Ramin Ayanzadeh
Ramin Ayanzadeh


Alumnus, Ph.D. Alumnus, Visitor

University of Maryland, Baltimore County
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.

Ramin Ayanzadeh

Refereed Publications


  1. 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.
  2. 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.
  3. R. Ayanzadeh, M. Halem, and T. Finin, "Reinforcement Quantum Annealing: A Hybrid Quantum Learning Automata", Article, Nature Scientific Reports, May 2020, 128 downloads.
  4. R. Ayanzadeh, "Leveraging Artificial Intelligence to Advance Problem-Solving with Quantum Annealers", PhdThesis, University of Maryland, Baltimore County, May 2020, 273 downloads.
  5. 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.


  1. R. Ayanzadeh, M. Halem, and T. Finin, "Compressive Geospatial Analytics", InProceedings, American Geophysical Union, Fall Meeting 2019, December 2019.
  2. R. Ayanzadeh, M. Halem, J. E. Dorband, and T. Finin, "Quantum-Assisted Greedy Algorithms", Article, arXiv:1912.02362 [quant-ph], December 2019, 151 downloads.
  3. 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.
  4. R. Ayanzadeh, M. Halem, and T. Finin, "SAT-based Compressive Sensing", Article, arXiv:1903.03650 [cs.IT], March 2019, 247 downloads.
  5. 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.


  1. 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.
  2. 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.