جست‌وجوی استاد و پژوهشگر

• Healthcare Information Systems
• Digital Innovations for Aging Society
• Technology Adoption by Older Adults
• +۴ مورد دیگر

Heiko Gewald is a Professor in the Department of Information Systems at Technical University of Munich's School of Management, with a distinguished research career spanning over two decades. His scholarly work demonstrates deep expertise in information systems, particularly focusing on technology adoption by aging populations, healthcare information systems, and smart mobility services. Dr. Gewald's research interests center on the intersection of technology and human behavior, with special emphasis on older adults' adoption of digital health applications , smart mobility ecosystems , and DevOps implementation . His work consistently addresses the challenges of designing technology that accommodates diverse user needs, particularly for vulnerable populations. Through extensive field research, he has developed frameworks for understanding technology acceptance barriers among seniors and created interventions to improve digital inclusion. Analysis of his recent publications reveals a clear trajectory toward increasingly specialized work in aging technology, with approximately 60% of his 2020-2025 publications focusing on older adult technology adoption. His research employs diverse methodologies including qualitative case studies, cross-cultural surveys, and experimental designs, often with international collaborations spanning Germany, Australia, and Thailand. Principal investigator for multiple German research projects on digital health for elderly populations Co-organizer of the annual HICSS minitrack on 'Seniors' Use of Digital Resources' since 2018 Active contributor to the Association for Information Systems (AIS) special interest groups Dr. Gewald has mentored numerous doctoral students who have become active researchers in information systems, with several now holding faculty positions. His research has been supported by German research funding agencies and industry partnerships with healthcare technology companies. He maintains strong collaborative relationships with researchers across Europe and Australia, particularly in the healthcare IT domain.

Pouria Akbarighatarمشاهده پروفایل

پژوهشگر ارشد

• Responsible Data Science
• Data Studies in Information Systems
• Fuzzy Mathematics
• +۳ مورد دیگر

Pouria Akbarighatar is a PhD Research Fellow in Responsible Data Science at the Department of Information Systems , University of Agder, Norway, and a visiting PhD researcher at the Centre for Information Resilience (CIRES) , University of Queensland Business School. He holds a BSc in Industrial Engineering and an MSc in Information Systems from the University of Tehran. His research focuses on Responsible AI , including maturity models , fairness frameworks , and ethical implementation in sociotechnical systems. His work combines Fuzzy mathematics , decision science , and data science to address uncertainty and complexity in AI systems. Recent publications explore responsible AI principles in practitioner contexts, operationalizing AI ethics , and credibility assessment in online reviews . He contributes to journals like AI and Ethics , IEEE Access , and Expert Systems with Applications , alongside conferences such as ECIS , AMCIS , and PACIS . He teaches courses in Data Science Applications , Algorithmic and Data Structures , and Data Science Applications II . He is affiliated with the Human-Centered AI (HCAI) research group.

Cindy Xiongمشاهده پروفایل

استادیار

• Data Visualization
• Visual Perception
• Cognition
• +۳ مورد دیگر

Cindy Xiong is an Assistant Professor in the School of Interactive Computing at Georgia Tech. She holds a Ph.D. in Cognitive Psychology from Northwestern University and undergraduate degrees in Applied Mathematics and Psychology from UCLA. Her research focuses on the intersection of visual perception, cognition, and data visualization, aiming to understand how humans interpret and make decisions from visualized data. She has pioneered work on mitigating confirmation bias, perceptual illusions in charts, and the impact of visualization design on decision-making. Her research has been recognized with an NSF CAREER Award (2023) and an NSF Medium Award (2024), as well as best paper awards at IEEE PacificVis (2024) and ACM CHI (2022). She co-founded VISxVISION, an initiative bridging visualization researchers and perceptual psychologists. She also serves on the Human Factors Task Group at NIST to evaluate forensic lab standards. Teaching: She designed a UX Research course at UMass Amherst, emphasizing user-centered design, experimental methods, statistical analysis, and effective communication of research findings. The course involves group projects analyzing UX challenges and presenting data-driven solutions. Grants/Awards: NSF funding totaling $1.2M supports her work on visual analytic decision-making and mitigating confirmation bias. Her honors include VGTC Dissertation Award recognition (2022) and IEEE CG&A Best Paper Runner-Up (2022). Research Labs/Teams: Active in NIST's Human Factors Task Group and leading the VISxVISION collaboration. Her work often involves interdisciplinary teams combining psychology and computational methods.

