Moe Win

Moe Win is a Professor at the Massachusetts Institute of Technology (MIT) and the founding director of the Wireless Information and Network Sciences Laboratory. Prior to joining MIT, he was with AT&T Research Laboratories and NASA Jet Propulsion Laboratory. His research encompasses fundamental theories, algorithm design, and network experimentation for a broad range of real-world problems. Current research topics include network localization and navigation, network interference exploitation, and quantum information science.

Professor Win is a Fellow of the AAAS, the EURASIP, the IEEE, and the IET. He has served the IEEE Communications Society as an elected Member-at-Large on the Board of Governors, as elected Chair of the Radio Communications Committee, and as an IEEE Distinguished Lecturer. He was honored with two IEEE Technical Field Awards: the IEEE Kiyo Tomiyasu Award and the IEEE Eric E. Sumner Award. His publications, co-authored with students and colleagues, have received several awards. Other recognitions include the IEEE Communications Society Edwin H. Armstrong Achievement Award; the Copernicus Fellowship and the Laurea Honoris Causa from the Università degli Studi di Ferrara; and the U.S. Presidential Early Career Award for Scientists and Engineers. He is an ISI Highly Cited Researcher.

Keynote: “Foundation for Localization-of-Things in 5G Ecosystem and Beyond”
Abstract: The availability of real-time, high-accuracy location awareness is essential for numerous wireless applications, particularly those involving Internet-of-Things and the 5G ecosystem. The coming years will see the emergence of network localization and navigation in challenging environments with sub-meter accuracy and minimal infrastructure requirements. This will call for the Localization-of-Things (LoT), a new paradigm referring to locating, tracking, and navigating collaborative and non-collaborative nodes (e.g., sensors, vehicles, and objects). Our work -relying on statistical inference, network optimization, and communication theory- approaches LoT from different perspectives. This talk will give an overview of LoT, examining our recent research results in this exciting new field, from the perspectives of theoretical framework, cooperative algorithms, network operations, and network experimentation.