Empire Innovation Professor: Siwei Lyu, University at Buffalo, State University of New York

Speaker Profile: Siwei Lyu is a SUNY Empire Innovation Professor at the University at Buffalo, State University of New York. He serves as the director of the UB Media Forensic Lab (UB MDFL) and Co-Director of the Center for Information Integrity (CII). Prior to joining UB, Dr. Lyu held the position of full Professor at the University at Albany, State University of New York, where he served as the Founding Director of UAlbany's Computer Vision and Machine Learning Lab (CVML).

Dr. Lyu's research interests span digital media forensics, computer vision, and machine learning. He has published over 190 journal and conference papers.

Recognized for his achievements, Dr. Lyu has received numerous awards, including the IEEE Signal Processing Society Best Paper Award, the National Science Foundation CAREER Award, both SUNY Albany's Presidential Award and Chancellor's Award for Excellence in Research and Creative Activities, the Google Faculty Research Award, and the IEEE Region 1 Technological Innovation (Academic) Award.

Professor Jennifer L. Newman, Iowa State University

Speaker Profile: Jennifer Newman is a full professor in the Department of Mathematics at Iowa State University. Her primary research focuses on creating and applying discrete mathematics, statistics, and machine learning tools to address challenges in steganography, steganalysis, forensic image analysis, validity of severe storm reports, image processing, texture analysis, and other imaging-related topics.

With over 8 awards and 75 publications in mathematics, engineering, and computer vision, Professor Newman's impactful research is supported by NIST’s Center for Statistics and Applications in Forensic Evidence (CSAFE). Her team collaborates with the National Oceanic and Atmospheric Administration (NOAA) to develop a machine learning diagnostic tool for verifying severe wind reports.

Professor Jun-Cheng Chen, Research Center for Information Technology Innovation, Academia Sinica

Speaker Profile: Dr. Jun-Cheng Chen is an associate research fellow at the Research Center for Information Technology Innovation, Academia Sinica.

Dr. Chen earned his Ph.D. in Computer Science from the University of Maryland, College Park, USA, under the guidance of Prof. Rama Chellappa in 2016. From 2017 to 2019, he served as a postdoctoral research fellow at the University of Maryland Institute for Advanced Computer Studies.

Dr. Chen's research interests encompass computer vision, machine learning, deep learning, adversarial robustness, and their applications to biometrics, including face recognition/facial analytics, activity recognition/detection in the visual surveillance domain, etc. Notably, he was awarded the APSIPA ASC Best Paper Award in 2023 and the ACM Multimedia Best Technical Full Paper Award in 2006.

Wendy Dinova-Wimmer, Sr. Digital Media Architect, Office of the Public Sector CTO, Adobe

Speaker Profile: Wendy Dinova-Wimmer, Sr. Digital Media Architect. Wendy works in Adobe’s Office of the Public Sector CTO Office supporting government customers with all things digital media. Prior to joining Adobe, Wendy spent thirty years in the government, first as a graphic designer and then visualizing scientific analysis with 3D animation. After 9/11, Wendy dove into multimedia forensic analysis specializing in media authentication. Wendy contributes to forensic image standards with the Organization of Scientific Area Committees for Forensic Sciences (OSAC) and ASTM standards organization. Wendy works as a Trusted Advisor with the Content Authenticity Initiative (CAI).

Prof. Matthew Stamm, Drexel University

Speaker Profile: Dr. Matthew C. Stamm is an Associate Professor in the Department of Electrical and Computer Engineering at Drexel University, where he leads the Multimedia and Information Security Lab (MISL). His research encompasses signal processing, machine learning, and information security, with a particular focus on information forensics and anti-forensic countermeasures.

Dr. Stamm’s research has been funded by the National Science Foundation (NSF), the Defense Advanced Research Projects Agency (DARPA), the Army Research Office (ARO), and the Defense Forensics and Biometrics Agency (DFBA). He is the recipient of a National Science Foundation CAREER Award and the Drexel University College of Engineering Outstanding Early-Career Research Achievement Award.

Moreover, Dr. Stamm has played a pivotal role in academic leadership, serving as the General Chair of the 2017 ACM Workshop on Information Hiding and Multimedia Security (IH&MMSec) and leading the organization of the IEEE Signal Processing Society’s 2018 Signal Processing Cup competition.

Rijul Gupta, Founder and CEO of Deep Media

Speaker Profile: Rijul Gupta is the Founder and CEO of Deep Media (https://www.deepmedia.ai), a pioneering force in Synthetic Media. Armed with a degree in Machine Learning from Yale University, Rijul is recognized as a thought leader in DeepFake technology, earning a distinction by Forbes. His commitment to ensuring the ethical use of DeepFake technology led him to establish DeepMedia, where he champions its responsible and secure application.

Prior to founding DeepMedia, Rijul amassed over 7 years of experience as a machine-learning engineer, contributing his expertise to the development of advanced object recognition, pattern matching, and product recommendation AI. His work has left an indelible mark on prominent companies such as Nike, Nordstrom, GAP, and Bloomingdale’s.

A Thiel Fellow Finalist and a patented inventor, Rijul Gupta has rightfully earned a place in Forbes Magazine's prestigious "Forbes Next 1000."