Dr. Elizabeth Behm-Morawitz is a Professor and Chair in the Department of Communication at the University of Missouri. Her research focuses on media effects, media psychology, and emerging technologies such as virtual reality, AI, and social media. She examines how media influences identity, health, and prosocial behavior, with a particular emphasis on marginalized groups and counter-narratives. Her academic background includes a Ph.D. in Communication from the University of Arizona. She teaches undergraduate and graduate courses on media theory, persuasion, and new technologies. Behm-Morawitz serves on editorial boards for Communication Monographs, Communication Studies, and Journal of Media Psychology, reflecting her leadership in the field. Her work spans multiple platforms, analyzing media's impact on body image, gender roles, and environmental attitudes through innovative frameworks like mediated counter-narratives. Her research highlights the intersection of technology and societal issues, such as using virtual reality for environmental advocacy or exploring how beauty filters affect self-perception. She also investigates media's role in shaping racial/ethnic identities and addressing diversity through education programs. Despite no listed awards or grants in the text, her prolific publication record and editorial roles underscore her significant contributions to media studies.
Francesco Fedele is an Associate Professor at Georgia Tech, concurrently affiliated with the School of Civil and Environmental Engineering and the School of Electrical and Computer Engineering. He holds a Ph.D. in Civil Engineering from the University of Vermont (2004) and a Laurea (magna cum laude) from the University Mediterranea, Italy (1998). His research spans nonlinear wave phenomena, coastal engineering, fluid mechanics, and sustainable ocean energy, with a focus on rogue waves, stereo imaging, and computational methods. His work has been published in high-impact journals like Physical Review Letters and IEEE Transactions series. Research Interests include wave turbulence, signal processing for biomedical and radar applications, and mathematical modeling of tidal energy systems. Notable contributions involve analyzing extreme waves in the Mediterranean and North Sea, contributing to maritime safety and hurricane impact studies. Publications reflect expertise in fluid dynamics, oceanography, and computational methods. Recent work addresses the geometrical phases of nonlinear systems and interval-based finite element analysis under uncertainty. His research has been featured in Georgia Tech news for applications in rogue wave prediction and structural engineering. Dr. Fedele’s academic positions and collaborations include postdoctoral research at NASA Goddard Space Flight Center (pre-Georgia Tech tenure). No specific awards are explicitly listed in the provided text, though his work has garnered media attention for its societal impact.
Emmanuel SIETY is a Professor of film and audiovisual studies at Sorbonne Nouvelle University - Paris 3, where he also serves as Director of the Institute for Research on Cinema and Audiovisual (IRCAV - EA 185). His research focuses on themes such as The Matter of Images, Game and Cinema, The Split Screen, and Acts, Gestures, and Postures in Cinema, particularly in the works of Jean-Luc Godard. He teaches courses in Film Analysis, General Aesthetics, and Godard’s filmic techniques. His research explores intersections between film theory, aesthetics, and cultural practices, with notable contributions to understanding fear in cinema, early film techniques, and the analysis of cinematic gestures. SIETY has published extensively, including monographs like Fictions d'images (2009) and La Peur au cinéma (2006), alongside chapters in edited volumes addressing topics ranging from Kurosawa’s use of memory to James Cameron’s mirror techniques. He has delivered lectures at institutions like the Cinémathèque française, discussing works such as Kubrick’s The Shining and Fritz Lang’s cinematic treatments of death. His academic leadership in IRCAV underscores his commitment to advancing cinema studies through research and scholarly collaboration.
