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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.


  • (10/09/2019) I was featured in an IEEE Spectrum article [Link]
  • (10/04/2019) I discussed DeepFakes and their detections on WHYY The Pulse [link].
  • (10/01/2019) We are releasing a new DeepFake evaluation dataset Celeb-DF [link].
  • (09/26/2019) I testified at the US House of Representative Committee on Science, Space, and Technology Subcommittee on Oversights and Investigation Hearing on "Online Imposter and Disinformation" link. See also report on Times Union [link] and Washington Post [link].
  • (09/03/2019) I am very excited to be an academic advisor of the DeepFake Detection Challenge sponsored by FaceBook, Microsoft and PAI with multiple universities, along with Profs Hany Farid and Alyosha Efros (UC-Berkeley), Serge Belongie (Cornell Tech), Rama Chellappa (John Hopkins), Phil Torr (Oxford), Phillip Isola and Antonio Torraalba (MIT) [link]. See also report on Times Union [link].
  • (07/25/2019) Wenbo Li successfully defended his thesis on Human Pose Estimation and Activity Recognition. Wenbo will join Samsung Research Lab USA as a Research Scientist. Congratulations Dr. Li!
  • (07/11/2019) I was interviewed by Brooklyn Eagles to discuss our work on detecting DeepFakes [link to story].
  • (06/25/2019) I have written an article on The Conversation about our work of detecting and protecting from DeepFakes [link].
  • (06/02/2019) Our work on detecting DeepFakes continues to draw attention and is featured on Full Measure with Sharyl Atkison [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.

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