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DTSTART;TZID=America/New_York:20260827T080000
DTEND;TZID=America/New_York:20260827T090000
DTSTAMP:20260828T063113Z
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SUMMARY:Identity Security in the Age of Deepfakes
DESCRIPTION:Title: Identity Security in the Age of Deepfakes\nSpeaker: Prof. Dr. Siwei Lyu\, University at Buffalo\, USA\nWhen: August 27\, 2026 at 8:00 AM US Eastern Time (2:00 pm CEST\, 8:00 PM Beijing Time)\nWhere: Online (Zoom) \nRecording of the Webinar\n \nAbstract\nRapid advances in generative AI have made it increasingly easy to synthesize or manipulate faces\, voices\, and real-time audiovisual streams\, creating new challenges for biometric identity systems. This talk examines how deepfakes can affect different stages of the biometric pipeline\, including synthetic identity creation\, impersonation\, morphing\, and real-time digital injection. It will clarify the complementary roles of biometric matching\, presentation attack detection and liveness\, and media forensics\, and review the forensic evidence that current deepfake detectors exploit. \nThe talk will also discuss why deepfake detection remains difficult in real-world settings and argue for moving beyond a single “real or fake” detector toward layered\, evidence-based and risk-aware biometric authentication. The webinar should be relevant to researchers\, practitioners\, students\, and security professionals working in biometrics\, identity verification\, media forensics\, AI security\, fraud prevention\, and trustworthy AI. \nAbout The Speaker\nSiwei Lyu is a SUNY Distinguished Professor at the University at Buffalo\, State University of New York\, where he directs the Institute for AI and Data Science and the UB Media Forensics Lab. His research focuses on digital media forensics\, deepfake and AI-generated media detection\, and trustworthy AI. He leads the development of DeepFake-o-Meter\, an open platform integrating state-of-the-art deepfake detection methods for research and real-world analysis. He is a Fellow of IEEE and IAPR.
URL:https://ieee-biometrics.org/event/identity-security-in-the-age-of-deepfakes/
CATEGORIES:Webinar
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DTSTART;TZID=America/New_York:20260924T090000
DTEND;TZID=America/New_York:20260924T100000
DTSTAMP:20260928T075339Z
CREATED:20260902T093659Z
LAST-MODIFIED:20260928T075339Z
UID:10000017-1790240400-1790244000@ieee-biometrics.org
SUMMARY:Beyond Pixels: Continuous Neural Representations for Biometrics
DESCRIPTION:Title: Beyond Pixels: Continuous Neural Representations for Biometrics\nSpeaker: Prof. Dr. Vishal Patel\, Johns Hopkins University\, USA\nWhen: September 24\, 2026 at 9:00 AM US Eastern Time (3:00 pm CEST\, 9:00 PM Beijing Time)\nWhere: Online (Zoom) \nRecording of the Webinar\n \nAbstract\nBiometrics has traditionally relied on discrete pixel representations and\, more recently\, learned feature embeddings for recognition and analysis. This talk explores an emerging alternative based on Implicit Neural Representations (INRs)\, which model biometric traits as continuous functions rather than discrete images. The talk will introduce the principles of INRs and demonstrate their applications to deepfake and presentation attack detection\, biometric quality assessment\, and function-space metric learning. Our speaker will conclude by discussing future opportunities for INRs in biometric recognition\, continuous biometric templates\, morph attack analysis\, privacy-preserving biometrics\, and multimodal biometric systems\, arguing that continuous neural representations may provide a new foundation for the next generation of biometric technologies. \nAbout The Speaker\nVishal M. Patel is a Professor in the Department of Electrical and Computer Engineering (ECE) at Johns Hopkins University. His research focuses on computer vision\, machine learning\, image processing\, medical image analysis\, and biometrics. He has received a number of awards including the 2021 IEEE Signal Processing Society (SPS) Pierre-Simon Laplace Early Career Technical Achievement Award\, the 2021 NSF CAREER Award\, the 2021 IAPR Young Biometrics Investigator Award (YBIA)\, the 2016 ONR Young Investigator Award\, and the 2016 Jimmy Lin Award for Invention. Patel serves as an associate editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence journal and IEEE Transactions on Biometrics\, Behavior\, and Identity Science.  He is a Fellow of the IEEE and IAPR.