Pasquale Cascarano is a fixed-term Assistant Professor at the University of Bologna , affiliated with the Department of the Arts . His research bridges computer science with creative industries (cinema, art, fashion) and biomedical applications, focusing on Artificial Intelligence and Extended Reality paradigms. He collaborates with national and international institutions on interdisciplinary projects. Institutional Affiliation: University of Bologna Academic Role: Assistant Professor (fixed-term) Research Interests center on integrating AI and XR into creative sectors and healthcare, with emphasis on: Generative AI for immersive environments Medical imaging and diagnostics Digital heritage preservation XR-based educational tools 3D visualization techniques Creative technology applications Recent Publications highlight trends in: Medical XR for surgical training AI-driven image restoration LLM integration with AR/VR Privacy in collaborative AR Fashion and cultural heritage digitization Deep learning for video enhancement
Panos Constantinides is a Professor of Digital Innovation at Alliance Manchester Business School, University of Manchester. He holds a PhD from the Judge Business School, University of Cambridge, and is a Fellow of the Cambridge Digital Innovation Centre. A co-founder of the European Digital Platforms Research Network (EU-DPRN), his research focuses on human-AI collaboration and digital platform governance. He has secured grants from the British Academy, Innovate UK, and UKRI, with publications in top-tier journals like Information Systems Research and MIS Quarterly . Education: PhD in Business (2005), Judge Business School, Cambridge MPhil in Business (2002), Judge Business School, Cambridge BSc in Computer Science (2000), New York University Research Interests: Exploring ethical and governance frameworks for AI integration in healthcare and autonomous systems Designing platform ecosystems resilient to crises like pandemics Advancing digital health through ecosystem approaches Studying innovation dynamics in decentralized systems Key Contributions: Authored Digital Transformation in Healthcare: An Ecosystem Approach (2023) Host of the Digital Podcast on YouTube/Spotify Advisor to corporations and policymakers on digital strategy Grants & Projects: Leading the £1.2M Applied AI and Quantum Technology in the Port Environment project (2024-2026) Recipient of British Academy grants (2015-2016) Co-PI on digital resilience research (2023) Labs/Initiatives: Principal Investigator at the Digital Futures Beacon Member of Christabel Pankhurst Institute Editorial roles at MIS Quarterly (2016-2025)
Alberto Del Bimbo is a Full Professor of Computer Engineering at the Department of Systems and Computer Science, University of Florence, Italy. He serves as Director of the Media Integration and Communication (MICC) Center, a National Center of Excellence focused on Artificial Vision, Artificial Intelligence, and Multimedia Technologies. His career spans academia and leadership roles, including Deputy Rector for Research and Innovation Transfer (2000-2006) and Director of the Department of Systems and Computer Science (1997-2000). Education : Master Degree in Electronic Engineering (1977), University of Florence. Research Interests : Artificial Vision, Multimedia, Multimodal Interaction, Image/Video Analysis, Surveillance, and Industry Automation. Academic Leadership : Editorial roles including Editor-in-Chief of ACM TOMM , and leadership in IEEE, IAPR, and ACM conferences. Projects : MICC Center’s work on neuromorphic computing, deepfake detection, and AI-driven surveillance systems, with industrial partnerships (Leonardo SpA, Thales Italia, IARPA). Article Trends : Recent work focuses on neuromorphic event-based vision, multimodal emotion prediction, compatible AI representations, and deepfake detection using local surface frames. Applications span smart environments, cultural heritage, and real-time surveillance. Scientific Awards : ACM Distinguished Scientist (2016) ACM Award for Outstanding Technical Contributions to Multimedia (2016) IEEE Senior Member IAPR Fellow Labs & Teams : Leads the MICC research team at the University of Florence, collaborating with international institutions and companies on vision and AI innovation.
Yu Chen is a Professor in the Department of Electrical and Computer Engineering at Binghamton University, State University of New York. He leads the Ubiquitous Smart & Sustainable Computing (US2C) Lab and serves as Director of the Center for Information Assurance and Cybersecurity (CIAC). His research focuses on Trust, Security, and Privacy in Edge-Fog-Cloud Computing, IoT, and Smart Cities. Dr. Chen holds a PhD from the University of Southern California (2006), with prior research under Professors Kai Hwang and Anthony F. J. Levi. His work has been funded by NSF, DoD, AFOSR, and industrial partners, yielding over 200 publications. He is a Senior Member of IEEE and SPIE, and a member of ACM. Education: PhD in Electrical Engineering, University of Southern California (2006) Affiliations: Director, US2C Lab Associate Director, CIAC Research Interests: Smart Cities, Intelligent Surveillance, Edge-Fog-Cloud Computing, IoT Security, and Privacy-Preserving Technologies. His work emphasizes real-time systems, resilient edge architectures, and decentralized consensus protocols for IoT. Grants & Awards: Funded by NSF, DoD, AFOSR, NYS MDPI Computers 2019 Best Paper Award Best Student Poster Award (IEEE AIPR 2014) Students & Labs: Advised 19 students (PhD/Master’s). Key projects include secure edge video processing, ENF-based authentication, and blockchain for IoT. The US2C Lab explores smart city applications and edge computing resilience.
