## July 22-25, 2024 — Las Vegas, NV

Dear Esteemed Colleagues,

Quantum computing is an expeditiously evolving field of interdisciplinary research, drawing upon fundamental principles from mathematics, physics, and engineering. To maintain scientific rigor and foster advancement, this domain necessitates a collaborative effort across various STEM disciplines.

We are delighted to announce the International Conference on Emergent and Quantum Technologies (ICEQT’24), scheduled for July 22-25, 2024, in Las Vegas, NV. The conference is designed to serve as a platform for researchers specializing in quantum machine learning and machine learning professionals exploring the application of AI in enhancing quantum computing algorithms. It aims to facilitate the exchange of insights and developments within these dynamic areas of study.

The burgeoning interest among machine learning practitioners in leveraging AI for quantum computing endeavors, and vice versa, underscores the relevance of this conference. Thus, we warmly welcome the submission of original research papers that contribute novel insights and state-of-the-art developments in the following areas of interest:

**Foundations of Quantum Computing and Quantum Machine Learning**

- Quantum computing models and paradigms, e.g., Grover, Shor, and others
- Quantum algorithms for Linear Systems of Equations
- Quantum Tensor Networks and their Applications in QML

**Quantum Machine Learning Algorithms**

- Quantum Neural Networks
- Quantum Hidden Markov Models
- Quantum PCA
- Quantum SVM
- Quantum Autoencoders
- Quantum Transfer Learning
- Quantum Boltzmann machines
- Theory of Quantum-enhanced Machine Learning

**AI for Quantum Computing**

- Machine learning for improved quantum algorithm performance
- Machine learning for quantum control
- Machine learning for building better quantum hardware

**Quantum Algorithms and Applications**

- Quantum computing: models and paradigms
- Quantum algorithms for hyperparameter tuning (Quantum computing for AutoML)
- Quantum-enhanced Reinforcement Learning
- Quantum Annealing
- Quantum Sampling
- Applications of Quantum Machine Learning

**Fairness and Ethics in Quantum Machine Learning**

**We look forward to receiving your submissions** and to welcoming you to ICEQT’24.

All submissions that are accepted for presentation will be included in the proceedings published by IEEE CPS. To ensure consistency in formatting, authors should follow the general typesetting instructions available on the IEEE’s website, including single-line spacing and a 2-column format. Additionally, authors of accepted papers must agree to the IEEE CPS standard statement regarding copyrights and policies on electronic dissemination.

Prospective authors are encouraged to submit their papers through the conference’s evaluation website at CMT. More information about the conference, including submission guidelines, can be found on our website at https://baylor.ai/iceqt/.

## Important Deadlines

**March 22, 2024:** Submission of papers: https://cmt3.research.microsoft.com/ICEQT2024

– Full/Regular Research Papers (maximum of 8 pages)

– Short Research Papers (maximum of 5 pages)

– Abstract/Poster Papers (maximum of 3 pages)

**April 15, 2024:** Notification of acceptance (+/- two days)

**May 1, 2024:** Final papers + Registration

**June 21, 2024: **Last day for hotel room reservation at a discounted price.

**July 22-25, 2024:** The 2024 World Congress in Computer Science, Computer Engineering, and Applied Computing (CSCE’24: USA)

Which includes the **International Conference on Emergent and Quantum Technologies** (ICEQT’24)

Chairs:

Pablo Rivas, PhD, Baylor University

Bikram Khanal, PhD Candidate, Baylor University