Vincent Y. F. Tan

Jump to other IT Society Websites:
Vincent Y. F. Tan portrait

Vincent Y. F. Tan

Associate Professor

Affiliation: National University of Singapore

Contact Information

Department of Electrical and Computer Engineering,

National University of Singapore

Research Interests

  • Detection and Estimation
  • Shannon Theory
  • Source Coding
  • Statistical Learning and Inference


Vincent Y. F. Tan was born in Singapore in 1981. He is currently an Associate Professor in the Department of Electrical and Computer Engineering (ECE) and the Department of Mathematics at the National University of Singapore (NUS). He received the B.A. and M.Eng.degrees in Electrical and Information Sciences from Cambridge University in 2005. He received the Ph.D. degree in Electrical Engineering and Computer Science (EECS) from the Massachusetts Institute of Technology in 2011. During his Ph.D. studies, he spent two summers at Microsoft Research—the Machine Learning and Perception group in Cambridge, U.K. in 2008 and the E-Science group in Los Angeles, CA in 2009. He was a postdoctoral researcher in the Department of ECE at the University of Wisconsin-Madison in 2011 and following that, a scientist at the Institute for Infocomm Research (I2R), A*STAR, Singapore from 2012 to 2013. His research interests include information theory, machine learning and statistical signal processing.

 Dr. Tan has received several awards including the MIT EECS Jin-Au Kong outstanding doctoral thesis prize in 2011; the A*STAR Philip Yeo prize for outstanding achievements in research in 2012; the NUS Young Investigator Award in 2014; the Engineering Young Researcher Awardin the Faculty of Engineering, NUS in 2018; and the Singapore National Research Foundation (NRF) Fellowship (Class of 2018). He is a Distinguished Lecturer of the IEEE Information Theory Society (2018/19).  He was also placed in the NUS Faculty of Engineering Teaching commendation list in 2015 and 2016.

 He has authored a research monograph titled “Asymptotic Estimates in Information Theory with Non-Vanishing Error Probabilities” in the Foundations and Trends® in Communications and Information Theory Series (NOW Publishers). A Senior Member of the IEEE, he served as a member of the IEEE “Machine Learning for Signal Processing” Technical Committee within the IEEE Signal Processing Society. He is currently serving as an Associate Editor for the IEEE Transactions on Signal Processing and the IEEE Transactions on Green Communications and Networking. He is also a Guest Editor of the Special Issue on “Information-Theoretic Methods in Data Acquisition, Analysis, and Processing” of the IEEE Journal on Selected Topics in Signal Processing.


Participation & Positions:

Student and Outreach Subcommittee (Chair, 02/11/18 until 12/31/19)
Membership Committee (Member, 02/11/18 until 12/31/19)
Distinguished Lecturers (Lecturer, 01/01/18 until 12/31/19)
Student and Outreach Subcommittee (Member, 01/01/16 until 12/31/18)