报告主题：Machine Learning for Quantum Materials and Algorithms

报告人：张亿

报告人单位：yl9193永利官网

主办：前沿计算研究中心

时间：2021年04月19日 上午11:00点

地点： 静园五院101室

讲座摘要

Today, we face significant scientific challenges because the large-scale data acquired by our instrumentation and algorithm and the vast degrees of freedom of our target subjects are constantly defying human analysis. Here we sketch how machine learning techniques may serve as useful tools in overcoming data largeness and noisiness, in reverse thinking, and in bridging fields or even disciplines, such as between computation, experiment, and theory. We report developments in machine learning approaches in recognizing various phases from quantum many-body states and validating theory-hypothesized order hidden through large, complex electronic quantum matter data, and developing efficient and general quantum compiling algorithms at the dawn of quantum computation. We also outline our progress in using machine learning to analyze many-body Hamiltonian ground-state property from a novel perspective.

报告人介绍

Dr. Yi Zhang is a theoretical condensed matter physicist focusing on emergent phenomena and novel approaches in quantum materials, systems, and algorithms. He obtained his undergraduate degree at the Department of Physics, Fudan University, and hisPh.D. degree at UC Berkeley under advisor Prof. Ashvin Vishwanath. Afterward, Dr. Zhang moved to Stanford University as a SITP postdoctoral fellow and later joined Cornell University as a Bethe fellow. He joined International Center for Quantum Materials and School of Physics at Peking University in 2019 as a junior faculty member. Yi Zhang is interested in various quantum algorithm applications, including machine learning and quantum entanglement in quantumsystems, theoretical characterizations and experimental properties of topological phases and materials, and various other topics. Dr. Zhang, Yi has published more than 40 papers in internationally recognizable journals, including Nature, Nature Physics, PRL, Nature communications, Nano Lett. and others.

报告主题：Pushing the Limits of Acoustic Sensing

报告人：熊杰

报告人单位：马萨诸塞大学阿默斯特分校

主办：软件研究所

时间：2021年4月20日 下午15：00

地点：理科二号楼2736报告厅

讲座摘要

Wireless technologies have achieved great success in data communication. In recent years, wireless signals are exploited  for sensing, enabling exciting new applications including passive localization, gesture recognition, respiration sensing and even material identification. Among these wireless signals, acoustic signals show a unique advantage for fine-grained sensing owing to the low propagating speed (340m/s) in the air. Promising progress has been achieved in subtle motion sensing such as respiration monitoring, finger tracking and even eye blink detection using acoustic signals. In this talk, the latest progress and research methodologies in acoustic sensing will be discussed.

报告人介绍

Jie Xiong is currently an Assistant Professor with the College of Information and Computer Sciences, University of Massachusetts Amherst. Jie Xiong received his PhD, MS and BEng degrees from University College London, Duke University and Nanyang Technology University respectively. He was a recipient of the Google European Doctoral Fellowship and the British Computer Society Distinguished Dissertation Award Runner-Up. His current research interests include wireless sensing and mobile computing. His recent work appeared at MobiCom, UbiComp, SenSys, CoNEXT, INFOCOM and NSDI. His work won Best Paper Award at CoNEXT 2014, Best Paper Candidate at SenSys 2019 and Best Paper Honorable Mention at MobiCom 2020.