siwei lyu image

Siwei Lyu, Ph.D. [CV] [Google Scholar] [DBLP]

Professor, Department of Computer Science
Director, Computer Vision and Machine Learning Lab
College of Engineering and Applied Sciences
University at Albany, State University of New York
Phone: (518) 437-4938
Email: slyu AT albany DOT edu
Office: UAB413, 1215 Western Avenue, Albany, NY12222


Siwei Lyu is a Professor at the Department of Computer Science and the Director of Computer Vision and Machine Learning Lab (CVML) of University at Albany, State University of New York.

Dr. Lyu received his Ph.D. degree in Computer Science from Dartmouth College in 2005, and his M.S. degree in Computer Science in 2000 and B.S. degree in Information Science in 1997, both from Peking University, China. Dr. Lyu was an Assistant Professor from 2008 to 2014 and an Associate Professor from 2014 to 2019. From 2005 to 2008, he was a Post-Doctoral Research Associate at the Howard Hughes Medical Institute and the Center for Neural Science of New York University. He was an Assistant Researcher at Microsoft Research Asia (then Microsoft Research China) in 2001.

Dr. Lyu's research interests include digital media forensics, computer vision, and machine learning. Dr. Lyu has published over 120 refereed journal and conference papers. Dr. Lyu's research projects are funded by NSF, DARPA, NIJ, UTRC, IBM and University at Albany, SUNY. He is the recipient of the IEEE Signal Processing Society Best Paper Award (2011), the National Science Foundation CAREER Award (2010), SUNY Albany's Presidential Award for Excellence in Research and Creative Activities (2017), SUNY Chancellor's Award for Excellence in Research and Creative Activities (2018) and Google Faculty Research Award (2019).

Dr. Lyu currently serves on the IEEE Signal Processing Society's Information Forensics and Security Technical Committee, and is on the Editorial Board of IEEE Transactions on Information Forensics and Security. Dr. Lyu is a senior member of International Society of Electric and Electronic Engineers (IEEE), and a member of Omicron Delta Kappa (OΔΚ).

Dr. Lyu is currently the coordinator of UAlbany CS Department Colloquiums.


  • (06/02/2019) Our work on detecting DeepFakes continues to draw attention and is featured on Full Measure [link to video] and on Brazil news media O Globo[ link].
  • (05/13/2019) Our work has been covered by Fox News [link], USA Today [link] and Chinese National TV (CCTV) [link].
  • (05/02/2019) Two papers on Digital Media Forensics are accepted by Workshop on Information Hiding and Multimedia Security (IHMMSec2019) in Paris.
  • (05/01/2019) Our lab keeps growing: Dr. Feng Ding joins as a post-doc, Ehab AlBadawy joins as a Ph.D. student, and Ao Luo joins as a visiting student.
  • (04/17/2019) I gave a presentation at O'Reilly AI Conference at NYC [link].
  • (03/01/2019) Our work is featured on Spanish News paper El Pais [link].
  • (02/28/2019) Our work on detecting AI-synthesized fake media has won Google Faculty Research Award for the year of 2019.
  • (02/14/2019) Our work is featured on O'Reily's Data Show Podcast [link] and a Brookings Institute blog [link].
  • (02/01/2019) Our work on detecting DeepFake is featured on Univision [link].
  • (11/19/2018) I received SUNY Chancellor's Award for Research and Creative Activities. Here is a photo at the ceremony.

    Chancellor Award 2018

    (left to right) President Havidàn Rodríguez, Dr. Siwei Lyu, and Dean Kim Boyer.

  • (11/06/2018) Our work on detecting DeepFake generated videos using detection of eye blinking are reported by many news media, including The MIT Technology Review [article], CNN Money [article], Spectrum News [TV interview] Wired Magazine [article], UAlbany Podcast [interview], DataSkeptics Podcast [interview], Deseret News [article], The Register [article], Columnbia Journalism Review [article], iNews [article]
    • For details, check my article on The Conversation and our paper to be presented at WIFS 18.
  • (09/01/2018) Our pose estimation work is ranked #1 on the very challenging MPII benchmark.
    Video demonstration of our pose estimation results. This work has also been accepted for publication by ECCV.

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