جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Dr. Philipp Mock serves as a Research Fellow at the Leibniz Institute for Knowledge Media (IWM) in Tübingen, Germany, where he has been a core member of the Media Development Group since 2014. His technical expertise centers on developing machine learning algorithms and AI systems for human-machine interaction, with current responsibilities including software development and methodological consulting for ML applications. Education: PhD in Computer Science, University of Tübingen (2017) Diploma in Computer Science, University of Tübingen (2004-2011) Mock's research integrates Human-Computer Interaction with machine learning to analyze behavioral patterns through interaction data. His work spans multimodal interfaces, educational technology, and cognitive assessment systems, with particular focus on translating touch interaction metrics into predictors of cognitive states (ADHD risk, workload) and developing novel collaborative interfaces for tabletop displays. This interdisciplinary approach bridges computer science, cognitive psychology, and educational design to create adaptive systems that respond to user behavior in real-time. His publication trajectory reveals a clear evolution from foundational work on interactive surface technologies (2012-2015) toward sophisticated ML applications for behavioral analysis (2016-2018). Current projects like the longitudinal human-AI interaction study (2024-2026) demonstrate continued innovation in understanding long-term dynamics between users and intelligent systems, with strong emphasis on real-world educational and clinical applications. Mock actively contributes to multiple IWM research labs including Multimodal Interaction, Everyday Media, Perception and Action, and Knowledge Construction. His collaborative projects such as the human-AI interaction study span these labs, reflecting an integrated approach to studying how people interact with increasingly sophisticated AI systems across diverse contexts from museums to educational settings.

• Keystroke Dynamics
• Machine Learning
• Data Mining
• +۶ مورد دیگر

Ioannis Tsimperidis is a Researcher at the Department of Informatics, Democritus University of Thrace (DUTH). His career includes roles as a Secondary Education teacher (2006-2021) and industry executive (2003-2004). Since 2021, he has been affiliated with DUTH's DI.PAE unit, focusing on interdisciplinary research. Education: BSc (Electrical & Computer Engineering, Aristotle University of Thessaloniki, 1997); MSc/PhD (Democritus University of Thrace, 2002/2017). Research interests span keystroke dynamics for user profiling, machine learning applications in cybersecurity and education, and deep learning for material defect detection. His work bridges behavioral science and engineering, with notable contributions to age/education-level prediction via typing patterns and marble crack detection via RGB-thermal fusion. Publications reflect a dual focus: technical advancements in keystroke-based user identification and pedagogical innovations in STEM education. His 2023-2024 work highlights cross-disciplinary impact, applying AI to both industrial (marble quality control) and educational challenges (mobile tech barriers). No awards/grants explicitly mentioned. Advising record unavailable. Active in multiple educational structures including IN.EP., D.I.E.K., and K.E.K., demonstrating sustained engagement with diverse educational frameworks.

Elif Şenerمشاهده پروفایل

مدرس

• Interaction Design
• User Experience (UX)
• Virtual Reality (VR)
• +۶ مورد دیگر

Dr. Elif Şener is a Lecturer at the School of Design, University of Leeds, with expertise in interaction design, UX of Virtual Reality (VR), immersive typography, and affective computing. Her academic journey began at İzmir University of Economics (BFA in Visual Communication Design) and continued at Sabancı University (MFA in Visual Arts & Visual Communication Design), before completing her Ph.D. in Design at North Carolina State University as a Fulbright Scholar. Education: BFA in Visual Communication Design, İzmir University of Economics MFA in Visual Arts & Visual Communication Design, Sabancı University Ph.D. in Design, North Carolina State University Şener’s research focuses on the intersection of design, technology, and user experience, particularly in virtual reality. Her master’s project MoodFace explored keystroke dynamics visualization, while her doctoral work investigated 3D typographic layouts in VR and their impact on memory recall. She emphasizes the democratization of XR technologies for educational and everyday contexts. Scientific Awards: Fulbright Scholarship (2018) At the University of Leeds, Şener teaches MA Design and conducts research into immersive analytics, typographic innovation, and user-centered design practices. She welcomes inquiries from prospective PhD students interested in her work.

