جستجوی استاد راهنمای دانشگاهی

Adriana Kovashkaمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Natural Language Processing
• +۷ مورد دیگر

Adriana Kovashka is an Associate Professor at the University of Pittsburgh , affiliated with the School of Computing and Information and serving as Department Chair . Her academic journey began with BA degrees in Computer Science and Media Studies from Pomona College (2008) and a PhD in Computer Science from The University of Texas at Austin (2014). Joined Pitt’s faculty in January 2015 NSF CAREER awardee (2021) Google Faculty Research Award recipient Dr. Kovashka’s research spans Computer Vision , Machine Learning , and Natural Language Processing , focusing on visual rhetoric, weak multimodal supervision, and domain adaptation. She pioneered techniques for analyzing political imagery, developing robust object detection frameworks, and exploring the intersection of visual and textual persuasion through large-scale annotated datasets. Her recent work emphasizes geographic diversity in vision-language systems, audio-visual fusion for domain generalization, and shape-texture bias mitigation in CNNs. Key publications include groundbreaking studies on symbolic reasoning, multimodal dialogue systems, and ethical AI applications in education. Scientific honors include: NSF CRII Award (2016) NSF CAREER Award (2021) Pitt CRDF Award (2016, 2018) Best Paper at ECV Workshop (2021) Google Faculty Research Award (2016, 2018) Dr. Kovashka actively mentors students in multimodal learning projects and collaborates with interdisciplinary teams on NSF-funded initiatives. She co-organizes workshops like the first CVPR workshop on advertisement understanding and leads research groups exploring human-AI co-learning systems.

• Artificial Intelligence
• Cognitive Science
• Complex Systems
• +۳ مورد دیگر

Melanie Mitchell is a Professor at the Santa Fe Institute, focusing on artificial intelligence, cognitive science, and complex systems. She is an inaugural Fractal Faculty member and originated the Complexity Explorer platform. PhD in Computer Science from University of Michigan (1990) Faculty/research roles at Santa Fe Institute, Portland State University, Los Alamos National Laboratory, and others Her research explores abstraction, analogy-making, and reasoning in AI and human intelligence. She has authored six books, including the award-winning Complexity: A Guided Tour and Artificial Intelligence: A Guide for Thinking Humans . Recent work examines large language models, conceptual understanding, and cognitive parallels between humans and AI. Her 15 most recent publications address topics like AI reasoning, language model robustness, cognitive metaphors, and the Turing test's evolving relevance. Awards include the Phi Beta Kappa Science Book Award and the Herbert A. Simon Award. She advises numerous PhD and postdoctoral students and leads public outreach through online courses and media appearances.

Ceren Budakمشاهده پروفایل

دانشیار

• Computational Social Science
• Social Media Analysis
• News Media Production and Consumption
• +۷ مورد دیگر

Ceren Budak is an Associate Professor at the University of Michigan School of Information and holds a joint appointment as Associate Professor of Electrical Engineering and Computer Science in the College of Engineering. Her work bridges computer science, statistics, and social sciences through computational social science approaches. Her educational background includes a PhD in Computer Science from the University of California, Santa Barbara (2012) and a Bachelors degree in Computer Science from Bilkent University in Turkey (2007). Prior to joining the University of Michigan faculty, she was a Postdoctoral Researcher at Microsoft Research New York. Professor Budak's research centers on computational social science, with particular emphasis on analyzing large-scale datasets to address questions with social, political, and policy implications. Her work spans several interconnected domains: News Media Production & Consumption (examining bias in news outlets and reader preferences), Social Movements & Media (using social media data to study collective action), Social Networks (understanding information diffusion processes), and Measuring and Promoting the Quality of Online Discussions (developing tools to improve online conversations). She teaches SI 608 (Networks) and SI 618 (Data Manipulation and Analysis) at the School of Information. Her publication record demonstrates consistent contributions to understanding how online information ecosystems operate, with recent work focusing on AI-human collaboration, misinformation dynamics, social movement framing, and the application of computational methods to political communication. Her research shows a clear trajectory from foundational work on social network diffusion to increasingly sophisticated analyses of contemporary information challenges. Among her service activities, she has served as Registration chair for COSN (ACM Conference on Online Social Networks) 2015 and as Program Committee Member for numerous prestigious conferences including WWW, ICWSM, WebSci, AAAI, and others. She has also been involved in organizing the MSR NYC Data Science Seminar Series and instructing the Microsoft Research Data Science Summer School.

