International Conference on Emergent and Quantum Technologies (ICEQT’22)

July 25-28, 2022 — Las Vegas, NV

Dear Colleagues,

Quantum computing is an emerging interdisciplinary research area at the intersection of mathematics, physics, and engineering. Quantum computing requires experts, and specialists from STEM areas to assure scientific rigor and to keep up with technological advances.

The main goal of organizing ICEQT’22 is to share knowledge about the recent advancements in the field of QML and build a forum for discussions on this topic for researchers working in this field as well as machine learning researchers, attending The 2022 World Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE’22), who are interested in applying AI to enhance quantum computing algorithms.

In recent years, we have observed a significant amount of published research papers in the quantum machine learning domain. There is an increasing interest from machine learning researchers to apply AI to the quantum computing domain (and vice versa). Therefore, we invite all contributions in the following areas:

AI for Quantum
* Machine learning for improved quantum algorithm performance
* Machine learning for quantum control
* Machine learning for building better quantum hardware
Quantum technologies and applications
* Quantum computing: models and paradigms
* Fairness/ethics with quantum machine learning
* Quantum algorithms for hyperparameter tuning (Quantum computing for AutoML)
* Theory of Quantum-enhanced Machine Learning
* Quantum Machine Learning Algorithms based on Grover search
* Quantum-enhanced Reinforcement Learning
* Quantum computing, models and paradigms such as Quantum Annealing,
* Quantum Sampling
Quantum computing foundations
* Quantum computing: models and paradigms
* Applications of Quantum Machine Learning
* Quantum Tensor Networks and their Applications in QML
* Quantum algorithms for Linear Systems of Equations, and other algorithms such as Quantum Neural Networks, Quantum Hidden Markov Models, Quantum PCA, Quantum SVM, Quantum Autoencoders, Quantum Transfer Learning, Quantum Boltzmann machines, Grover, Shor, and others.

You are invited to submit a paper for consideration. ALL ACCEPTED PAPERS will be published in the corresponding proceedings by Publisher:
Springer Nature – Book Series: Transactions on Computational Science & Computational Intelligence

Prospective authors are invited to submit their papers by uploading them to the evaluation website at:

For more information, visit our website:

Important Deadlines

March 31, 2022: Submission of papers:
– Full/Regular Research Papers (maximum of 10 pages)
– Short Research Papers (maximum of 6 pages)
– Abstract/Poster Papers (maximum of 3 pages)

April 18, 2022: Notification of acceptance (+/- two days)

May 12, 2022: Final papers + Registration

June 22, 2022: Hotel Room reservation (for those who are physically attending the conference).

July 25-28, 2022: The 2022 World Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE’22: USA)
Which includes the International Conference on Emergent and Quantum Technologies (ICEQT’22)

Dr. Javier Orduz, Baylor University
Dr. Pablo Rivas, Baylor University

A review of Earth Artificial Intelligence

In recent years, Earth system sciences are urgently calling for innovation on improving accuracy, enhancing model intelligence level, scaling up operation, and reducing costs in many subdomains amid the exponentially accumulated datasets and the promising artificial intelligence (AI) revolution in computer science. This paper presents work led by the NASA Earth Science Data Systems Working Groups and ESIP machine learning cluster to give a comprehensive overview of AI in Earth sciences. It holistically introduces the current status, technology, use cases, challenges, and opportunities, and provides all the levels of AI practitioners in geosciences with an overall big picture and to “blow away the fog to get a clearer vision” about the future development of Earth AI. The paper covers all the major spheres in the Earth system and investigates representative AI research in each domain. Widely used AI algorithms and computing cyberinfrastructure are briefly introduced. The mandatory steps in a typical workflow of specializing AI to solve Earth scientific problems are decomposed and analyzed. Eventually, it concludes with the grand challenges and reveals the opportunities to give some guidance and pre-warnings on allocating resources wisely to achieve the ambitious Earth AI goals in the future. [pdf, bib]

Challenges and opportunities.