جست‌وجوی استاد و پژوهشگر

Linda Saulīte-Subatnieceمشاهده پروفایل

استادیار

• Branding
• Marketing
• Media Studies
• +۳ مورد دیگر

Linda Saulīte-Subatniece serves as Assistant Professor at the Economics and Business Institute within Riga Technical University's Faculty of Engineering Economics and Management, while concurrently leading as CEO and Board Member of dentsu Latvia with over two decades of industry experience in marketing, media, and business management. Her dual academic-industry role positions her at the forefront of integrating theoretical research with practical marketing innovation. Her educational background features: PhD in Economics specializing in Branding and Marketing Research interests concentrate on branding dynamics in digital environments, with particular emphasis on media branding, audience behavior analysis, and artificial intelligence applications in marketing intelligence. Her work examines how non-product attributes influence media consumption, develops theoretical frameworks for media brands, and investigates generational differences in brand perception - especially among younger audiences in evolving media landscapes. This research bridges academic theory with real-world marketing challenges through empirical audience studies and cross-cultural analysis. Analysis of her 2020-2023 publications reveals consistent focus on media brand uniqueness phenomena, news media branding in digital contexts, and audience segmentation effects. Her work demonstrates increasing integration of AI concepts in marketing intelligence, with strong methodological emphasis on audience perspective analysis and cross-platform brand equity measurement. Key thematic threads include adaptation of branding strategies to fragmented media consumption and cultural specificity in brand perception. She actively participates in the EQUATION project (EQUalIty through AccreditaTION, 2022-2025), which examines accreditation frameworks for promoting equality in higher education. While her industry leadership at dentsu Latvia drives practical implementation of marketing innovations, her academic advising activities aren't explicitly documented in available sources.

Stevan Rudinacمشاهده پروفایل

دانشیار

• multimedia
• computer vision
• information retrieval
• +۳ مورد دیگر

Stevan Rudinac is an Associate Professor of Artificial Intelligence for Business at the University of Amsterdam Business School, which is part of the Faculty of Economics and Business. He also serves as a guest researcher at the Informatics Institute of the University of Amsterdam. His academic career focuses on advancing multimedia analytics with applications to societal challenges. Rudinac's primary research interests include multimedia analytics, computer vision, information retrieval, machine learning, and artificial intelligence with specific applications in urban computing. His work aims at enabling large-scale multimedia analytics based on higher semantic level relevance criteria by jointly analyzing visual content with heterogeneous associated information including text, metadata, and social network data. What particularly fascinates him is the potential of artificial intelligence in addressing important societal challenges, such as liveability and security. His recent publication trends (2020-2025) demonstrate a strong focus on interactive multimedia systems, particularly the Exquisitor framework for interactive learning and search, hypergraph learning techniques, urban computing applications, and the integration of large language models with multimedia systems. His work spans both theoretical advancements in multimodal learning and practical applications addressing real-world challenges. Rudinac has been actively involved in academic service, particularly in organizing workshops and conferences in the Multimedia Modeling (MMM) series, and has contributed to advancing the field through his editorial work on special issues focused on content-based multimedia indexing. He currently advises multiple PhD students working on diverse topics including art market analysis, marketing applications of AI, urban computing, and multimedia forensics, demonstrating the breadth of his research impact across different domains.

Stefano Grazioliمشاهده پروفایل

استاد

• Information Technology
• Digital Innovation
• Enterprise Architecture
• +۳ مورد دیگر