Verena Zimmermannمشاهده پروفایل

استادیار

• Usable Security
• Privacy
• Human-Computer Interaction
• +۳ مورد دیگر

Verena Zimmermann serves as Assistant Professor (Tenure Track) for Security, Privacy and Society at ETH Zurich within the Department of Humanities, Social and Political Sciences. She leads the Security, Privacy and Society research group, focusing on human-centered approaches to safety, IT security, and privacy challenges in emerging technologies. Her academic foundation includes a PhD in Usable Security from TU Darmstadt, where her dissertation From the Quest to Replace Passwords towards Supporting Secure and Usable Password Creation earned dual awards from the German Association for Data Protection and Data Security (GDD) and the Ernst-Ludwigs-Hochschulgesellschaft. Zimmermann's research pioneers the shift from viewing humans as security vulnerabilities to recognizing them as integral solutions. Her work spans password security, phishing interventions, smart home privacy, and cybersecurity education, consistently applying human factors principles to design systems that align with natural user behavior. Current projects explore emotional dimensions of security engagement, quantum governance frameworks, and LLM-related privacy concerns through interdisciplinary lenses combining computer science, psychology, and safety science. Recent publications reveal strong thematic trends toward understanding user motivations in security behavior, developing personalized training through augmented reality and adaptive systems, and translating safety science principles to cybersecurity incident management. Her work increasingly addresses societal implications of emerging technologies like quantum computing and generative AI. Her distinguished recognitions include: GDD Dissertation Award for Usable Security research Ernst-Ludwigs-Hochschulgesellschaft Dissertation Award IANUS Award (2nd place) for Moving from a 'Human-as-Problem' to a 'Human-as-Solution' Cybersecurity Mindset Zimmermann actively mentors through ETH's Human-Centered Security and Privacy Lab while collaborating internationally with institutions including ATHENE (German National Center for Applied Cybersecurity), Abertay University's Cybersecurity Division, and the Safety Science Innovation Lab. Her research receives support from Swiss and European funding bodies focused on privacy-preserving technologies and organizational security behavior. At ETH Zurich, she directs the Security, Privacy and Society group which employs design thinking, LEGO Serious Play, and mixed-methods research to tackle real-world security challenges. The team partners with industry stakeholders to develop practical solutions for phishing resistance, smart home privacy, and cybersecurity education while maintaining strong ties to the Research Training Group 2050 Privacy and Trust for Mobile Users.

• Natural Language Processing
• Machine Learning
• Multimodal Learning
• +۵ مورد دیگر

Ekaterina Shutova is an Associate Professor at the Institute for Logic, Language and Computation (ILLC) within the Faculty of Science at the University of Amsterdam. She concurrently holds a Visiting Associate Professor position in the Computer Science Department at Stanford University. She leads the Amsterdam Natural Language Understanding Lab and heads the NLP & Digital Humanities research unit at ILLC. An ELLIS Scholar, she earned her PhD from the University of Cambridge Computer Laboratory and Pembroke College. Her research has been funded by ERC, Innovate UK, British Academy, Leverhulme Trust, Google, Meta, and Deloitte. Her research spans natural language processing and machine learning, with core interests in: Few-shot learning for NLP Multilingual and cross-lingual systems Joint modeling of language and vision Cognitive processing and semantic representation Figurative language interpretation Computational social science applications Her recent publications (2024-2025) predominantly focus on multimodal learning, cultural alignment in AI, metaphor processing, and evaluation methodologies for language models. These works reflect a trend toward integrating cognitive science with multilingual systems and ethical considerations. Awards & Fellowships: ERC Consolidator Grant (2025) ELLIS Scholar Outstanding Paper Award at ACL 2023 Finalist for Outstanding Certification by TMLR Runner-up Best Paper Award at NAACL-HLT 2016 Research Leadership: She directs the Amsterdam Natural Language Understanding Lab, supervising 8 PhD students, 1 MSc student, and 34 alumni. Her projects include an ERC-funded initiative on globally accessible language technology and an AI Democratization grant for hate speech detection.

