SPECIAL QUANTUM SEMINAR - Dr. Min-Hsiu Hsieh

<b>Title: Challenge and Opportunity in Quantum Machine Learning</b><br /><br />
Abstract: Quantum learning machines have been broadly used in various works with different levels of claimed benefits. However, there are still several obstacles ahead, such as read-in, read-out, the effectiveness of learning machines, and ubiquitous quantum noise. In this talk, I will introduce these difficulties and our results to address/resolve them. <br /><br />

Min-Hsiu Hsieh received his BS and MS in electrical engineering from National Taiwan University in 1999 and 2001, and PhD degree in electrical engineering from the University of Southern California, Los Angeles, in 2008. From 2008-2010, he was a Researcher at the ERATO-SORST Quantum Computation and Information Project, Japan Science and Technology Agency, Tokyo, Japan. From 2010-2012, he was a Postdoctoral Researcher at the Statistical Laboratory, the Centre for Mathematical Sciences, the University of Cambridge, UK. From 2012-2020, he joined the Faculty of Engineering and Information Technology, University of Technology Sydney, Australia. He received Australian Research Council (ARC) Future Fellowship and became an Associate Professor at the Centre for Quantum Software and Information, University of Technology Sydney, Australia in 2014. He is now the director of the Hon Hai (Foxconn) quantum computing center. His scientific interests include quantum information, quantum learning, and quantum computation.

<a href="https://uchicago.zoom.us/j/99237231273?pwd=dG1hQUdtcjRJOFdocTRhb1JKQ1Ft…; Zoom Link</a>