Quantum Computing

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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.

Contact us to find out how you can engage with the Quantum Collaborative