Ellen Droogمشاهده پروفایل

استادیار

• Satirical News Analysis
• Media Literacy
• Metaphorical Humor
• +۴ مورد دیگر

Ellen Droog is an Assistant Professor at Vrije Universiteit Amsterdam's Faculty of Social Sciences and Humanities, Department of Communication Science. She holds additional affiliations with the Network Institute and the Communication Choices, Content and Consequences (CCCC) research group. Her work focuses on satirical news, metaphorical humor, audience responses to media, and corporate social responsibility claims. Research Interests: Droog's research explores how humor and satire function in media, particularly their cognitive, emotional, and persuasive effects. She investigates how metaphors shape public understanding of complex issues like corporate responsibility and health crises. Her recent projects examine the effectiveness of media literacy interventions against misinformation. Key Contributions: Over 14 peer-reviewed publications since 2020, including seminal work on satirical news mechanisms, metaphor analysis in satire, and CSR communication strategies. Her 2023 PhD thesis bridged satirical news features with audience effects through metaphor analysis. Awards: Wilhelmina Drucker Student Talent Award (2017) Teaching: Courses include Communication Science foundations, corporate communication strategies, and media persuasion techniques. Cross-Disciplinary Work: Collaborations span psychology, health communication, and political science.

Courtney N. Reedمشاهده پروفایل

مدرس

• Human-Computer Interaction
• Music Technology
• Digital Instrument Design
• +۵ مورد دیگر

Courtney N. Reed is a Lecturer in Digital Technologies at Loughborough University London, where she joined in November 2023. She maintains a dual role as a visiting research fellow at the Max Planck Institute for Informatics. Her academic journey includes a BMus in Electronic Production and Design from Berklee College of Music (2016), followed by an MSc (2018) and PhD (2023) in Computer Science from Queen Mary University of London. Prior to her current position, she completed postdoctoral research at both the Max Planck Institute for Informatics and King's College London. Bachelor of Music: Electronic Production and Design, Berklee College of Music (2016) Master of Science: Computer Science, Queen Mary University of London (2018) Doctor of Philosophy: Computer Science, Queen Mary University of London (2023) Dr. Reed's research explores the entangled relationships between humans, bodies, instruments, and technology in music interaction, with particular focus on vocal electromyography (VoxEMG) and the vocalist-voice relationship. Her work incorporates feminist and post-human theories to examine sociopolitical contexts within arts technology, aiming to design for creativity while acknowledging individual, messy bodies in artistic practice. She has developed an open-source platform for vocal electromyography to investigate how biosignal feedback changes understanding and perception of the body in vocal performance. Her interdisciplinary approach bridges music technology, human-computer interaction, and embodied interaction studies. Analysis of Dr. Reed's recent publications (2023-2025) reveals a strong thematic focus on embodied interaction in music technology, with particular emphasis on vocal performance, biosignal feedback, and the philosophical underpinnings of digital instrument design. Her work consistently integrates theoretical frameworks like Karen Barad's agential realism with practical applications in digital musical instruments. Key trends include the exploration of ambiguity in data representation, the sociocultural dimensions of timbre in instrument design, and the development of novel methodologies for understanding embodied musical experiences through micro-phenomenology and ethnographic approaches. ACM SIGCHI Outstanding Dissertation Award (2024) for her thesis 'Imagining & Sensing: Understanding and Extending the Vocalist-Voice Relationship Through Biosignal Feedback' Best Newcomer Award at Loughborough University London's Community Awards Celebration (2024) Dr. Reed actively contributes to the academic community through conference organization and leadership roles. She serves as Member-at-Large on the NIME Board, previously chaired papers for NIME 2024, and co-organized the IBM SkillsBuild Sprint at Loughborough London. She has also chaired sessions at the ACM TEI Conference and co-chaired the Student Design Competition. Her collaborative work spans multiple institutions and includes significant contributions to interdisciplinary projects that bridge music, technology, and human experience. She has been instrumental in developing the senSInt research group and the RaveNET wearable network project. Dr. Reed leads the senSInt research group which focuses on sensorimotor interaction in music and performance contexts. The group develops innovative technologies including the VoxEMG platform for vocal electromyography, the Bones anti-corset for vocal performance, and the RaveNET network of wearable biosensing nodes. These projects explore the intersection of biosignals, embodied interaction, and musical expression, creating novel frameworks for understanding how technology mediates human creativity and performance. The group frequently collaborates with musicians, technologists, and theorists to develop and test these systems in real-world performance contexts.

