I-Hsiang Wang received his Ph.D. in Electrical Engineering and Computer Sciences from University of California at Berkeley, USA, in 2011. From 2011 to 2013, he was a postdoctoral research associate in the School of Computer and Communication Sciences (IC) at École Polytechnique Fédérale de Lausanne (EPFL), Switzerland. In Fall 2013, he joined National Taiwan University, where he is now an assistant professor. Prof. Wang’s expertise lies in information theory, statistical learning, and networked information and data processing. He received the Berkeley Vodafone Fellowship in 2006 and 2007. He was a finalist of the Best Student Paper Award of IEEE International Symposium on Information Theory, 2011. He won the 2017 IEEE Information Theory Society Taipei Chapter and IEEE Communications Society Taipei/Tainan Chapters Best Paper Award for Young Scholars, and the 2016 National Taiwan University Distinguished Teaching Award (top 1%). He served on the technical program committees of flagship conferences in information theory, including IEEE International Symposium on Information Theory (ISIT) and IEEE Information Theory Workshop (ITW).
Prof. Wang’s recent research agenda is to leverage information theory and statistical methods to investigate large-scale data extraction and high dimensional unsupervised learning problems, including hypergraph community structure analysis.