Stefano Grazioli is a Professor and Academic Director of the M.S. in the Management of Information Technology (MSMIT) program at the McIntire School of Commerce, University of Virginia. With over a decade of leadership in the MSMIT program—which serves seasoned professionals averaging 14 years of work experience—he bridges advanced information systems with business strategy. His institutional affiliations include the Center for the Management of Information Technology, where he drives initiatives connecting academic research with industry applications. Grazioli holds a Ph.D. and M.S. in Management Information Systems and Computer Sciences from the University of Minnesota, and a B.S. in Business & Economics from Bocconi University, Milan. His educational background underpins his expertise in translating technical concepts into business value. His research spans three interconnected domains: Digital Innovation explores blockchain, IoT, and generative AI through courses like Digital Innovation and projects analyzing ChatGPT's business impact; Fraud Detection pioneers empirical studies on phishing and deception, including the first experimental analysis of internet fraud published in IEEE Transactions; and IT-Finance Integration develops algorithmic trading systems and risk management frameworks through initiatives like the IT Hedge Tournament. Recent work focuses on GenAI applications and Metaverse business models. Analysis of his 15 most recent publications reveals consistent emphasis on adversarial problem-solving in digital environments, with growing attention to AI ethics and value assessment since 2022. His work transitions from foundational fraud detection (2001-2006) to current explorations of emerging technologies' business implications. UVA All-University Teaching Award (2009) Order of Claw & Dagger Faculty Recognition Award (2018) Jefferson Scholars Foundation Excellence in Teaching Award (2022) Inaugural McIntire Teaching Fellow (2023) Grazioli mentors high-impact professionals, with dozens of students achieving C-suite positions across industries. His grant-funded projects with Bank of America, IRS, and KPMG address real-world challenges in risk management and system design. International initiatives like UVA in Argentina deploy student teams to solve SME business problems through technology, while his leadership in the MSMIT program shapes executive education globally. He directs the Center for the Management of Information Technology, fostering collaborations between academia and industry. Current projects examine generative AI implementation frameworks and metaverse business models, positioning his work at the intersection of emerging technologies and strategic management.

Anthony Riosمشاهده پروفایل

استادیار

• Biomedical informatics
• Computational social science
• Natural language processing
• +۱ مورد دیگر

Dr. Anthony Rios is an Assistant Professor in the Department of Information Systems and Cyber Security at The University of Texas at San Antonio (UTSA), affiliated with the Alvarez College of Business. He holds a Ph.D. in Computer Science from the University of Kentucky (2018) and a B.S. in Computer Science from Georgetown College (2011). His research focuses on biomedical informatics, computational social science, natural language processing (NLP), and machine learning, with applications in healthcare and social media analysis. Dr. Rios has published extensively in top venues such as EMNLP, NAACL, AMIA, and JAMIA, and has received awards including a distinguished poster finalist award at AMIA 2014 and a best paper finalist at ICHI 2015. His work includes developing robust NLP systems for electronic medical records (EMR) coding, combating bias in AI systems (e.g., dialect biases in privacy policies), and enhancing cybersecurity through SQL-based threat detection frameworks. He leads the UTSA-NLP team, contributing to projects like ArchEHR-QA and Chemotimelines. Current research explores large language model (LLM) validation, ethical AI, and scalable evaluation of data visualization systems. Education: Ph.D. in Computer Science, University of Kentucky, 2018 B.S. in Computer Science, Georgetown College, 2011 Awards: 2014: Distinguished Poster Finalist Award, AMIA 2015: Best Technical Paper Finalist, ICHI Labs/Teams: UTSA-NLP Lab, focused on NLP applications in healthcare and cybersecurity

• Social Media Use
• Algorithm Acceptance
• Human-Machine Communication
• +۳ مورد دیگر

