Quantum Computing for Statisticians and Data Scientists
Quantum Computing for Statisticians and Data Scientists
Abstract
Quantum computing has emerged as the next computing technology paradigm, which promises to transform many critical fields, such as pharmaceutical and fertilizer design, supply chain and traffic optimisation, or optimisation for machine learning tasks. This is an exciting development for statisticians and data scientists because it will give rise to a new evolutionary branch of statistical and data analytics methodologies. This seminar will introduce quantum computing, explain its power and challenges, and provide a few examples of applications of quantum computing to problems of interest to statisticians.
Bio
Dr. Anna Lopatnikova is a Senior Research Fellow with the Discipline of Business Analytics at the University of Sydney Business School, working on applications of quantum computing to practical problems in statistics, machine learning, and finance. Prior to joining the Discipline, she served as a Senior Research Fellow with the Discipline of Finance. She has held senior roles in investment management (Allan Gray, ICAP) and served as management consultant (BCG). She holds a PhD degree in theoretical statistical and quantum physics from Harvard University and an S.B. degree in physics with a minor in mathematics from MIT. She has published in top-tier journals on topics in quantum and statistical physics.