URL:https://ieee-biometrics.org/event/beyond-pixels-continuous-neural-representations-for-biometrics/
CATEGORIES:Webinar
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261104T080000
DTEND;TZID=America/New_York:20261104T090000
DTSTAMP:20261013T073555Z
CREATED:20261013T070907Z
LAST-MODIFIED:20261013T073555Z
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SUMMARY:Fundamentals of Hand Biometrics: Commercial and Forensic Applications
DESCRIPTION:Title: Fundamentals of Hand Biometrics: Commercial and Forensic Applications\nSpeaker: Prof. Dr. Wai Kin Adams Kong\, Nanyang Technological University\, Singapore\nWhen: November 4\, 2026 at 8:00 AM US Eastern Time (2:00 pm CEST\, 8:00 PM Beijing Time)\nWhere: Online (Zoom)\nRegistration (free but required): https://us06web.zoom.us/webinar/register/WN_1lFx8W0-Q5CJrQWJoGfIAw \nAbstract\nIn this talk\, the speaker will first introduce the fundamental concepts of hand-based biometrics and discuss their advantages\, including user acceptance\, privacy protection\, and biometric distinctiveness\, particularly for commercial applications. The talk will focus on palmprint recognition\, covering its underlying principles\, practical applications\, and potential for reliable identity verification. The speaker will also introduce other hand-based biometric modalities\, including palm vein and finger vein recognition\, and discuss the key challenges in developing robust\, accurate\, and secure hand biometric systems for real-world commercial deployment. These challenges include variations in data acquisition conditions\, presentation attacks\, and the need to balance recognition performance with usability and privacy. In addition to commercial applications\, the talk will explore the potential of palmprints and wrist characteristics for forensic investigations. It will highlight how hand-based biometric evidence can support identity analysis and assist forensic experts in investigating cases where conventional biometric evidence may be unavailable or insufficient. The talk will conclude by discussing emerging opportunities and future research directions in hand biometrics for both commercial and forensic applications. \nAbout The Speaker\nDr. Adams Kong received his Ph.D. from the University of Waterloo. He is an Associate Professor at Nanyang Technological University (NTU)\, Singapore\, and Director of the MSc in Artificial Intelligence programme. His research has appeared in leading AI conferences and journals. His papers have been selected as spotlight papers by TPAMI\, ICML\, and ICLR\, and for oral presentation at CVPR; another received an Honorable Mention from PR. His Ph.D. students have won Best Student Paper Awards at BTAS 2012 and BIBE 2013\, as well as awards including the Google Anita Borg Memorial Scholarship. He serves as an editor for IEEE T-BIOM\, The Visual Computer\, and TMLR\, and as an area chair for NeurIPS\, ICLR\, CVPR\, and ECCV. He has been recognised as a top reviewer by ICML\, NeurIPS\, and BTAS\, and a top area chair by NeurIPS. He served as an expert witness for the U.S. Department of Justice in a child sexual abuse case and as a consultant in a cross-border legal case.
URL:https://ieee-biometrics.org/event/fundamentals_of_hand_biometrics_commercial_and_forensic_applications/
CATEGORIES:Webinar
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BEGIN:VEVENT
DTSTART;TZID=America/New_York:20261126T080000
DTEND;TZID=America/New_York:20261126T090000
DTSTAMP:20261013T073436Z
CREATED:20261013T073346Z
LAST-MODIFIED:20261013T073436Z
UID:10000019-1795680000-1795683600@ieee-biometrics.org
SUMMARY:Designing computational tools for behavioral and clinical science
DESCRIPTION:Title: Designing computational tools for behavioral and clinical science\nSpeaker: Prof. Dr. Albert Ali Salah\, Utrecht University\, Netherlands\nWhen: November 26\, 2026 at 8:00 AM US Eastern Time (2:00 pm CEST\, 8:00 PM Beijing Time)\nWhere: Online (Zoom)\nRegistration (free but required): https://us06web.zoom.us/webinar/register/WN_uaf_6-kfQq-J7fuFt6coKA \nAbstract\nAutomatic analysis of human affective and social signals brought computer science into closer alignment with social sciences\, enabling new collaborations between computer scientists and behavioral researchers. In this talk\, I highlight the key research directions in this burgeoning interdisciplinary field\, and provide an overview of its major opportunities and challenges.\n\nComputer science and psychology have different methodological assumptions and approaches. In the extended version of this talk\, I introduce the foundational principles of both computational and statistical methods used in this context. I explain the core concepts\, outline different goals and methodologies\, and distinguish between data-driven and theory-driven approaches.\n\nDrawing on examples from our recent research – such as automatic analysis of interactive play therapy sessions with children\, and diagnosis of bipolar disorder from multimodal cues – as well as relying on examples from the growing literature\, I explore the potential of human-AI collaboration\, where AI systems do not replace\, but support monitoring and human decision making in behavioral and clinical sciences. In particular\, the role of face\, body\, gesture\, speech and multimodal analysis  are discussed\, as well the role of explainability and interpretability\, which are important aspects for trustworthy computer systems in this domain.\nAbout The Speaker\nDr. Albert Ali Salah is professor and chair of Social and Affective Computing at the Information and Computing Sciences Department of Utrecht University. His research is broad\, but mainly uses pattern recognition and machine learning for computer analysis of human behavior\, with over 250 publications in these areas\, including edited textbooks Computer Analysis of Human Behavior (2011\, Springer)\, Data Science for Migration and Mobility (2022\, Oxford University Press) and Privacy-Aware Monitoring for Assisted Living (2025\, Springer Cham). \nDr. Salah has a PhD in Computer Engineering from Boğaziçi University (2007). He subsequently held positions at CWI\, University of Amsterdam\, and Boğaziçi University\, as well as a one-year visiting position at Nagoya University. His research group at Utrecht University investigates behavior at different scales; looking at individual behaviors (such as facial expression analysis)\, dyadic and group behaviours (e.g. child-parent or patient-doctor interactions)\, and at computational social science (e.g. mobile phone based analysis of migration and mobility). He was the coordinator of the Data for Refugees (D4R) Challenge between 2016-2019\, and directed the mobile phone workpackage in the HumMingBird EU project. He is also a member of the AI and Animal Welfare Lab in Utrecht. \nDr. Salah was the inaugural recipient of the EBF European Biometrics Research Award (2006)\, and a recipient of the GEBIP award of Science Academy (2017). He served as a program committee member of over 200 conferences\, and as associate editor of several journals\, including IEEE Trans. Affective Computing\, IJHCS\, and Pattern Recognition. He chaired ACM ICMI 2014\, ISSI 2015\, SPECOM 2019\, IEEE FG 2024 conferences\, and served in the Steering Boards of ACM ICMI and IEEE FG\, and as VP Conferences for the IEEE Biometrics Council. He is a Senior Member of the ACM and of IEEE.
URL:https://ieee-biometrics.org/event/designing_computational_tools_for_behavioral_and_clinical_science/
CATEGORIES:Webinar
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