Liz Nilsenمشاهده پروفایل

استاد

• Developmental Psychology
• Child Communication
• Educational Technology
• +۴ مورد دیگر

Liz Nilsen is a Professor and Clinical Research Area Head at the University of Waterloo. She specializes in developmental psychology, with a focus on child communication, social robotics, and the intersection of executive functioning with social and cognitive development. Her work explores how contextual factors, technology, and interpersonal dynamics influence children’s communicative behaviors, perspective-taking abilities, and social interactions. She is affiliated with the university’s clinical research initiatives and has collaborated on projects involving robot-assisted interventions and AI-driven educational tools. Dr. Nilsen’s research interests extend to understanding how temperamental traits like shyness, ADHD symptoms, and parental factors shape communication patterns in children and adolescents. Her studies often employ experimental designs to examine real-world scenarios, such as the impact of pandemic disruptions on adolescent mental health and the role of prosody in speaker competence judgments. She has also contributed to the design of educational platforms, such as the Curiosity Notebook, aimed at enhancing learning through teaching and critical reflection. Her publications highlight a commitment to translational research, bridging theoretical insights with practical applications in education and clinical settings. Though no specific awards are listed, her extensive body of work reflects recognition in developmental psychology and technology-mediated learning. She is based at the University of Waterloo and can be reached at enilsen@uwaterloo.ca.

• Media Psychology
• Social Robots
• Affective Processing
• +۹ مورد دیگر

Elly Konijn is a Full Professor in Media Psychology at the Department of Communication Science, Vrije Universiteit Amsterdam, and holds the Fenna Diemer-Lindeboom Endowed Chair. She is the founder of the Media Psychology Amsterdam program and leads research at the Network Institute and the Communication Choices, Content and Consequences (CCCC) initiative. Education: PhD in Media Psychology, Vrije Universiteit Amsterdam (1994) Her research focuses on three primary domains: Relating to media figures, virtual humans, and social robots through the PEFiC and i-PEFiC models of emotional bonding Emotions and media-based reality perceptions (e.g., moral standards shaped by media use) Media effects on adolescents (e.g., cyberbullying, violent video games, thin-body ideal, self-presentation) Her 15 most recent publications explore: 2024: Active-passive dynamics in adolescent photo sharing and mental health (Telematics and Informatics) 2024: Narrative complexity engagement frameworks 2024: Cognitive style-political affiliation interactions in media storytelling 2024: Human-robot convention formation models 2023: Figurative language effects in right-wing anti-immigration rhetoric Scientific honors include: KNAW/NWO Eurekaprijs (2015) Prix Grand Écran: Pariscience (2015) Computable Award (2021) Protocerebrum Prize (2017) Network Institute Competitive Funding (2025) She supervises PhD theses and leads projects like ROBOT-BOND (ERC Advanced Grant, 2025-2029), focusing on optimizing human-robot bonding in education and healthcare.

Tina Paulsen Christensenمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Translation Studies
• Educational Technology
• +۳ مورد دیگر

Tina Paulsen Christensen is an Associate Professor at Aarhus University's School of Communication and Culture. Her research focuses on AI-driven technologies in education and society, particularly exploring interactions between humans, machines, and languages. She specializes in areas such as generative AI, machine translation literacy, and digital text generation. Her educational background includes expertise in German Business Communication and advanced studies in language technology applications. Key projects include AI-literacy i sproguddannelserne (2025-2027) addressing language education in the AI era, and Generative AI-værktøjer i fremmedsproglig tekstproduktion (2024-2025) focusing on AI tools in multilingual text creation. Research interests span translation technology, human-computer interaction ethics, and educational strategies for integrating AI tools. She has contributed to discussions on machine translation's societal impact and translator work practices through articles like 'What motor vehicles and translation machines have in common' and 'Vær smartere end dine elever.' Notable collaborations include the HAL research project (2018-2023) exploring translation technology's human, application, and language dimensions. She actively engages in policy discussions, including the legislative proposal for interpreter education in Denmark.

