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<b><u><span style="font-size:32.0pt;line-height:115%;font-family:"Segoe UI Symbol",sans-serif">EECS Research Seminar Talk</span></u></b><b><span style="font-size:20.0pt;line-height:115%;font-family:"Segoe UI Symbol",sans-serif"><br>
</span></b><b><span style="font-size:22.0pt;line-height:115%;font-family:"Segoe UI Symbol",sans-serif">Dr. Jinyuan Chen</span></b><b><span style="font-size:20.0pt;line-height:115%;font-family:"Segoe UI Symbol",sans-serif"><o:p></o:p></span></b></p>
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<p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:18.0pt;line-height:115%;font-family:"Segoe UI Symbol",sans-serif">Coding Theory for Distributed Consensus
<o:p></o:p></span></b></p>
<p class="MsoNormal" align="center" style="text-align:center"><b><span style="font-size:18.0pt;line-height:115%;font-family:"Segoe UI Symbol",sans-serif">Friday, March 24, 2023<br>
11:45 am – 12:50 pm<br>
Academic and Research Center (ARC) 315<o:p></o:p></span></b></p>
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<p class="MsoNormal" style="text-align:justify"><b><u><span style="font-size:10.5pt;line-height:115%;font-family:"Segoe UI Symbol",sans-serif">ABSTRACT<o:p></o:p></span></u></b></p>
<p class="MsoNormal" style="text-align:justify">Distributed consensus is a fundamental problem in distributed computing and cryptography, where distributed processors want to reach consensus on some data value in the presence of Byzantine processors who may
arbitrarily deviate from the designed protocol. In a different area, coding theory is a powerful tool for error detection and correction, which has been widely used in data transmission, compression and storage. In this talk we will show how to solve a distributed
consensus problem by using tools from coding theory, together with graph theory and linear algebra. <o:p></o:p></p>
<p class="MsoNormal" style="text-align:justify"><b><u><span style="font-size:10.5pt;line-height:115%;font-family:"Segoe UI Symbol",sans-serif">BIOGRAPHY<o:p></o:p></span></u></b></p>
<p class="MsoNormal" style="text-align:justify">Jinyuan Chen is currently an Associate Professor at Louisiana Tech University. Before joining Louisiana Tech, he was a postdoctoral scholar at Stanford University. He received the Ph.D. degree from Télécom Paris
in 2014, the M.Sc. degree from Beijing University of Posts and Telecommunications in 2010, and the B.Sc. degree from Tianjin University in 2007. His research interests include information theory, distributed consensus, blockchain, and machine learning.<o:p></o:p></p>
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