Quantum Machine Learning: An Interplay Between Quantum Computing and Machine Learning
Speaker: Samuel Yen-Chi Chen (Senior Research Scientist at Wells Fargo)
Date: 13 June 2025
Time: 11:00 AM – 12:00PM ET
Registration Link: https://landing.signalprocessingsociety.org/jun-13-2025
Abstract:
Quantum Machine Learning (QML) represents an exciting frontier where the power of quantum computing meets the versatility of traditional machine learning. This talk will explore how QML leverages the unique principles of quantum physics to potentially revolutionize machine learning, while also using machine learning to push the boundaries of quantum computing research. We will introduce the role of variational quantum circuits (VQC) in designing QML architectures for noisy intermediate-scale quantum (NISQ) devices and share key insights from our recent research. Additionally, I will discuss the role of AI in quantum computing, highlighting the symbiotic relationship between these fields. Finally, we’ll look toward the future, considering both the opportunities and challenges that lie ahead for QML research.
Short Bio:
Samuel Yen-Chi Chen received the Ph.D. and B.S. degree in physics and the M.D. degree in medicine from National Taiwan University, Taipei City, Taiwan.
He is now a senior research scientist at Wells Fargo Bank. Prior to that, he was an assistant computational scientist in the Computational Science Initiative, Brookhaven National Laboratory. He is the first one to use variational quantum circuits to perform deep reinforcement learning and the inventor of quantum LSTM. His research interests include building quantum machine learning algorithms as well as applying classical machine learning techniques to solve quantum computing challenges such as quantum error correction and quantum architecture search. He is involved in multiple advanced privacy-preserving quantum AI research project and is an experienced distributed computing researcher and developer. He won the First Prize In the Software Competition (Research Category) from Xanadu Quantum Technologies, in 2019.
Dr. Chen is a seasoned speaker renowned for his expertise in delivering tutorials on quantum machine learning at prestigious conferences. Notably, he has presented tutorial talks on leveraging quantum neural networks for speech and natural language processing at IJCAI 2021 and ICASSP 2022. At ICASSP 2024, IJCNN 2024 and IEEE QCE 2024, Dr. Chen expanded on this knowledge, providing tutorials on the integration of quantum tensor networks and quantum neural networks for signal processing in machine learning. Moreover, he shared insights into quantum machine learning and its applications in 6G communication at IEEE ICC 2024.