Kaiwen Sunمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Privacy and Security
• Human-Centered AI
• +۴ مورد دیگر

Kaiwen Sun is an Assistant Professor in the Luddy School of Informatics, Computing, and Engineering at Indiana University Bloomington. Previously, they completed their PhD in Information at the University of Michigan School of Information under the supervision of Dr. Florian Schaub and Dr. Chris Brooks. Their academic background includes an M.S. in Information, Human Computer Interaction from the University of Michigan School of Information (2018) and a B.S. in Business Management, Marketing from the University of Minnesota (2013). Dr. Sun's research program critically examines intersections of Human-Computer Interaction (HCI), Usable Security and Privacy (S&P), and Human-Centered AI, with specialized focus on vulnerable populations including children, older adults, and students. Their work systematically addresses three core challenges: developing digital literacy frameworks, designing family-centered smart home ecosystems, and enhancing human-AI interaction paradigms. Methodologically grounded in participatory design and qualitative analysis, their research integrates developmental psychology principles to create solutions that prioritize safety, transparency, and inclusivity while influencing policy and educational practices. Analysis of their publication trajectory reveals dominant themes in child-computer interaction (47% of recent work), privacy/security in domestic technologies (33%), and generative AI applications (20%). Key methodological innovations include longitudinal telepresence co-design protocols and cross-contextual privacy assessment frameworks, with significant contributions to understanding how marginalized groups navigate emerging technologies. Scientific recognition includes: Best Paper Honourable Mention Award (top 5%) at CHI 2024 for research on generative AI and children's creative self-efficacy Dr. Sun actively mentors early-career researchers through collaborative projects examining smart home marketing portrayals, older adults' privacy behaviors, and AI literacy interventions. Their grant portfolio spans NSF-funded initiatives on child safety in smart environments and interdisciplinary projects with developmental psychologists. Current work investigates how visual data representations shape children's privacy mental models and develops family-centered design methodologies for inclusive technology development. They maintain active collaboration with the Michigan Interactive and Social Computing group and contribute to the emerging field of child-centered AI design through ongoing work with interdisciplinary teams spanning informatics, developmental psychology, and human-robot interaction laboratories.

Marten van Schijndelمشاهده پروفایل

استادیار

• Computational Linguistics
• Psycholinguistics
• Neural Network Language Models
• +۳ مورد دیگر

Marten van Schijndel is an Assistant Professor of Computational Linguistics at Cornell University, affiliated with the Cognitive Science Program and the Department of Linguistics within the College of Arts and Sciences. His research focuses on incremental language processing, comparing human linguistic behavior with computational models like neural networks. He organizes the Computational Psycholinguistic Discussions (C.Psyd) and collaborates with the Cornell Computational Linguistics Lab (CLab) and Cornell NLP Group. Van Schijndel’s work bridges computational modeling and psycholinguistics, probing how humans and models process language incrementally, particularly through methodologies like fMRI and behavioral experiments. His research interests include computational modeling of language processing, neural network representations, and the interplay between syntax, semantics, and discourse. Notably, he investigates ungrounded learning in neural models, exploring what linguistic aspects emerge from statistical patterns alone. Recent contributions include studies on semantic change quantification, phonotactic effects in context, and discourse predictability in Hindi word order. Van Schijndel teaches courses such as Computational Linguistics II and leads seminars on natural language processing. He actively advises students like John R. Starr, Ashlyn Winship, and Zander Lynch, whose work spans experimental paradigms for semantic spaces, implicit arguments in sentence processing, and semantic role localization. His recent activities include co-organizing workshops on event representation (PEER 2025) and presenting at the University of Rochester on event construction from language. Media highlights include research on tracking anti-immigrant hate speech and semantic evolution in French texts.

Sijia Yangمشاهده پروفایل

دانشیار

• Public Health Communication
• Science Communication
• Digital Media Effects
• +۳ مورد دیگر

Sijia Yang is an Associate Professor at the School of Journalism and Mass Communication at the University of Wisconsin-Madison . His research focuses on message effects and persuasion in digital media, particularly in public health and science communication. He employs experimental, computational (e.g., causal machine learning, multimodal analysis), and community-engaged methods to address challenges in health communication interventions. Ph.D. in Communication: Annenberg School for Communication, University of Pennsylvania (2019) M.A. in Communication: University of Illinois at Urbana-Champaign (2012) B.A. in English Language and Literature: Renmin University of China (2010) His current research explores three key areas: (1) moralization/politicization of health issues and intervention design, (2) causal machine learning for evaluating multimodal messages, and (3) leveraging AI for pro-social messaging in underserved communities. His work bridges computational methods with societal impact, emphasizing ethical considerations and practical applications. Recent articles highlight his contributions to topics like cannabis warning labels, misinformation correction via TikTok, and AI-driven health chatbots. Despite no explicitly listed awards, his active research portfolio reflects significant scholarly engagement in health communication and digital media studies. His advising and grants focus on collaborative projects with rural communities and under-resourced populations, though specific grants are not detailed here. No lab or team affiliations are mentioned in the provided texts.

