6 citations · 19 across the 14 of their papers we have counts for
17 papers
Agentic Multi-Turn Reasoning: A Fairness Approach
Thanh-Dat Truong, Sankalp Pandey, Hugh Churchill +3
Recent advances in Large Language Models (LLMs) have enabled agentic systems capable of solving complex tasks through multi-turn planning, tool use, verification, and memory update…
QuPAINT: Physics-Aware Multimodal Reasoning for Quantum Material Characterization
Sankalp Pandey, Xuan-Bac Nguyen, Hoang-Quan Nguyen +4
Characterizing two-dimensional (2D) quantum materials by optical microscopy requires localizing exfoliated flakes and determining their layer thickness from subtle optical contrast…
OpenQlaw: An Agentic AI Assistant for Analysis of 2D Quantum Materials
Sankalp Pandey, Xuan-Bac Nguyen, Thanh-Dat Truong +5
Physics-aware multimodal large language models (MLLMs) can localize and characterize two-dimensional (2D) material flakes from optical microscopy images, producing rich candidate o…
QuPAINT: Physics-Aware Instruction Tuning Approach to Quantum Material Discovery
Xuan-Bac Nguyen, Hoang-Quan Nguyen, Sankalp Pandey +4
Characterizing two-dimensional quantum materials from optical microscopy images is challenging due to the subtle layer-dependent contrast, limited labeled data, and significant var…
CLIFF: Continual Learning for Incremental Flake Features in 2D Material Identification
Sankalp Pandey, Xuan Bac Nguyen, Nicholas Borys +2
Identifying quantum flakes is crucial for scalable quantum hardware; however, automated layer classification from optical microscopy remains challenging due to substantial appearan…
-Adapt: A Physics-Informed Adaptation Learning Approach to 2D Quantum Material Discovery
Hoang-Quan Nguyen, Xuan Bac Nguyen, Sankalp Pandey +4
Characterizing quantum flakes is a critical step in quantum hardware engineering because the quality of these flakes directly influences qubit performance. Although computer vision…
Quantum-Brain: Quantum-Inspired Neural Network Approach to Vision-Brain Understanding
Hoang-Quan Nguyen, Xuan-Bac Nguyen, Hugh Churchill +4
Vision-brain understanding aims to extract semantic information about brain signals from human perceptions. Existing deep learning methods for vision-brain understanding are usuall…
Hierarchical Quantum Control Gates for Functional MRI Understanding
Xuan-Bac Nguyen, Hoang-Quan Nguyen, Hugh Churchill +2
Quantum computing has emerged as a powerful tool for solving complex problems intractable for classical computers, particularly in popular fields such as cryptography, optimization…
Diffusion-Inspired Quantum Noise Mitigation in Parameterized Quantum Circuits
Hoang-Quan Nguyen, Xuan Bac Nguyen, Samuel Yen-Chi Chen +4
Parameterized Quantum Circuits (PQCs) have been acknowledged as a leading strategy to utilize near-term quantum advantages in multiple problems, including machine learning and comb…
Quantum Visual Feature Encoding Revisited
Xuan-Bac Nguyen, Hoang-Quan Nguyen, Hugh Churchill +2
Although quantum machine learning has been introduced for a while, its applications in computer vision are still limited. This paper, therefore, revisits the quantum visual encodin…
QClusformer: A Quantum Transformer-based Framework for Unsupervised Visual Clustering
Xuan-Bac Nguyen, Hoang-Quan Nguyen, Samuel Yen-Chi Chen +3
Unsupervised vision clustering, a cornerstone in computer vision, has been studied for decades, yielding significant outcomes across numerous vision tasks. However, these algorithm…
Hybrid Quantum Tabu Search for Solving the Vehicle Routing Problem
James Holliday, Braeden Morgan, Hugh Churchill +1
There has never been a more exciting time for the future of quantum computing than now. Near-term quantum computing usage is now the next XPRIZE. With that challenge in mind we hav…
Quantum Vision Clustering
Xuan Bac Nguyen, Hugh Churchill, Khoa Luu +1
Unsupervised visual clustering has garnered significant attention in recent times, aiming to characterize distributions of unlabeled visual images through clustering based on a par…
Voltage Activated Parametric Entangling Gates on Gatemons
Yinqi Chen, Konstantin N. Nesterov, Hugh Churchill +3
We describe the generation of entangling gates on superconductor-semiconductor hybrid qubits by ac voltage modulation of the Josephson energy. Our numerical simulations demonstrate…
Fairness in Visual Clustering: A Novel Transformer Clustering Approach
Xuan-Bac Nguyen, Chi Nhan Duong, Marios Savvides +3
Promoting fairness for deep clustering models in unsupervised clustering settings to reduce demographic bias is a challenging goal. This is because of the limitation of large-scale…
Two-Dimensional Quantum Material Identification via Self-Attention and Soft-labeling in Deep Learning
Xuan Bac Nguyen, Apoorva Bisht, Ben Thompson +3
In quantum machine field, detecting two-dimensional (2D) materials in Silicon chips is one of the most critical problems. Instance segmentation can be considered as a potential app…
Defining Quantum Neural Networks via Quantum Time Evolution
Aditya Dendukuri, Blake Keeling, Arash Fereidouni +3
This work presents a novel fundamental algorithm for for defining and training Neural Networks in Quantum Information based on time evolution and the Hamiltonian. Classical Neural…