Quantum Computing
The realization of the potential benefits of quantum computing to a variety of research computing paradigms and to society as whole is a tantalizing prospect. Certain research computing paradigms, such as optimization problems and search and factoring algorithms, are reaping the advantages of computing approaches influenced by the implementation of quantum mechanical principles. Development of hardware based on the same is producing novel compute environments using trapped ions, superconducting transmons and photonic elements. Discovering the ways in which quantum computing ideas and manifestations can integrate with current classical systems to enhance computation as a whole is a central focus of the Quantum Collaborative. Uniting industry, academia and national laboratories toward advancing high-performance computing is one example of the Collaborative’s aspirations to leverage quantum techniques to solve those most elusive of global challenges.
Steering committee
Ying-Cheng Lai
Regents Professor, School of Electrical, Computer and Energy Engineering, Arizona State University
Expertise: Quantum Control and Information, Machine Learning, Quantum Chaos, 2D Dirac Materials Physics, Complex Networks, Nonlinear Dynamics
David Ferry
Emeritus Professor, School of Electrical, Computer and Energy Engineering, Arizona State University
Expertise: Quantum transport in condensed matter and semiconductor devices
Andreas Spanias
Professor and Senior Global Futures Scientist, Arizona State University
Expertise: Machine Learning, Signal Processing and Communications
John Fowler
Motorola Professor of International Business, Arizona State University
Expertise: Simulation, Optimization, Scheduling
Vladimiro Mujica
Professor, School of Molecular Sciences, Arizona State University
Expertise: Molecular Quantum Information Sciences, Quantum Sensing, Quantum Biology
Vaneet Aggarwal
Professor, School of Industrial Engineering, Purdue University
Expertise: Reinforcement Learning, Generative AI, Quantum Machine Learning, Federated Learning, Applications of ML in Networking, Transportation, Robotics, Manufacturing, Healthcare, Biomedical, and Climate
Panagiotis (Panos) P. Markopoulos
Margie and Bill Klesse Endowed Associate Professor, Departments of Electrical & Computer Engineering and Computer Science, The University of Texas at San Antonio
Expertise: Machine Learning; Signal Processing; Efficient and Robust Optimization
Aviral Shrivastava
Professor, School of Computing Informatics and Decision Systems Engineering, School of Electrical Computer and Energy Engineering, Arizona State University
Expertise: Quantum Machine Learning, Quantum Algorithms
Houlong Zhuang
Assistant Professor, School for Engineering of Matter, Transport and Energy, Arizona State University
Expertise: Quantum Simulations, Machine Learning, and Quantum Computing
Gennaro De Luca
Assistant Teaching Professor, School of Computing and Augmented Intelligence, Arizona State University
Expertise: Quantum/Classical Machine Learning and Algorithms, Software Verification, Computer Science Education
David Liu
Associate Professor of Computer Science, Rosen Center for Advanced Computing, Purdue University
Expertise: Quantum Computing and Algorithm Design, Quantum/Classical Machine Learning, Quantum Optimization, Distributed Quantum Computing, Cybersecurity
Mostafa Hajiaghaeikeshteli
Associate Research Professor, Department of Industrial Engineering, School of Engineering and Science, Tecnológico de Monterrey
Expertise: Metaheuristics, Optimization, Stochastic Processes, AI, Supply Chain, Energy
Douglas Jennewein
Senior Director, Research Computing, Research Technology Office, Arizona State University
Expertise: Classical Computer Science, High Performance Computing, cyberinfrastructure workforce development and professionalization
Gil Speyer
Director, Research Technology Office, Computational Research Accelerator, Arizona State University
Expertise: Quantum Computing simulation environments, HPC, numerical methods
Torey Battelle
Associate Director, Research Technology Office, Arizona State University
Expertise: Quantum Information Theory, Condensed Matter Physics, High-Performance Computing
César Vargas-Rosales
Leader, Innovation in Smart Digital Technologies and Infrastructure, Tecnológico de Monterrey
Expertise: Wireless Communications, Signal Processing, Quantum Optimization, Quantum Error Correcting Codes, Quantum Routing, Stochastic Modeling
Glen S Uehara
Senior Research Associate, Arizona State University
Expertise: Quantum Computing, Quantum Networking, Quantum Algorithms, Machine Learning, Signal Processing
Burns Healy
Emerging Technologies Researcher, Dell Technologies
Expertise: Hybrid Quantum-Classical Workflows, Optimization with Quantum Technologies, QPU Emulation
Miguel Paredes Quiñones
Research Scientist, Dell Technologies
Expertise: Quantum Optimization, Quantum Annealing, Hybrid computing
Acknowledgment Statement for the Quantum Collaborative
Publications/proposals/projects/research using resources provided by the Quantum Collaborative are requested to include the following acknowledgment statement:
The Quantum Collaborative, led by Arizona State University, provided valuable expertise and resources for this (research/proposal/publication/project). The Quantum Collaborative connects top scientific programs, initiatives, and facilities with prominent industry partners to advance the science and engineering of quantum information science.