Prof. Sonja Utz is a Professor of communication via social media at the University of Tübingen and Head of the Everyday Media Lab. She leads research on social and mobile media use in knowledge acquisition, algorithm acceptance, and human-machine communication. Her work bridges informal (e.g., YouTube) and professional contexts (e.g., LinkedIn). She has secured prestigious grants including an ERC and Excellence Initiative awards. Education: PhD in Psychology (1999), Catholic University of Eichstätt PostDoc at VU University Amsterdam (Social Psychology and Communication Science) Part-time Associate Professor at NHL Leeuwarden (2011-2013) Research Interests: Focuses on social media dynamics, AI-human interaction, crisis communication, and algorithmic fairness. Her lab explores how platforms like YouTube and LinkedIn mediate knowledge exchange, with recent work on voice assistants' credibility and ChatGPT usage patterns. Awards: ERC Grant Recipient Excellence Initiative Success Grants & Projects: Leads projects on AI-human interaction, pandemic media use, and algorithmic bias. Notable projects include NewOrder (traditional knowledge erosion) and VREUNDE (long-distance social connections). Labs: Directs the Everyday Media Lab, investigating media's role in daily life and professional settings.

• Computer Science Education
• Programming Education
• Adaptive Learning Systems
• +۶ مورد دیگر

Barbara Ericson is a Professor in the Computer Science and Engineering department at the University of Michigan, Ann Arbor. Her research focuses on computer science education, programming pedagogy, and broadening participation in computing. She has developed innovative educational tools including interactive ebooks and Parsons problems for teaching programming concepts. Dr. Ericson's research interests span multiple areas of computer science education including adaptive learning systems, CS teacher professional development, and broadening participation in computing, particularly for underrepresented groups. She has pioneered work on Parsons problems as learning tools and has extensively researched how to make computer science education more accessible and effective. Her recent work has focused on AI literacy and the integration of large language models in programming education. Her publication record shows a clear trend toward integrating AI technologies into computer science education while maintaining a strong focus on equity and accessibility. The majority of her recent articles address how to effectively use AI tools like large language models in programming education, develop AI literacy among students, and create more inclusive computing classrooms. Her work bridges educational theory with practical classroom applications. Dr. Ericson has received recognition for her work in broadening participation in computing, particularly through initiatives like Sisters Rise Up and Project Rise Up 4 CS which support underrepresented students in Advanced Placement Computer Science courses. She has been instrumental in developing the Runestone Interactive platform for free, open-source computer science ebooks and has conducted extensive research on how teachers and students use these resources. Her work on adaptive Parsons problems has influenced programming pedagogy across multiple institutions.

• Privacy-preserving technologies
• Educational technology
• Cybersecurity
• +۵ مورد دیگر

Zikai Alex Wen is an Assistant Professor in the Department of Computer Science and Engineering at the Hong Kong University of Science and Technology. Previously, he earned his PhD from Cornell University in 2021 with a dissertation on educational video games and intelligent tutoring systems. His research bridges multiple domains including privacy-preserving technologies, educational technology, cybersecurity, and accessibility. Wen's primary research interests focus on differential privacy, educational technology for students with learning disabilities, phishing detection and prevention, and game design for accessibility. His work uniquely combines theoretical privacy foundations with practical applications in education and security. He has made significant contributions to understanding how privacy mechanisms can be effectively explained to users and how to design systems that protect sensitive data while maintaining utility. His publication record demonstrates consistent output in top venues including IEEE S&P, CHI, ASSETS, and VLDB. Recent work shows increasing focus on generative AI applications for household safety, enhanced differential privacy mechanisms, and continued innovation in educational technology for diverse learners. His research often involves interdisciplinary collaboration across computer security, human-computer interaction, and educational psychology. Wen has received recognition through publications in prestigious venues but specific awards aren't documented in the available records. His work has been supported by research grants focused on privacy technologies and educational accessibility, though specific grant details aren't provided in the source material. He maintains active collaborations with researchers worldwide, particularly with Changyu Dong, Wei Cai, and Shiri Azenkot. His research group focuses on developing practical privacy-preserving systems and accessible educational technologies, with ongoing projects exploring the intersection of AI, security, and inclusive design.