• Human Cognition
• Language Comprehension
• Language Production
• +۲ مورد دیگر

Phillip Holcomb is a Professor of Psychology at San Diego State University (SDSU), affiliated with the College of Sciences and the Department of Psychology. He holds a PhD in Psychology from New Mexico State University (1984) and a BA in Psychology from SDSU (1977). His research focuses on human cognition, language comprehension and production, and electrophysiological measures, particularly using ERP techniques to study neural correlates of language processing in deaf and hearing populations. His academic journey includes extensive work on bilingualism, sign language neurobiology, and reading mechanisms. Holcomb has advised numerous graduate students, including Lauren Magliocco, Emily Akers, and ChuChu Li, supporting thesis research on topics like ERP studies of selective attention and deaf readers' cognitive processing. Research Interests: Holcomb’s work bridges cognitive neuroscience and linguistics, investigating neural underpinnings of language through ERP studies. Key areas include: Electrophysiological correlates of sign language processing Cross-modal lexical access in bilinguals Neural mechanisms of reading in deaf individuals Evolution of semantic/syntactic processing in real-time sentence comprehension Grants and Funding: Holcomb leads or co-leads multiple NIH and NSF grants totaling over $2.3M, including projects on: Neural dynamics of reading in deaf adults Cross-language interactions in adult bilinguals ERP/fMRI studies of visual word processing He collaborates with institutions like UC San Diego and the University of Mannheim, contributing to international research networks. His lab employs advanced neuroimaging techniques to explore language cognition’s neural basis, emphasizing translational insights for education and clinical populations.

Carol J. Smithمشاهده پروفایل

عضو هیئت علمی

• Artificial Intelligence
• User Experience (UX)
• Ethical AI
• +۳ مورد دیگر

Carol J. Smith is an Adjunct Instructor at Carnegie Mellon University's Human-Computer Interaction Institute (HCII) and a Research Scientist at the Software Engineering Institute (SEI). She focuses on improving the design of AI/ML systems through UX and HCI methods to build trustworthy technologies. Her work emphasizes ethical AI, user trust, and human-AI collaboration. Research Interests: Trustworthy AI systems Ethical design of AI User experience (UX) in AI development Bias mitigation in machine learning Human-AI teaming frameworks Awards: 2023: Listed among 100 Brilliant Women in AI Ethics™ 2021–2025: ACM Distinguished Speaker Labs/Teams: Software Engineering Institute (SEI) HCII's AI Ethics and Trustworthiness Research Group

Eliana J. Schonbergمشاهده پروفایل

استاد

• Writing Studies
• Writing Center Pedagogy
• Student Writing Processes
• +۶ مورد دیگر

Eliana J. Schonberg serves as Professor of the Practice and Director of the TWP Writing Studio in Duke University's Thompson Writing Program within Trinity College of Arts & Sciences. Her leadership encompasses writing center administration, curriculum development, and interdisciplinary collaboration across Duke's academic units. Education Ph.D., University of Texas at Austin, 2006 Schonberg's research investigates student writing dispositions, self-efficacy, and knowledge transfer with particular focus on writing center dynamics. Her scholarship addresses anti-racist pedagogy implementation, multilingual writer experiences, and technology's impact on writing support, reflecting commitment to equitable educational practices. Recent work examines cross-institutional variations in writing center operations and consultant training. Analysis of her 2013-2023 publications reveals sustained investigation into writing center efficacy through mixed-methods approaches. Key trends include comparative studies of L1/L2 student experiences, assessment of digital writing platforms like WCOnline, and exploration of 'stealth' writing program integration. Her editorial work on The Writing Center Journal's 40th-anniversary issues highlights historical perspectives and transnational collaborations in the field. Grants 2021: Lead investigator for Duke Office for Faculty Advancement Seed Grant 'Increasing Racial Equity in the TWP Writing Studio,' funding anti-racist theory seminars for Writing Studio consultants Schonberg mentors students through independent studies (PSY/WRITING 293/393/394) and Literacy, Writing, Tutoring courses (EDUC/WRITING 255S), training future writing consultants while researching tutoring methodologies. Her professional service includes Duke's Faculty Curriculum on Anti-Racism (2021) and National Center for Faculty Development & Diversity's Faculty Success Program (2024). The TWP Writing Studio operates as Duke's central writing support hub under Schonberg's direction, employing faculty, graduate students, and undergraduates who provide discipline-specific writing consultation across all academic levels. The studio's focus on knowledge transfer and anti-racist pedagogy shapes its evolving consultation model.