• Educational Data Mining
• Learning Analytics
• Cognitive Psychology
• +۵ مورد دیگر

Caitlin Mills is an Assistant Professor in the Department of Educational Psychology at the University of Minnesota's College of Education and Human Development. She also maintains affiliations with the University of Southern California's Keck School of Medicine (Division of Bioinformatics) and Harvard Medical School. Her research bridges educational psychology, cognitive science, and learning analytics. Her primary research interests focus on mind wandering detection during learning , educational data mining , learning analytics , and eye tracking technologies for educational purposes. She investigates how cognitive processes like attention, task-unrelated thoughts, and comprehension can be measured and enhanced through technological interventions. Her work increasingly addresses neurodivergent learners and inclusive educational technologies. Analysis of her recent publications shows a strong trend toward developing non-invasive methods for monitoring cognitive states during learning, particularly through webcam-based eye tracking and keystroke analysis. Her research spans multiple domains including virtual reality learning environments, automotive safety interfaces, and language-based cognitive assessment. She has made significant contributions to understanding how mind wandering impacts learning outcomes across diverse populations. Mills has served as co-editor for the Proceedings of the International Conference on Educational Data Mining (EDM 2025) and regularly publishes in top venues including the Journal of Learning Analytics (LAK), Educational Data Mining (EDM), and Cognitive Science. Her collaborative work includes major projects with researchers from USC, Harvard, and other institutions, focusing on developing technologies that can detect and respond to learners' cognitive states in real-time to improve educational outcomes. She has developed innovative approaches to measuring attentional states during learning tasks using various physiological and behavioral metrics.

Martin Staceyمشاهده پروفایل

مدرس ارشد

• Design Thinking
• Design Processes
• Human-Computer Interaction
• +۳ مورد دیگر

Dr Martin Stacey is a Senior Lecturer at De Montfort University's Faculty of Computing, Engineering and Media, where he works within the School of Computer Science and Informatics. His interdisciplinary background combines psychology and artificial intelligence to inform both teaching and research activities focused on human-computer interaction and information design. His educational background includes a BA in Experimental Psychology from the University of Oxford, an MS in Psychology from Carnegie-Mellon University, and a PhD in Artificial Intelligence from the University of Aberdeen. His research spans cognitive science, design methodology, and human factors engineering. Stacey's research interests center on design thinking , design processes , and human-design tool interaction . His work examines how designers use representations of information, factors influencing problem structuring, causal modeling of design processes, and the role of object references in design. His interdisciplinary approach integrates psychology, sociology, AI, and philosophy to compare design processes across industries. Analysis of his recent publications reveals a consistent focus on the epistemology of design processes, with increasing attention to method ecosystems, knowledge representation in engineering, and the philosophical foundations of design. His work bridges theoretical design research with practical applications in biomedical engineering, digital governance, and stress monitoring systems. As an academic supervisor, he currently advises PhD student Yee Mei Lim. His professional service includes membership on the Advisory Board for Design Computing and Cognition conferences (2006-2014) and extensive peer review activities for leading design and engineering journals.