Sang Won Leeمشاهده پروفایل

دانشیار

• Human-Computer Interaction (HCI)
• Computer-Mediated Empathy
• Creative Computing
• +۵ مورد دیگر

Sang Won Lee is an Associate Professor of Computer Science at Virginia Tech and a Visiting Researcher at NAVER AI Lab. His work focuses on Human-Computer Interaction (HCI), computer-mediated empathy, and creative computing. He explores technologies like VR, conversational agents, and live coding to foster empathy, support self-reflection, and enable inclusive collaboration. His research has been recognized with best paper awards at ACM CHI and Creativity & Cognition. He holds a Ph.D. in Computer Science from the University of Michigan, alongside degrees in Music Technology (Georgia Tech), Management Science (Stanford), and Industrial Engineering (Seoul National University). His teaching spans courses like Creative Computing Studio, Computer-Supported Cooperative Work, and Game Design. Research interests include: Empathy through interactive systems Music technology and live coding performances Collaborative tools for education and work VR/AR applications in learning Notable awards include the 2016 International Computer Music Association Award for his composition Live Writing: Gloomy Streets . Recent work explores AI ethics in education, voice agents in parent-child interactions, and cross-device mixed reality experiences. Active in both academic conferences (CHI, NIME) and artistic venues (ICMC performances), he bridges technical innovation with creative expression. His lab develops tools like TaskScape for holistic task management and Octave for spatiotemporal data analysis in construction education.

Denis Gracaninمشاهده پروفایل

دانشیار

• Virtual Reality
• Computer Graphics
• Human-Computer Interaction
• +۵ مورد دیگر

Denis Gracanin is an Associate Professor in the Department of Computer Science at Virginia Tech, part of the College of Engineering. He holds a Ph.D. in Computer Science from the University of Louisiana at Lafayette (1994) and multiple advanced degrees in Electrical Engineering from the University of Zagreb, Croatia. His research focuses on Virtual Reality (VR), Augmented Reality (AR), human-computer interaction, privacy, and immersive analytics. He has held notable fellowships, including from ONR and NASA, and contributes to editorial boards of journals like Naše more and International Journal on Systems and Software Engineering . Education: Ph.D., Computer Science, University of Louisiana at Lafayette, 1994 M.S., Computer Science, University of Louisiana at Lafayette, 1992 M.Sc., Electrical Engineering (Telecommunications), University of Zagreb, 1988 B.Sc., Electrical Engineering (Radiocommunications), University of Zagreb, 1986 B.Sc., Electrical Engineering (Telecommunications), University of Zagreb, 1985 Research Interests: Gracanin explores VR/AR applications, cybersecurity in immersive systems, generative AI for 3D object creation, and smart built environments. Recent work includes optimizing light probes in VR, BCI for mobility assistance, and stress management using wearables and LLMs. Publications: His recent articles address topics like cross-layer security frameworks for XR, context-aware AR content generation, and interactive cooling system design. These contributions span computer science, cybersecurity, and biomedical engineering. Awards & Fellowships: ONR Summer Senior Faculty Fellowship (2015, 2010, 2005) NASA Summer Faculty Fellowship (2004) Fulbright Scholarship (1991) Grants & Labs: Gracanin collaborates on projects like XR-CEIL (cybersecurity training) and Smart Re-configurable Spaces (SReS) for pandemic adaptation. He also engages in industry partnerships, such as with Naval Surface Warfare Center and NASA.

