critical spaces for public discourse, shaping opinions and community dynamics, yet their widespread use has amplified harmful content, particularly hate…
QSimPy: A Learning-centric Simulation Framework for Quantum Cloud Resource Management
Hoa T. Nguyen, Muhammad Usman, Rajkumar Buyya
Quantum cloud computing is an emerging computing paradigm that allows seamless access to quantum hardware as cloud-based services. However, effective use of quantum resources is ch…
Theory of the electronic structure of dilute bismide and bismide-nitride alloys of GaAs: Tight-binding and k.p models
Muhammad Usman, Christopher A Broderick, Eoin P. O'Reilly
The addition of dilute concentrations of bismuth (Bi) into GaAs to form GaBiAs alloys results in a large reduction of the band gap energy Eg accompanied by a significant increase o…
Variational Quantum Machine Learning with Quantum Error Detection
Eromanga Adermann, Hajime Suzuki, Muhammad Usman
Quantum machine learning (QML) is an emerging field that promises advantages such as faster training, improved reliability and superior feature extraction over classical counterpar…
MSRNet: A Multi-Scale Recursive Network for Camouflaged Object Detection
Leena Alghamdi, Muhammad Usman, Hafeez Anwar +2
Camouflaged object detection is an emerging and challenging computer vision task that requires identifying and segmenting objects that blend seamlessly into their environments due…
Automatizing the search for mass resonances using BumpNet
Jean-François Arguin, Georges Azuelos, Ãmile Baril +15
Physics Beyond the Standard Model (BSM) has yet to be observed at the Large Hadron Collider (LHC), motivating the development of model-agnostic, machine learning-based strategies t…
Quantum computer error structure probed by quantum error correction syndrome measurements
Spiro Gicev, Lloyd C. L. Hollenberg, Muhammad Usman
With quantum devices rapidly approaching qualities and scales needed for fault tolerance, the validity of simplified error models underpinning the study of quantum error correction…
NNrepair: Constraint-based Repair of Neural Network Classifiers
Muhammad Usman, Divya Gopinath, Youcheng Sun +2
We present NNrepair, a constraint-based technique for repairing neural network classifiers. The technique aims to fix the logic of the network at an intermediate layer or at the la…
QFOR: A Fidelity-aware Orchestrator for Quantum Computing Environments using Deep Reinforcement Learning
Hoa T. Nguyen, Muhammad Usman, Rajkumar Buyya
Quantum cloud computing enables remote access to quantum processors, yet the heterogeneity and noise of available quantum hardware create significant challenges for efficient resou…
Multi-Task Adversarial Variational Autoencoder for Estimating Biological Brain Age with Multimodal Neuroimaging
Muhammad Usman, Azka Rehman, Abdullah Shahid +5
Despite advances in deep learning for estimating brain age from structural MRI data, incorporating functional MRI data is challenging due to its complex structure and the noisy nat…
KaFHCa: Key-establishment via Frequency Hopping Collisions
Muhammad Usman, Simone Raponi, Marwa Qaraqe +1
The massive deployment of IoT devices being utilized by home automation, industrial and military scenarios demands for high security and privacy standards to be achieved through in…
Tight-binding analysis of the electronic structure of dilute bismide alloys of GaP and GaAs
Muhammad Usman, Christopher A. Broderick, Andrew Lindsay +1
We develop an atomistic, nearest-neighbor sp3s* tight-binding Hamiltonian to investigate the electronic structure of dilute bismide alloys of GaP and GaAs. Using this model we calc…
Experimental and Atomistic Theoretical Study of Degree of Polarization from Multi-layer InAs/GaAs Quantum Dots
Muhammad Usman, Tomoya Inoue, Yukihiro Harda +2
Recent experimental measurements, without any theoretical guidance, showed that isotropic polarization response can be achieved by increasing the number of QD layers in a QD stack.…