Heather Shoenberger is an Associate Professor at the Bellisario College of Communications, Pennsylvania State University. Her research focuses on authenticity in digital advertising, consumer behavior in response to media, and health communication. She explores how emerging technologies like AR and virtual influencers shape advertising efficacy and consumer trust. Her work also examines political communication dynamics and the psychological impacts of media content, including strategies to counter misinformation and enhance message credibility. Shoenberger’s expertise spans multiple areas: the persuasive role of authenticity in advertising, the ethical dimensions of digital media manipulation, and the intersection of health outcomes with media exposure. She has published extensively in journals like the Journal of Advertising Research and Communication Research , addressing topics ranging from virtual influencer effectiveness to crisis communication during pandemics. Her research often highlights practical implications for creating healthier, more transparent media content. Notable areas include strategies to mitigate green skepticism in sustainability campaigns, the persuasive framing of political messages, and leveraging narrative techniques to enhance message credibility in health and environmental contexts. Awards/Achievements: None explicitly listed in the provided text. Advising/Grants: No advising relationships or grants are detailed in the text. Her work primarily focuses on research and scholarly publications.
Stan Sclaroff is a Professor of Computer Science and Dean of the College of Arts & Sciences at Boston University. He holds affiliated faculty status in the Department of Electrical and Computer Engineering. His research focuses on computer vision, pattern recognition, and machine learning, with expertise in tracking, human motion analysis, and multimedia retrieval systems. He co-leads the Image and Video Computing research group and has contributed pioneering work like the ImageRover content-based image retrieval system. Education: PhD in Media Arts & Sciences from MIT (1995), SM from MIT (1991), and BS in Computer Science and English from Tufts University (1984). Research Interests: Human motion tracking, sign language analysis, deformable shape matching, and multimedia indexing. Notable contributions include early work on content-based image retrieval and foundational techniques in video analysis. Honors: IEEE & IAPR Fellowships, NSF CAREER Award (1996), ONR Young Investigator Award (1996), and BU's Mentor of the Year (2018). Over 40+ students advised, many now in academia and industry leadership roles. Key roles: Chair of BU Computer Science (2007–2013), Associate Dean for Mathematical & Computational Sciences (2015–2018), Interim Dean (2018–2019), and current Dean since 2019.
Dr. Donyale Padgett serves as Associate Professor in the Department of Communication at Wayne State University, where she has been a faculty member since 2002 and on the tenure-track since 2006. With over 15 years of professional communications experience in client service and strategic planning, she integrates practical industry insights into her teaching through service learning projects with local non-profits. She actively contributes to university-wide initiatives on diversity, inclusion, and student retention efforts. Professor Padgett earned her academic credentials from Wayne State University and Howard University: Bachelor of Arts in Journalism with Public Relations concentration, Wayne State University Master of Arts in Organizational Communication and Public Relations, Wayne State University Ph.D. in Rhetoric and Intercultural Communication, Howard University Her research centers on critical rhetoric examining how marginalized groups negotiate power and identity within social structures. Primary interests include crisis rhetoric and organizational legitimacy, crisis-cultural dynamics, and diversity in workplace communication. Secondary focuses encompass service learning pedagogy, student retention strategies in higher education, and hip-hop's influence on identity formation. This critical scholarship investigates rhetoric's generative power in public discourse, particularly regarding race, culture, and institutional oppression. Her publication record demonstrates consistent interdisciplinary scholarship bridging crisis communication with cultural studies, race theory, and social justice. Key contributions include the development of "restorative rhetoric" for non-traditional crises and analyses of race-based crisis response variations. Recent work spans political scandals, cross-cultural crisis management, hip-hop femininity, and critical journalism approaches, reflecting her commitment to examining communication through lenses of power and marginalization. Professor Padgett advises undergraduate and graduate students including thesis and dissertation supervision. She engages students through service learning projects connecting classroom theory with community needs. Her current research involves an interdisciplinary team studying retention challenges among marginalized student populations, aiming to develop actionable strategies for improving graduation rates through narrative analysis of student experiences.