• Artificial Intelligence
• Machine Learning
• Data Science
• +۴ مورد دیگر

Dr. Lia Song is a Lecturer (teaching-research balanced) at the University of Adelaide (UoA) and a researcher at the Australian Institute for Machine Learning (AIML). She is also a Visiting Scholar at the Australian Artificial Intelligence Institute (AAII) at the University of Technology Sydney (UTS). Previously, she held roles as a Laureate Postdoctoral Research Associate at AAII and a Research Fellow at RMIT University. She holds a PhD in Statistics from the University of Technology Sydney, complemented by a Master's and Bachelor's in Statistics from China. Her teaching focuses on artificial intelligence and machine learning, including coordinating courses like 'Concepts in Artificial Intelligence' and 'Using Machine Learning Tools PG.' She supervises student projects across various levels, emphasizing critical thinking and teamwork. Her research addresses foundational challenges in machine learning, particularly data distribution discrepancies, aiming to enhance model accuracy, robustness, fairness, and transparency. Key areas include robust modeling, AI agent collaborations, and real-time forecasting applications in finance and weather. She collaborates with institutions like UniSA's Australian Research Centre for Interactive and Virtual Environments and RMIT's Enterprise AI and Data Analytics Hub. Dr. Song leads and participates in grants such as the Surrey-Adelaide Partnership Fund and UoA Start-up Grant, focusing on adversarial learning, digital capabilities for aged care, and AI ethics tools. Her long-term goal is to develop end-to-end trustworthy AI solutions for diverse users.

Gary Holnessمشاهده پروفایل

دانشیار

• Machine Learning
• Robotics
• Ensemble Methods
• +۴ مورد دیگر

Gary Holness is an Associate Professor of Computer Science at Clark University, where he directs the Laboratory for Intelligent Perceptual Systems (LIPS). He holds a PhD in Computer Science from the University of Massachusetts Amherst (2008) focusing on machine learning ensembles, robotics, and distributed systems. Research spans: Machine learning ensembles and error diversity Robotic perception and autonomous systems Nonparametric density estimation Human-robot interaction for autism therapy Distributed frameworks for medical alerting Interactive AI with manifold learning His publications show progression from theoretical machine learning to applied systems, with recent work on spectroscopic analysis and kernel methods. Maintains active student research programs in robotics, GPU acceleration, and terrain classification.

• Computer Vision
• Image and Video Processing
• Machine Learning
• +۵ مورد دیگر

Alexander C. Loui is a Professor in the Department of Computer Engineering at Rochester Institute of Technology (RIT), leading the Multimodal Analysis and Perception (MAP) Lab. He holds a Ph.D., M.A.Sc., and B.A.Sc. in Electrical Engineering from the University of Toronto, Canada. His academic roles include Senior Area Editor of IEEE Transactions on Image Processing and Senior Editor of SPIE/IS&T Journal of Electronic Imaging. Loui specializes in computer vision, image/video processing, machine learning, and multimedia systems, with over 100 peer-reviewed publications and 95+ patents. Research interests span video summarization, medical image segmentation, and AI-driven multimedia applications. He has led technical teams at Kodak Alaris, Kodak Research Labs, and Bell Communications Research. Awards include IEEE Region 1 Technological Innovation Award and Fellowships from IEEE and SPIE. His work bridges academia and industry, emphasizing practical algorithm development and patent innovations. Teaching responsibilities include Digital Signal Processing and Multidisciplinary Senior Design courses. Key contributions: MAP Lab leadership, over 95 patents (e.g., video object segmentation, salient foreground detection), and editorial roles in top journals. His research trends focus on label-efficient learning, trustworthy AI, and predictive content curation systems.

Justus Robertsonمشاهده پروفایل

استادیار

• Human-Centered Artificial Intelligence
• Computer Games
• Interactive Narrative

Justus Robertson is an Assistant Professor in the School of Interactive Games and Media at Rochester Institute of Technology (RIT). His research focuses on human-centered AI, computer games, and interactive narrative systems. He develops AI agents that generate dynamic stories using computational models of narrative theory and human cognition, creating immersive experiences such as adaptive training scenarios and entertainment narratives. His work aims to merge targeted story structures, simulated environments, and character behavior with human interaction, inspired by concepts like Star Trek's holodeck. Key projects include the General Mediation Engine (GME), a framework for interactive narratives, and BaseCase, a Unity-based demo showcasing GME applications. Robertson also explores esports analytics, player performance metrics, and data-driven audience engagement strategies through platforms like Dax. His GitHub repositories (e.g., GME, LitWiki) highlight contributions to game development frameworks and academic literature management tools. Collaborative projects like IC-CRIME demonstrate his interest in applied technology for crime scene analysis.

