Alumnus, Ph.D. Alumnus, Visitor
Computer Science and Electrical Engineering, 1000 Hilltop Circle, Baltimore, MD 21250, United States
Graduated in May 2020
I aim to employ quantum computing to address real-world problems that are intractable in the realm of classical computing, and leverage artificial intelligence to advance quantum information processing. As a Google Scholar, I have proposed the first generation of compilers for quantum annealers and awarded the second place in ACM grad SRC competition (sponsored by Microsoft Research). Also, I have proposed a novel post-quantum error correction scheme that can notably improve the quality and reproducibility of results attained by the quantum annealers. Besides, I have introduced two AI hybrid models for quantum annealers, so-called reinforcement quantum annealing (RQA) and greedy quantum annealing (GQA).
From an application viewpoint, I have demonstrated how to address the NP-hard problem of compressive sensing using quantum computers, and I am exploring how to leverage quantum information processing for protein folding applications. In addition to adiabatic quantum computers and quantum annealers, I am interested in gate models; specifically, I am very impressed by cold atoms that can provide a disruptive capability in the post-Moore era. I enjoy listening to audiobooks, and I am a strong advocate of diversity.
- R. Ayanzadeh, J. E. Dorband, M. Halem, and T. Finin, "Post-Quantum Error-Correction for Quantum Annealers", Article, arXiv:2010.00115 [quant-ph], September 2020, 52 downloads.
- R. Ayanzadeh, M. Halem, and T. Finin, "An Ensemble Approach for Compressive Sensing with Quantum Annealers", InProceedings, IEEE International Geoscience and Remote Sensing Symposium, June 2020, 185 downloads.
- R. Ayanzadeh, M. Halem, and T. Finin, "Reinforcement Quantum Annealing: A Hybrid Quantum Learning Automata", Article, Nature Scientific Reports, May 2020, 128 downloads.
- R. Ayanzadeh, "Leveraging Artificial Intelligence to Advance Problem-Solving with Quantum Annealers", PhdThesis, University of Maryland, Baltimore County, May 2020, 273 downloads.
- R. Ayanzadeh, M. Halem, and T. Finin, "Reinforcement Quantum Annealing: A Quantum-Assisted Learning Automata Approach", Article, arXiv:2001.00234 [quant-ph], January 2020, 298 downloads.
- R. Ayanzadeh, M. Halem, and T. Finin, "Compressive Geospatial Analytics", InProceedings, American Geophysical Union, Fall Meeting 2019, December 2019.
- R. Ayanzadeh, M. Halem, J. E. Dorband, and T. Finin, "Quantum-Assisted Greedy Algorithms", Article, arXiv:1912.02362 [quant-ph], December 2019, 151 downloads.
- S. Mousavi, M. Rezaee, and R. Ayanzadeh, "A Survey on Compressive Sensing: Classical Results and Recent Advancements", Article, arXiv:1908.01014, August 2019, 71 downloads.
- R. Ayanzadeh, M. Halem, and T. Finin, "SAT-based Compressive Sensing", Article, arXiv:1903.03650 [cs.IT], March 2019, 247 downloads.
- R. Ayanzadeh, S. Mousavi, M. Halem, and T. Finin, "Quantum Annealing Based Binary Compressive Sensing with Matrix Uncertainty", Article, arXiv:1901.00088 [cs.IT], January 2019, 479 downloads.
- R. Ayanzadeh, M. Halem, and T. Finin, "Solving Hard SAT Instances with Adiabatic Quantum Computers", American Geophysical Union, Fall Meeting 2018, abstract #IN41B-27, December 2018.
- R. Ayanzadeh, "Quantum Artificial Intelligence for Natural Language Processing Applications", InProceedings, SIGCSE '18: Proceedings of the 49th ACM Technical Symposium on Computer Science Education, February 2018.