Join us for “Witness the New Era of Quantum Computing: Enhancing Reliability and Transparency through Noise Analysis and Visualization in the NISQ Era” a keynote presentation by Dr. Qiang Guan, College of Engineering – Electrical Engineering & Computer Science, MizzouForward faculty candidate.  Dr. Guan will present on his research for approximately 40-minutes with a 20-minute question and answer session to follow.

Dr. Qiang Guan is an assistant professor in the Department of Computer Science at Kent State University, Kent, Ohio. Dr. Guan is the director of the Green Ubiquitous Autonomous Networking System lab (GUANS). He is also a member of the Brain Health Research Institute (BHRI) at Kent State University. He was a computer scientist in Data Science at Scale team at Los Alamos National Laboratory before joining KSU. His current research interests include fault tolerance design for HPC applications, HPC-cloud hybrid systems, virtual reality, quantum computing systems, and applications.  His research has spanned over HPC, Cloud, AI, and Quantum Computing. He has published 20+ publications in quantum computing in different subareas, noise prediction, noise mitigation, error suppression, quantum system simulation, compiler optimization, and quantum visualization. He has won the best paper of QCE 2023, which is the flagship quantum computing conference. He also leads the collaboration of quantum computing with Cleveland Clinic. Besides, he has seven active NSF and NIH grants serving as PIs with total funding of $4M+.

As quantum computing evolves with contributions from leading industries such as IBM, Rigetti, and Google, the challenges posed by noise in Noisy Intermediate-Scale Quantum (NISQ) computers remain a critical barrier to realizing their full potential. This talk presents innovative approaches to tackling these challenges by analyzing quantum noise patterns, predicting hardware quality, and mitigating errors through cutting-edge methods. Their research focuses on developing multivariate noise prediction models, profiling quantum readout errors, and designing a Just-in-Time noise-adaptive compilation framework. These solutions aim to provide a transparent and interactive visualization system, empowering quantum application developers to make informed decisions about hardware selection and circuit optimization.

You can access Dr. Guan’s CV via OneDrive here:  Academic_CV_2024_QG.pdf (University log in required to access)

After the keynote, please provide candidate feedback with our brief survey.