Undergraduate Research and Education in Quantum Machine Learning

Glen Uehara; Jean Larson; Wendy Barnard; Michael Esposito; Filippo Posta; Maxwell Yarter; Aradhita Sharma; Niki Kyriacou; Matthew Dobson; Andreas Spanias

doi:10.1109/FIE56618.2022.9962749

Undergraduate Research and Education in Quantum Machine Learning

Glen Uehara, Jean Larson, Wendy Barnard, Michael Esposito, Filippo Posta, Maxwell Yarter, Aradhita Sharma, Niki Kyriacou, Matthew Dobson, Andreas Spanias

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

2 Scopus citations

Abstract

This Work-In-Progress paper describes a program in quantum machine learning launched in the academic year of 2021-22. The program engaged undergraduate students from STEM areas with faculty and industry mentors. Because of the COVID-19 conditions, this undergraduate engagement was offered in a virtual format. In 2022, some face-to-face meetings with presentations were also held. The program included: a) training in machine learning with quantum simulators, b) weekly presentations, and c) semester end presentations. The assessment of the program included surveys, interviews, and presentation observations. Challenges and opportunities from virtual engagement were also part of the assessment.

Original language	English (US)
Title of host publication	2022 IEEE Frontiers in Education Conference, FIE 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781665462440
DOIs	https://doi.org/10.1109/FIE56618.2022.9962749
State	Published - 2022
Event	2022 IEEE Frontiers in Education Conference, FIE 2022 - Uppsala, Sweden Duration: Oct 8 2022 → Oct 11 2022

Publication series

Name	Proceedings - Frontiers in Education Conference, FIE
Volume	2022-October
ISSN (Print)	1539-4565

Conference

Conference	2022 IEEE Frontiers in Education Conference, FIE 2022
Country/Territory	Sweden
City	Uppsala
Period	10/8/22 → 10/11/22

Keywords

AI
machine learning
quantum audio and image processing
quantum computing

ASJC Scopus subject areas

Software
Education
Computer Science Applications

Access to Document

10.1109/FIE56618.2022.9962749

Cite this

Uehara, G., Larson, J., Barnard, W., Esposito, M., Posta, F., Yarter, M., Sharma, A., Kyriacou, N., Dobson, M., & Spanias, A. (2022). Undergraduate Research and Education in Quantum Machine Learning. In 2022 IEEE Frontiers in Education Conference, FIE 2022 (Proceedings - Frontiers in Education Conference, FIE; Vol. 2022-October). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/FIE56618.2022.9962749

Undergraduate Research and Education in Quantum Machine Learning. / Uehara, Glen; Larson, Jean; Barnard, Wendy et al.
2022 IEEE Frontiers in Education Conference, FIE 2022. Institute of Electrical and Electronics Engineers Inc., 2022. (Proceedings - Frontiers in Education Conference, FIE; Vol. 2022-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Uehara, G, Larson, J, Barnard, W, Esposito, M, Posta, F, Yarter, M, Sharma, A, Kyriacou, N, Dobson, M & Spanias, A 2022, Undergraduate Research and Education in Quantum Machine Learning. in 2022 IEEE Frontiers in Education Conference, FIE 2022. Proceedings - Frontiers in Education Conference, FIE, vol. 2022-October, Institute of Electrical and Electronics Engineers Inc., 2022 IEEE Frontiers in Education Conference, FIE 2022, Uppsala, Sweden, 10/8/22. https://doi.org/10.1109/FIE56618.2022.9962749

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abstract = "This Work-In-Progress paper describes a program in quantum machine learning launched in the academic year of 2021-22. The program engaged undergraduate students from STEM areas with faculty and industry mentors. Because of the COVID-19 conditions, this undergraduate engagement was offered in a virtual format. In 2022, some face-to-face meetings with presentations were also held. The program included: a) training in machine learning with quantum simulators, b) weekly presentations, and c) semester end presentations. The assessment of the program included surveys, interviews, and presentation observations. Challenges and opportunities from virtual engagement were also part of the assessment.",

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AB - This Work-In-Progress paper describes a program in quantum machine learning launched in the academic year of 2021-22. The program engaged undergraduate students from STEM areas with faculty and industry mentors. Because of the COVID-19 conditions, this undergraduate engagement was offered in a virtual format. In 2022, some face-to-face meetings with presentations were also held. The program included: a) training in machine learning with quantum simulators, b) weekly presentations, and c) semester end presentations. The assessment of the program included surveys, interviews, and presentation observations. Challenges and opportunities from virtual engagement were also part of the assessment.

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Undergraduate Research and Education in Quantum Machine Learning

Abstract

Publication series

Conference

Keywords

ASJC Scopus subject areas

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