Reza Bosagh Zadeh is an Adjunct Professor at the Institute for Computational and Mathematical Engineering (ICME) at Stanford University. His research focuses on machine learning, deep learning, and their applications in video classification, healthcare analytics, and distributed algorithms. He specializes in developing scalable computational methods for real-time data processing and has contributed to advancements in neural networks and optimization techniques. Reza's work spans theoretical and applied domains, with notable contributions to TensorFlow frameworks, video summarization systems, and medical imaging analysis. His research often integrates interdisciplinary approaches, leveraging both academic and industrial collaborations. Notable projects include developing machine learning models for glaucoma detection and creating efficient algorithms for large-scale data processing in environments like Apache Spark. His publications emphasize real-time video stream analysis, distributed computing architectures, and practical implementations of deep learning. Reza holds a strong presence in both academic and tech sectors, with contributions to platforms like Twitter's Who-to-Follow system and innovations in edge computing for video surveillance.
Dr. Ahmed Elgammal is a Professor of Computer Science at Rutgers University, where he leads the Art and Artificial Intelligence Laboratory. His work focuses on applying AI and computer vision to digital humanities, particularly art analysis and generation. He has published over 180 peer-reviewed papers and received the NSF CAREER Award in 2006. Elgammal’s research bridges art and technology, including AI-generated art and computational methods for art history. His work has been featured in prominent media such as the Washington Post, New York Times, and PBS, which earned an Emmy for a segment about his research. His art installations have been exhibited globally in cities like New York and Frankfurt. He holds a Ph.D. and M.Sc. in Computer Science from the University of Maryland, College Park. His academic leadership includes roles as Executive Council Faculty at Rutgers’ Center for Cognitive Science. Research Interests: Creative AI and Art Generation Computer Vision Applications in Digital Humanities Machine Learning for Art Analysis Awards: National Science Foundation CAREER Award (2006) Grants & Projects: Includes NSF-funded projects and collaborations in AI-driven art analysis and structural engineering applications. Labs & Teams: Founder and Director of the Art & AI Lab at Rutgers, focusing on interdisciplinary art-tech innovation.
Antoine Miech is a Researcher at DeepMind's Vision Group , with prior affiliations at Inria and Ecole Normale Supérieure where he completed his computer vision Ph.D. under Ivan Laptev and Josef Sivic . He has collaborated with researchers from Facebook AI and Google during his academic career. Research Interests span video understanding, weakly-supervised machine learning, and multimodal analysis. His work focuses on: Text-video embedding Self-supervised video representation Action localization Anticipatory video modeling Scalable multimodal learning Scientific Contributions include: HowTo100M - A massive dataset of narrated instructional videos MIL-NCE - A novel loss function for video-text alignment MEE - A model for handling heterogeneous data Context Gating - Learnable pooling architecture Awards & Recognition : Google Ph.D. Fellowship (2018) Technical Leadership : Created the LOUPE TensorFlow toolbox for feature pooling and maintained annotated video dataset catalogs. Organized the Data Science Game competition (2016-2017).
