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About Siwei
Siwei Lyu is a SUNY Distinguished Professor and a SUNY Empire Innovation Professor in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York. He earned his Ph.D. in Computer Science from Dartmouth College in 2005, M.S. in Computer Science and Technology from Peking University in 2000, and B.S. in Information Science from Peking University in 1997. Prior to joining the University at Buffalo in 2020, he progressed through faculty ranks at the University at Albany, State University of New York, serving as Assistant Professor from 2008 to 2014, tenured Associate Professor from 2014 to 2019, and Full Professor from 2019 to 2020, where he also founded the Computer Vision and Machine Learning Lab. Earlier, he was a Postdoctoral Research Associate at the Howard Hughes Medical Institute and Center for Neural Science at New York University from 2005 to 2008, and an Assistant Researcher at Microsoft Research Asia from 2000 to 2001. Currently, he directs the Institute for Artificial Intelligence and Data Science since 2026, serves as the founding Director of the UB Media Forensic Lab, and is Co-Director of the Center for Information Integrity since 2021.
Lyu's research specializes in digital media forensics, computer vision, and machine learning, with over 240 refereed journal and conference papers and more than 28,000 citations on Google Scholar. His key publications include the edited book 'Truth Seeking in Our Age of (Mis)Information Overload' (SUNY Press, 2024), 'Natural Image Statistics in Digital Image Forensics' (VDM Verlag, 2008), 'VB-KGN: Variational Bayesian Kernel Generation Networks for Motion Image Deblurring' (IEEE Transactions on Multimedia, 2024), 'LandmarkBreaker: A Proactive Method to Obstruct DeepFakes via Disrupting Facial Landmark Extraction' (Computer Vision and Image Understanding, 2024), and 'FakeTracer: Catching Face-swap DeepFakes via Implanting Traces in Training' (IEEE Transactions on Emerging Topics in Computing, 2024). He has received numerous honors, including IEEE Fellow (2022), IAPR Fellow (2022), AAIA Fellow (2022), ACM Distinguished Member (2022), IEEE Region 1 Technological Innovation Award (2021), Google Faculty Research Award (2019), SUNY Chancellor's Award for Excellence in Research (2018), NSF CAREER Award (2010), and IEEE Signal Processing Society Best Paper Award (2011). Lyu has testified before the U.S. House of Representatives on disinformation and the New York State Senate on consumer data privacy, and advised the Global DeepFake Detection Challenge.
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