Dagmar Gromannمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Natural Language Processing
• Machine Learning
• +۷ مورد دیگر

Roles & Affiliations: Dagmar Gromann is an Associate Professor for Terminology Science and Translation Technology at the University of Vienna's Centre for Translation Studies. Previously, she served as a Research Associate at TU Dresden's International Center for Computational Logic (ICCL) and held postdoctoral roles in Barcelona within the ESSENCE Marie Curie Training Network. She completed her PhD at the University of Vienna under Prof. Gerhard Budin, focusing on ontology-terminology integration. Education: PhD in Computer Science and Linguistics, University of Vienna (2015) Postdoctoral Research, Artificial Intelligence Research Institute (IIIA), Barcelona (2015–2017) Research Assistant, Vienna University of Economics and Business (until 2015) Research Interests: Her work bridges computational linguistics, cognitive science, and terminology science. Key areas include: Ontology learning and neurosymbolic AI Image schemas in natural language processing Machine translation ethics and genderfair language Multilingual knowledge extraction and linked data Terminology modeling and semantic web applications Publications & Awards: Over 60 peer-reviewed papers in journals such as Future Generation Computer Systems and Journal of Lexicography . Notable awards include the Best Paper Award at MuC 2021 (GenderFairMT team) and the ISWC 2019 Best PC Award. Her research has pioneered methods for extracting embodied cognition concepts like image schemas from text. Grants & Leadership: PI of the European Language Grid (ELG) pilot project Text2TCS, member of the COST Action NexusLinguarum, and organizer of conferences like LDK 2023. Editorial board roles include the Semantic Web Journal and Applied Ontology . Labs & Teams: Former member of TU Dresden's ICCL and currently part of the University of Vienna’s translation technology initiatives. Active in interdisciplinary collaborations spanning computational linguistics, AI ethics, and multilingual systems.

• Artificial Intelligence
• Natural Language Processing
• Computational Semantics
• +۵ مورد دیگر

Luis Espinosa-Anke is a Senior Lecturer at Cardiff University's School of Computer Science and Informatics. His academic journey includes working as a Natural Language Processing (NLP) scientist at Savana Médica, a Madrid-based healthcare AI company, prior to joining Cardiff. He completed his PhD at Pompeu Fabra University in Barcelona while working at Savana. Dr. Espinosa-Anke's research focuses on Artificial Intelligence and NLP, with particular emphasis on meaning representation, computational semantics, multilingual NLP, and computational lexicography. His work spans theoretical and applied aspects of language technology, with applications in healthcare, social media analysis, and multilingual systems. His recent publications reveal a strong trend toward analyzing language model behavior, bias detection in AI systems, and creating resources for semantic analysis. The publications show increasing focus on practical applications of NLP in healthcare, social media, and cross-lingual settings, with notable contributions to datasets like WIKITIDE and 3D-EX that support definition extraction and semantic understanding. laCaixa Fellow Fulbright scholarship recipient Erasmus Mundus program participant Dr. Espinosa-Anke has secured research funding including a Kaggle Open Research grant ($2,000 USD) as PI for the 'Don't Patronize Me!' project, a Snap Inc. grant ($10,000 USD) as CO-I for modeling meaning shift in social media, and a £90,000 Welsh Government grant for English-Welsh bilingual embeddings research. He currently supervises five PhD students working on meaning representations, contextual word embeddings, NLP for healthcare applications, and metaphor identification.

Vlad Pojogaمشاهده پروفایل

مدرس

• Romanian Literature
• Digital Humanities
• Literary Analysis
• +۶ مورد دیگر

Vlad Pojoga is Deputy Dean of the Faculty of Letters and Arts at Lucian Blaga University of Sibiu, holding a Lecturer position in the Department of Romance Studies. His research focuses on Romanian literature, digital humanities, and literary analysis, with particular emphasis on quantitative methods and spatial narratives. He leads projects like the Digital Museum of the Romanian Novel, exploring 19th-20th century literary trends through digital curation and geocritical approaches. His academic background includes advanced studies in literary theory and digital methodologies. Research interests span translation studies, postmodernism, and the intersection of narrative forms with cultural geography. Recent work analyzes character networks in classical novels and metaphor systems in contemporary poetry. Pojoga frequently collaborates on international literary projects, contributing to FORTHEM Alliance initiatives and organizing events like the International Week at ULBS. His publications bridge traditional literary criticism with computational methods, offering innovative frameworks for understanding Romanian literary history.