Hongxin Hu is a Professor and Associate Chair in the Department of Computer Science and Engineering at the University at Buffalo, State University of New York (SUNY). His research spans security, networking, and machine learning, with publications across top conferences including security (S&P, CCS, USENIX Security, and NDSS), networking (SIGCOMM and NSDI), machine learning (NeurIPS, ICML, and EMNLP), and human-computer interaction (CHI and CSCW). His work has been funded by NSF (SaTC, CNS, IIS, OAC, SOC), USDOT, VMware, Amazon, Google, and Dell. Dr. Hu earned his PhD in Computer Science and Engineering from Arizona State University in 2012. His academic journey has led him to become a prominent researcher in cybersecurity with a strong publication record and significant research impact. Dr. Hu's research interests encompass a wide range of topics at the intersection of security, networking, and artificial intelligence. His work focuses on Emerging Network Technologies and Security (5G/Future-G, NFV, SDN, Edge computing), Machine Learning for Security and Privacy , Security and Privacy in IoT and Cyber-Physical Systems , and AI for Social Good (addressing online abuse, unsafe children's games, and cyberbullying). His interdisciplinary approach has enabled him to tackle complex security challenges through innovative solutions that combine networking expertise with machine learning techniques. His recent publications demonstrate a strong trend toward applying large language models and advanced machine learning techniques to security challenges, particularly in content moderation, vulnerability detection, and privacy protection. The research spans multiple domains including voice assistant security, IoT security, network security, and social media safety, showing a consistent pattern of addressing real-world security problems with cutting-edge technical approaches. IEEE Big Data Security Senior Research Award (2025) ACM SACMAT Test-of-Time Award (2024) NSF CAREER Award (2019) Multiple Best Paper Awards from ACM ASIACCS (2022), ACSAC (2020), IEEE ICC (2020), and ACM SIGCSE (2018) Amazon Faculty Research Award (2022) First Place Award in ACM SIGCOMM 2018 Student Research Competition Dr. Hu has successfully advised multiple PhD students, including Nishant Vishwamitra who joined UT San Antonio as a tenure-track Assistant Professor. His research has been generously funded by major agencies and industry partners. As an active member of the academic community, he serves as Associate Editor for IEEE Transactions on Dependable and Secure Computing and Computers & Security, and has held numerous leadership roles in major security conferences including TPC Co-Chair for ASONAM 2025 and IWSPA 2024/2025. Dr. Hu leads a vibrant research group that has produced significant contributions in network security function virtualization, intrusion detection systems, and privacy-preserving technologies. Current projects include developing LLM-assisted vulnerability detection systems, defenses against jailbreak attacks on large language models, and security mechanisms for emerging networking technologies. His team's work on IoT security, voice assistant applications, and online content moderation has received wide recognition and press coverage.
Andrés Bruhn is a Professor for Intelligent Systems and Dean of Computer Science Studies at the University of Stuttgart, where he leads research in the Institute for Visualization and Interactive Systems (VIS). His academic career spans over a decade with significant contributions to computer vision, particularly in optical flow, scene flow, and motion estimation. As Dean of Studies, he oversees academic programs while maintaining an active research agenda focused on cutting-edge computer vision problems. Bruhn's research interests center around computer vision with emphasis on optical flow estimation, scene flow, motion analysis, and adversarial machine learning. His work bridges theoretical foundations with practical applications, developing algorithms that address real-world challenges in motion estimation, image processing, and visual understanding. His research group has pioneered approaches that combine variational methods with deep learning, creating robust systems for motion analysis that can withstand adversarial attacks and challenging environmental conditions. The publication record demonstrates a strong focus on advancing the state-of-the-art in motion estimation, with recent work exploring adversarial attacks on optical flow systems, high-resolution datasets for benchmarking, and multi-frame fusion techniques. His research shows consistent innovation, moving from traditional variational methods to modern deep learning approaches while maintaining mathematical rigor. The work spans both theoretical contributions and practical implementations with real-world applicability. Bruhn has mentored numerous researchers who appear as first authors on publications, including Jenny Schmalfuss, Lukas Mehl, and Azin Jahedi, indicating his commitment to developing the next generation of computer vision researchers. His leadership role as Dean of Studies demonstrates institutional recognition of his expertise and administrative capabilities.
