![]() His research aims to build language model agents that transform (“grounding”) language instructions into code or actions executable in real-world environments, including databases, web applications, and the physical world etc. His main research interest is in Natural Language Processing. Tao has received the Google and Amazon faculty research awards ( Google Research Scholar Award 2023, Amazon Research Award 2022). in Computer Science from Yale University, advised by Dragomir Radev and master's at Columbia University advised by Owen Rambow and Kathleen McKeown. He spent one year in the UW NLP Group working with Noah Smith, Luke Zettlemoyer, and Mari Ostendorf. He served as an Associate Editor for the IEEE Transactions on Information Theory from 2014 to 2016.Tao Yu is an Assistant Professor of Computer Science at The University of Hong Kong and a director of the XLANG Lab (as part of the HKU NLP Group). ![]() He received several awards for his research, including the Josef Raviv Memorial Postdoctoral Fellowship in 2006, the Early Researcher Award from the Province of Ontario in 2010, and the IBM Faculty Award in 2010. His research interests include information theory, wireless communications, and signal processing. Since September 2007 he has been with the Department of Electrical and Computer Engineering at McMaster University, Hamilton, ON, Canada, where he is currently an Associate Professor and a Joseph Ip Distinguished Engineering Fellow. Watson Research Center, Yorktown Heights, NY, from July 2006 to August 2007. He was a Postdoctoral Research Associate in the Coordinated Science Laboratory at the University of Illinois at Urbana-Champaign, Urbana, IL, from September 2005 to July 2006, and a Postdoctoral Fellow at the IBM Thomas J. degrees in electrical and computer engineering from Cornell University, Ithaca, NY, in 20, respectively. degree with honours in communication engineering from Shanghai Jiao Tong University, Shanghai, China, in 2001 and the M.S. Song, L., Chen, J., and Tian, C., Broadcasting Correlated Vector Gaussians, IEEE Transactions on Information Theory, vol. and Chen, J., Outer Bounds on the Admissible Source Region for Broadcast Channels with Correlated Sources, IEEE Transactions on Information Theory, vol. Xiao, Z., Chen, J., Li, Y., and Wang, J., Distributed Multilevel Diversity Coding, IEEE Transactions on Information Theory, vol. ![]() and Chen, J., A Source-Channel Separation Theorem With Application to the Source Broadcast Problem, IEEE Transactions on Information Theory, vol. Zhou, Y., Xu, Y., Yu, W., and Chen, J., On the Optimal Fronthaul Compression and Decoding Strategies for Uplink Cloud Radio Access Networks, IEEE Transactions on Information Theory, vol. Xu, R., Chen, J., Weissman, T., and Zhang, J., When is Noisy State Information at the Encoder as Useless as No Information or as Good as Noise-Free State?, IEEE Transactions on Information Theory, vol. Tian, C., Chen, J., Diggavi, S., and Shamai, S., Matched Multiuser Gaussian Source Channel Communications via Uncoded Schemes, IEEE Transactions on Information Theory, vol. Chen served as an Associate Editor for the IEEE Transactions on Information Theory from 2014 to 2016 We are also interested in developing machine learning techniques for video analysis.ĭr. Multimedia Signal Processing: We are currently designing a new predictive coding architecture based on the concept of virtual data and exploring its application to video compression and video descriptor compression. We are particularly interested in the scenarios where the transmitter side information and the receiver side information are not deterministically related. Wireless Communications: Our goal is to establish architectural principles for the design of communication systems through the analysis of the relevant channel models. Network Information Theory: A major focus of our work in this area is on the development of new analytical techniques for characterizing the fundamental performance limits of multiterminal networks. We particularly enjoy analyzing simple models that require mathematical techniques from diverse areas to obtain insights for practical system/algorithm design. My research group is interested in the broad intellectual theme of information science.
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