• Robotics and AI
• Digital Cultures
• Media Studies
• +۷ مورد دیگر

Dr. Chris Chesher is a Senior Lecturer in Digital Cultures within the Discipline of Media and Communications at the University of Sydney's Faculty of Arts and Social Sciences. He co-founded both the Digital Cultures program and the Master of Digital Communication and Culture at the University. Previously, he served as a senior lecturer in the School of Media and Communications at the University of New South Wales. His academic career spans interdisciplinary research at the intersection of digital media, cultural studies, and technology. Dr. Chesher's educational background includes: PhD from Macquarie University Master of Arts (Interdisciplinary Studies) from the University of New South Wales Bachelor of Arts (Media and Communications) from Mitchell CAE (now Charles Sturt University) Dr. Chesher's research adopts a transdisciplinary approach connecting digital cultures, media studies, and cultural studies with philosophy of technology, science and technology studies, games studies, internet studies, sociology of technology, human-computer interaction, social robotics, cultural robotics, and digital humanities. His work challenges conventional understandings of human-machine relations and explores the cultural implications of emerging technologies through projects on robotics beyond anthropomorphism, invocational media theory, and smart urban environments. His recent publications reveal a strong thematic focus on robotics, AI, and digital media theory, with particular attention to non-anthropomorphic approaches to social robotics, invocational media theory, and smart urban environments. The publications demonstrate his consistent engagement with how digital technologies reshape human experience, social relations, and spatial understanding across multiple domains including banking, restaurants, street furniture, and home environments, reflecting both theoretical depth and practical relevance. Dr. Chesher has received recognition for his teaching excellence: 2023 - University of Sydney Faculty of Arts and Social Sciences Teaching Innovation Award As an academic supervisor, Dr. Chesher has guided multiple PhD candidates to completion across diverse topics including digital gambling, game items in digital environments, user regulation on Facebook, and climate change visualizations. His grant history demonstrates sustained research funding, including the Australia-Korea Partnership on Mobile Robot Development in Public Space (2019), Public Forum on Urban Robots and the Future City (2018), and Everyday Social Media Network (2014), highlighting his leadership in collaborative, interdisciplinary research initiatives. Dr. Chesher is actively involved in collaborative research through the Sydney Institute for Robotics and Intelligent Systems (SIRIS) at the University of Sydney, where he contributes to projects examining the cultural dimensions of robotics and AI beyond anthropomorphic frameworks, bridging technical innovation with critical cultural analysis.

• Social cognition
• Spatial cognition
• Cognitive processes in abstract reasoning
• +۴ مورد دیگر

Dr Ulrich Von Hecker is a Senior Lecturer (Reader) in the School of Psychology at Cardiff University, where he has taught since 2000. He leads research on how spatial processes underpin abstract reasoning and social cognition, focusing on mental models, social hierarchies, and cognitive deficits in depression. Education Diploma in Psychology, University of Hamburg (1986) Ph.D. in Psychology, Free University of Berlin (1992) Habilitation, Free University of Berlin (1999) Research Interests Dr Von Hecker’s work integrates spatial cognition , social cognition , and cognitive psychopathology . He investigates how spatial metaphors (e.g., up-down, left-right) structure our understanding of social hierarchies and abstract categories, and how these mappings vary with cultural factors like reading direction. A second major strand examines constructive mental processes —how people build coherent mental models of novel social groups or networks—revealing the role of logical inference, stereotypes, and reciprocity. Finally, he explores cognitive symptoms of depression , demonstrating that sub-clinical depression selectively impairs the formation of global mental models while sparing detail-level processing. Publication Trends Across more than 60 peer-reviewed articles, three clear streams emerge: (1) experimental studies on spatial representation of order, equivalence, and social status; (2) integrative papers on mental model construction in social contexts; and (3) investigations of cognitive control, fluency, and attention in both healthy and depressed populations. Recent work increasingly employs neuroimaging (fMRI), eye-tracking, and cross-cultural designs. Scientific Awards & Recognition Nominated to ESRC Peer Review College (2010–2012) Empanelled as Research Guide, Christ University, Bangalore (2009–2011) Supervision & Grants Dr Von Hecker currently supervises PhD students including Lukas Wolf (embodiment of social values) and Jin Zixi, and incoming MSc student Maohua Nie. His research has been funded by the German Research Foundation (DFG) , Economic and Social Research Council (ESRC) , Polish Committee for Scientific Research (KBN) , and the Russell Sage Foundation . Teams & Collaborations He heads an active research group and collaborates internationally with scholars such as Geoffrey Haddock (Cardiff), Simon Dymond (Swansea), Ana Guinote (UCL), Elanor Hinton (Bristol), and Karl Christoph Klauer (Freiburg), among many others spanning Europe, North America, and Asia.

