[演講公告] Graph Computing for Network Science and Machine Intelligence, Dr. Ching-Yung Lin (Chief Scientist , IBM Watson Lab, USA)
最後更新時間: 2017-03-09 18:20:27
日期：3/16 (四) 10:10am-12:00pm
題目：Graph Computing for Network Science and Machine Intelligence
主講者：Dr. Ching-Yung Lin 服務單位：Chief Scientist , IBM Watson Lab, USA
The human brain is a giant graph, performing four major functions: memorization, observation, judgment & perception, and abstract reasoning & strategy. Graphs are our natural way to remember, correlate, and understand all that surrounds us. To mimic the human experience of intelligence, graph computing can play a key role. We define graph computing machines as those that store, analyze, and interpret data through graph databases, graph topological analytics, and with probabilistic graphical models such as artificial neural networks, Bayesian networks, or game-theoretical networks.
Ching Yung Lin is the Chief Scientist in IBM T. J. Watson Research Center. He is also an Adjunct Professor in Columbia University since 2005 and in NYU since 2014. His research interest is mainly on fundamental research of multimodality signal understanding, network computing, and computational social & cognitive sciences, and applied research on security, commerce, and collaboration. Since 2011, Lin has been leading a team of more than 40 Ph.D. researchers in worldwide IBM Research Labs and more than 20 professors and researchers in 9 universities. He is the Principle Investigator of projects on Graph Computing and Social Cognitive Analytics. Ching-Yung is an author of 160+ publications and 19 issued patents. His team recently won the Best Paper Award in BigData 2013, Best Paper Award in CIKM 2012, and Best Theme Paper Award in ICIS 2011. He is a Fellow of IEEE.
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