Martha Snyderمشاهده پروفایل

استاد آموزشی

• Knowledge Management
• Learning Design
• Educational Technology
• +۷ مورد دیگر

Martha Snyder, Ph.D., serves as Director of Faculty Professional Development at Nova Southeastern University's Learning and Education Center within the Office of the Provost and Academic Affairs. With a Ph.D. from NSU, M.Ed. from University of Missouri—Columbia, and B.A. from Columbia College, she bridges corporate organizational development experience with academic leadership. Her research spans knowledge management, learning design, cybersecurity education, and experiential learning methodologies. Current investigations focus on generative AI applications in education, virtual reality instructional design, phishing attack mitigation, and qualitative research methodologies. Snyder's work consistently addresses the intersection of technology, pedagogy, and human factors in educational contexts. Recent publications reveal strong trends in immersive learning technologies (VR/360-degree video), AI-driven educational innovations, and cybersecurity awareness training. Her scholarship demonstrates methodological diversity across qualitative, experimental, and design-based approaches while maintaining focus on practical applications in higher education settings. Snyder actively contributes to professional organizations including the National Society for Experiential Education (serving as 2020 conference chair), Association for Information Systems, ISACA, and Project Management Institute. Her professional certifications (PMP, SPHR) complement her academic work in organizational development and faculty training. As an educator, she teaches across undergraduate, master's, and doctoral programs in instructional design, learning theory, and technology ethics using face-to-face, blended, and fully online formats. Her administrative leadership focuses on faculty development initiatives and experiential education coordination through NSU's Shark Preview program.

Martin Gaedkeمشاهده پروفایل

استاد

• Web Engineering
• Knowledge Engineering
• Artificial Intelligence (AI)
• +۴ مورد دیگر

Prof. Dr.-Ing. Martin Gaedke is a Full Professor and Dean of the Department of Computer Science at Technische Universität Chemnitz (TU Chemnitz). He leads the research group Distributed and Self-organizing Systems (VSR) and holds roles such as President of the International Society of Web Engineering (ISWE), founder of the International AIQT Foundation, and member of the German Foundation for University Admissions' IT-advisory board. His expertise spans Web Engineering, AI-driven systems, and decentralized technologies. Education: Martin Gaedke earned a Master's degree (1997) and doctoral degree (2000) in Computer Science/Engineering from the University of Karlsruhe (now Karlsruhe Institute of Technology). Research Focus: Gaedke's work advances collaborative systems in hyper-connected societies, emphasizing Web Engineering, knowledge engineering, and AI-supported hypermedia systems. Key areas include chatbot design patterns, decentralized web trust, smart IoT systems, and end-user development tools. His contributions include pioneering work in Web Engineering since the 1990s, notably co-authoring the first Web Engineering paper at WWW6 (1997). Recent Trends in Publications: Recent research highlights dynamic code migration, GenAI-driven UIs, and ethical AI in chatbots. He emphasizes trust in decentralized systems (e.g., Solid-based social networks) and practical applications like autonomous smart home agents (WS3H). Awards: Ranked 39th globally in Knowledge Engineering (2020), honored with the AI 2000 Most Influential Scholars Honorable Mention and listed in the AI 2000 Annual List. His work is cited over 1,800 times in key areas like Web Engineering and IoT. Advising & Outreach: Gaedke has mentored numerous researchers and entrepreneurs through roles as a Certified High Performance Coach and business advisor. His lab, VSR, develops open-source tools like the Web-Based Network Simulator (WNSWE) for education and industry. Labs/Teams: The Distributed and Self-organizing Systems (VSR) group at TU Chemnitz focuses on innovative projects such as the Trusting Decentralized Web Data framework and the GenAI-Driven Multimodal UI Architecture .