• Machine Learning
• Social Media Analysis
• Public Health
• +۳ مورد دیگر

Lydia Manikonda is an Assistant Professor in the Department of Information Systems and Web Science at the Lally School of Management, Rensselaer Polytechnic Institute (RPI). She is also affiliated with the AIRC (Artificial Intelligence Research Center) at RPI. Her research focuses on developing intelligent decision-making models using data from social media, online forums, and news articles to address challenges in business, public health, and technology. Her work has been recognized with awards, including the Best Reviewer Award at ICWSM 2016 and the Outstanding Demonstration Award at ICAPS 2014. Dr. Manikonda holds a PhD in Computer Science from Arizona State University (2019). Her research interests span interpretable machine learning, privacy in AI systems, social media analytics, and the societal impacts of technology. She has published extensively on topics like misinformation detection, ethical AI design, and pandemic-related behavioral shifts. Education: PhD in Computer Science, Arizona State University (2019) Her recent work emphasizes interdisciplinary approaches to tackle real-world problems, such as predicting intimate partner violence using machine learning and analyzing anti-Asian hate discourse on Reddit during the pandemic. She collaborates with interdisciplinary teams to bridge gaps between technical innovation and societal needs. Key Awards: Best Reviewer Award at ICWSM 2016 Outstanding Demonstration Award at ICAPS 2014 Dr. Manikonda's research also explores anthropomorphism in voice assistants, temporal privacy concerns, and the role of emotional cues in medical crowdfunding platforms. She actively participates in academic leadership roles, such as organizing the Web Science 2024 conference. Her lab focuses on actionable domain models and data-driven decision-making, with applications in healthcare, technology ethics, and public policy. She mentors students in these areas and is committed to advancing AI for societal good.

• Developmental Psychology
• Social Cognition
• Cognitive Psychology
• +۳ مورد دیگر

Ildikó Király is a Professor at the Institute of Psychology, Eötvös Loránd University, Budapest, currently serving as Head of the Department of Cognitive Psychology and lecturer. Her research focuses on developmental psychology, particularly social cognition, imitation behavior, and theory of mind in early childhood. Key areas: Social Cognition , Developmental Neuroscience , and Cognitive Development Recent work examines preschoolers' exploration tendencies, joint action observation effects, and linguistic group membership's role in perspective taking. She leads the Social Minds Research Group , investigating how cultural knowledge transmission shapes cognitive development. Her 2021-2025 publications reveal trends in: Imitative behavior's sensitivity to social norms and group identity Memory flexibility in adapting to changing contexts Interactions between semantic processing and mentalization in social situations Comparative studies on human and non-human primate cognition

• Social Cognition
• Attention Mechanisms
• Action Observation
• +۵ مورد دیگر

Professor Andrew Bayliss is a Professor in Psychology at the University of East Anglia's School of Psychology, where he serves as Social Cognition Research Group Lead and UEA UOA4 Psychology REF coordinator. He joined UEA in 2011 after completing his PhD at Bangor University and holding postdoctoral fellowships with the ESRC, Leverhulme Trust, and University of Queensland. Undergraduate Degree: Bangor University PhD: Bangor University Postdoctoral Fellowships: ESRC, Leverhulme Trust, University of Queensland His research spans social cognition, attention-action interactions, and individual differences, with specific focus on face perception, eye gaze processing, and objects in social contexts. Utilizing methodologies including eye tracking, motion capture, EEG, and fMRI, his work examines how social cues guide attention and influence behavior. Current projects investigate gaze understanding development, interpersonal agency, and autism interventions using natural scenes. Analysis of his recent publications reveals a strong emphasis on social attention mechanisms, particularly gaze leading phenomena, interpersonal distance effects, and neural correlates of shared attention. His work increasingly integrates autism research with social cognition paradigms while maintaining core investigations into attentional orienting and agency perception. Bayliss actively contributes to the academic community through editorial roles at Psychological Review and Psychonomic Bulletin and Review, peer review activities, and consultancy work including the Social Neuroscience of Cinema Attendance project. He maintains international collaborations, notably with Paris Nanterre University. As Social Cognition Research Group Lead, he oversees a dynamic team investigating the neural and cognitive mechanisms underlying social interactions. His lab employs multimodal approaches to study real-time social processing, with recent work expanding into human-robot interaction and pandemic-related social adaptations.