Deborah Zlotskyمشاهده پروفایل

استاد

• Abstract Painting
• Geometric Abstraction
• Jewish Cultural Art
• +۳ مورد دیگر

Deborah Zlotsky is a Professor of Experimental and Foundational Studies at the Rhode Island School of Design (RISD), where she teaches within the Faculty of Liberal Arts. Her academic career bridges rigorous studio practice with theoretical exploration of history, memory, and identity. She received her BA in History of Art from Yale University and MFA in Painting and Drawing from the University of Connecticut. Zlotsky's research focuses on how historical narratives press against contemporary consciousness through abstract visual language. Her work explores geometric abstraction as metaphor, particularly examining stripes as timelines that build patterns while suggesting societal cycles and marginalization. She investigates how abstraction provides sensory experiences for understanding the complex relationship between past and present, with specific attention to Jewish cultural identity and historical trauma. Her recent artistic output shows consistent thematic development across painting series from 2021-2024, with recurring motifs including chai symbols (representing life), shiva references (Jewish mourning), and diaspora concepts. Technical innovations include trompe l'oeil elements like stitched threads, air holes, and fleshy textures that disrupt geometric precision, creating visual metaphors for historical disruption and memory fragmentation. Guggenheim Fellowship (2019) New York Foundation for the Arts Fellowships (2012, 2018) Residencies at MacDowell Colony, Yaddo, Bogliasco Foundation, and Bemis Center Works in collections including RISD Museum, Borusan Contemporary Art Collection, and Waldorf Astoria Zlotsky maintains an active exhibition schedule with recent solo shows at McKenzie Fine Art, Markel Fine Arts, and Robischon Gallery. Her work connects studio practice with academic inquiry through residencies that function as research opportunities, and her teaching at RISD directly informs her exploration of foundational visual concepts. She continues to develop her investigation into how geometric abstraction can simultaneously represent historical weight and visual beauty.

Melanie Mitchellمشاهده پروفایل

استاد

• Artificial Intelligence
• Cognitive Science
• Complex Systems
• +۴ مورد دیگر

Melanie Mitchell is a Professor at the Santa Fe Institute, where she conducts research at the intersection of artificial intelligence, cognitive science, and complex systems. Her work focuses on conceptual abstraction and analogy-making in artificial intelligence systems, seeking to understand the mechanisms that enable both human and machine intelligence. Mitchell received her PhD in Computer Science from the University of Michigan in 1990 and has held positions at numerous institutions including the University of Michigan, Los Alamos National Laboratory, the Oregon Graduate Institute, and Portland State University. Her research bridges the gap between theoretical understanding of intelligence and practical AI development. Her recent publications explore fundamental questions about AI understanding, reasoning capabilities, and the relationship between language models and world knowledge. She has developed novel evaluation frameworks for assessing analogical reasoning and abstraction in AI systems, challenging assumptions about what current AI can truly comprehend. Her work often examines the limitations of large language models while proposing pathways for more robust and human-like artificial intelligence. 2010 Phi Beta Kappa Science Book Award for "Complexity: A Guided Tour" Finalist for the 2023 Cosmos Prize for Scientific Writing for "Artificial Intelligence: A Guide for Thinking Humans" Senior Scientific Award from the Complex Systems Society Distinguished Cognitive Scientist Award from UC Merced Herbert A. Simon Award of the International Conference on Complex Systems Mitchell actively advises numerous PhD students and postdoctoral researchers, fostering the next generation of researchers in AI and complex systems. She has also developed educational resources including the popular online course "Introduction to Complexity" on Complexity Explorer. Her public outreach includes a Substack newsletter "AI: A Guide for Thinking Humans," Science Magazine columns, and the podcast series "The Nature of Intelligence."

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.