Melvin McInnisمشاهده پروفایل

استاد

• Bipolar Disorder
• Circadian Rhythms
• Genomic Psychiatry
• +۵ مورد دیگر

Melvin McInnis serves as Professor of Psychiatry and Professor of Learning Health Sciences at the University of Michigan Medical School. He holds multiple leadership roles including Program Director in Psychiatry and membership in the Center for Computational Medicine and Bioinformatics and the Eisenberg Family Depression Center. His research integrates genomic, circadian, and computational approaches to bipolar disorder. Dr. McInnis's research focuses on bipolar disorder pathophysiology with emphasis on circadian rhythm mechanisms, lithium treatment response, and digital phenotyping. His work employs Genomic analyses of patient-derived neural cells Longitudinal mood tracking through digital tools (BiAffect study) Computational ontologies for cross-study data integration Machine learning approaches to suicide risk prediction Investigation of circadian-sleep-mood relationships His publications consistently address mood instability metrics, bipolar subtyping, and precision medicine applications. Analysis of his 15 most recent publications reveals strong emphasis on digital mental health (7/15 articles), circadian biology (6/15), and computational approaches (5/15). Key trends include development of novel mood instability metrics, integration of multi-omics data, and real-world validation of digital biomarkers through passive smartphone sensing. Dr. McInnis secures substantial research funding through NIH and private foundations, with 55 active grants including: NIH R01 MH139125: "Detecting dynamic fluctuations in emotion, mood, and functioning" (2023-2028) NIH R01 MH131845: "Correcting Circadian Rhythms in Bipolar Disorder" (2023-2025) NIH R01 MH129624: "Affective and Cognitive Mechanisms of Emotion-Based Impulsivity" (2023-2028) Brain & Behavior Research Foundation: "Modeling and Predicting Intraindividual Mood Dynamics" (2023-2025) His work involves extensive international collaboration through the Global Bipolar Cohort network. He leads the Heinz C. Prechter Longitudinal Study of Bipolar Disorder, a comprehensive research program integrating genomic, clinical, and digital data. His laboratory develops computational frameworks including the Bipolar Disorder Ontology (OBD) and participates in the Michigan Institute for Clinical and Health Research (MICHR). Current initiatives focus on developing learning health networks for mood disorders and validating circadian-based interventions.

Yan Maمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Artificial Intelligence
• AI-powered input technologies
• +۴ مورد دیگر

Yan Ma is a tenure-track Assistant Professor in the Department of Computer Science at Kean University, specializing in Human-Computer Interaction and Artificial Intelligence. His research develops innovative AI-powered interaction techniques with strong emphasis on accessibility and user performance enhancement. Dr. Ma's educational background includes: Ph.D. in Computer Science, Stony Brook University (Advised by Prof. Xiaojun Bi) B.S. in Computer Science, Binghamton University B.S. in Mathematics, Renmin University of China His research focuses on transforming human-computer interaction through: LLM-Powered Interaction: Developing novel text entry methods for smartphones and VR environments Accessibility Engineering: Creating inclusive technologies like soft Braille keyboards and ASL recognition systems Performance Modeling: Using GANs and deep learning to understand and optimize user input behavior VR/XR Innovation: Designing next-generation interaction techniques for immersive environments Professor Ma's recent publications (2021-2025) reveal a clear trajectory toward LLM integration in interaction design, with four major publications already in 2025 across CHI, UIST, and IEEE VR venues. His work consistently bridges theoretical modeling and practical applications, particularly in accessibility domains. Key recognition includes: Best Paper Honorable Mention Award at ACM CHI 2023 As an active educator, Professor Ma teaches core computer science courses while building his research program. His service as a reviewer for top conferences (CHI, UIST, IEEE VR) and journals demonstrates his standing in the HCI research community. Students in his group gain hands-on experience with cutting-edge AI/VR technologies and opportunities to publish at premier venues. Though no formal lab name is established, his research group at Kean University maintains strong connections with Stony Brook's HCI community, facilitating collaborative projects in input modeling and accessibility research.

Daqing Houمشاهده پروفایل

استاد

• Software Engineering
• Cybersecurity
• Software Education
• +۴ مورد دیگر

Daqing Hou serves as Professor and Chair of the Department of Software Engineering within the Golisano College of Computing and Information Sciences at Rochester Institute of Technology (RIT). His leadership integrates RIT's cooperative education model with industry-aligned teaching methodologies to prepare students for software development careers. Research spans Software Engineering (focusing on empirical studies and human factors for efficient development), Cybersecurity , and Software Education innovation. He pioneers Project-based Learning (PjBL) frameworks and applies software solutions to behavioral biometrics (keystroke/mouse dynamics), smart housing systems, and energy management. His work emphasizes authentic, hands-on learning through RIT's co-op program. Funded by the National Science Foundation (NSF), Dr. Hou leads initiatives in cybersecurity integration and REU programs. His January 2025 NSF grant advances cybersecurity education, while ongoing projects bridge academic research with industry practices through experiential learning frameworks.