Professor  Irwin King

Prof. Irwin King, an eminent scholar in machine intelligence, is currently a professor at the Department of Computer Science & Engineering, The Chinese University of Hong Kong. His research interests span machine learning, social computing, AI, and data mining. In these fields, he has published over 350 technical works in world-renowned conferences and top journals. He has been named among the world’s top 2% scientists by Stanford University. He is the Director of the Machine Intelligence and Social Computing (MISC) Lab and the ELearning Innovation and Technology (ELITE) Centre. He is a Fellow of IEEE, INNS, AAIA, HKIE, and a Distinguished Member of ACM.

Prof. King has held numerous leadership roles, including serving as the President of the International Neural Network Society and currently as the Vice-Chair of the ACM SIGWEB society as well as the Vice-Chair of the ACM WebConf Steering Committee. He has co-chaired internationally renowned conferences such as ACM WebConf 2020, ICONIP 2020, ACML 2015, ACM RecSys 2013, and ACM WSDM 2011, and also served in leading capacities at conferences such as ACM WebConf (formerly WWW), NIPS, ICML, IJCAI, AAAI, WCCI, IJCNN, and ICONIP.

His outstanding contributions to machine intelligence have earned him several prestigious awards, including the 2021 INNS Dennis Gabor Award for neural network engineering applications, the 2020 APNNS Outstanding Achievement Award, and multiple Test of Time Awards from ACM conferences at CIKM2019, SIGIR 2020, and WSDM 2022 for work done in the theoretical and application of machine learning in social computing.

During his sabbatical at AT&T Labs Research in San Francisco, he also served as a Visiting Professor and taught courses at UC Berkeley. Prof. King earned his B.Sc. in Engineering and Applied Science from the California Institute of Technology (Caltech) and his M.Sc. and Ph.D. degrees in Computer Science from the University of Southern California (USC).

Social Media Profiles:
• LinkedIn: https://www.linkedin.com/in/irwinking/

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• Graph Neural Networks from Theory to Applications
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• Social Recommendations: A historical perspective and recent advancements
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