جست‌وجوی استاد و پژوهشگر

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۸ مورد دیگر

Dr. Siobahn Day Grady is an Assistant Professor of Information Science/Systems at North Carolina Central University (NCCU) and serves as the Founding Director of the Institute for Artificial Intelligence and Emerging Research (IAIER), which she established in 2025. She also holds leadership roles as Co-Director of The Center fOr Data Equity (CODE), Program Director of the Information Science Program, and Faculty Fellow in the Office of Faculty and Professional Development. Dr. Grady reports to the Provost with oversight of a $1M+ annual budget and $3M+ grant portfolio, managing a staff of 5 plus advisory boards. Ph.D. in Computer Science, North Carolina Agricultural & Technical State University (2018) M.S. in Computer Science, North Carolina Agricultural & Technical State University (2018) M.S. in Information Science, North Carolina Central University (2009) B.S. in Computer Science, Winston-Salem State University (2005) Dr. Grady's research focuses on the ethical implementation of artificial intelligence, with particular emphasis on fairness, bias mitigation, and equity in AI systems. Her work bridges technical AI development with social justice considerations, especially in healthcare applications and educational contexts. She has pioneered initiatives to increase AI literacy at HBCUs and developed frameworks for operationalizing fairness in AI governance. Her research interests include natural language processing, machine learning applications for social good, digital literacy programs for marginalized communities, and strategies to increase diversity in STEM fields through her STEM-It-Yourself program. Analysis of Dr. Grady's recent publications reveals a strong trajectory toward practical applications of AI ethics in real-world settings, particularly in healthcare and education. Her work demonstrates a consistent focus on creating frameworks that translate theoretical AI ethics principles into actionable guidelines for practitioners. There's a clear progression from technical AI research toward more interdisciplinary work that bridges computer science with social sciences, nursing, and education. Her publications increasingly address the needs of underrepresented communities and focus on practical implementation strategies rather than purely theoretical contributions. Winston-Salem State University 2023 Distinguished Alumni Award Durham Section of the National Council of Negro Women 2024 Distinguished Educator Sigma Iota Omega Chapter of Alpha Kappa Alpha Sorority, Incorporated® 2022 Soaring to Greater Heights in Science Technology Engineering Arts Mathematics Honoree The Links, Inc., Raleigh (NC) Chapter 2022 Emerald Award Honoree Association for Educational Communications and Technology (AECT) Culture, Learning, and Technology (CLT) Division 2023 Outstanding Publication Award Dr. Grady has secured significant grant funding totaling over $3 million, including a $1 million Google.org investment, $100K+ from Cisco, $15K from FICO, and funding from NTIA and NIH. She serves as Principal Investigator for the Digital Equity Leadership Program (DELP) and the Genomic Research and Data Science Center for Computation and Cloud Computing (GRADS-4C). Her mentoring extends to numerous students through programs like STEM-It-Yourself, which focuses on cultivating STEM identity among adolescent girls. Dr. Grady has established three endowed scholarships supporting economically disadvantaged students at multiple HBCUs, demonstrating her commitment to educational access. As Founding Director of the Institute for Artificial Intelligence and Emerging Research (IAIER), Dr. Grady leads North Carolina Central University's strategic vision for AI education, research, and policy. The institute includes the AI Emerging Scholars and Leaders Programs, which engage students, faculty, and staff in cross-disciplinary AI innovation. She has developed NCCU's first AI minor (pending approval) and serves as co-facilitator for the UNC AI Faculty Learning Community. Dr. Grady also holds leadership positions on the Governor's AI Council and multiple advisory boards, positioning NCCU as a national leader in responsible AI development and implementation.

Monika Unterreinerمشاهده پروفایل

مدرس

• Music Education
• Educational Equity
• Recognition Theory
• +۷ مورد دیگر

Dr. Monika Unterreiner serves as a part-time Lecturer in specialist practice at the Chair of Music Education within the Institute for Music Research at the University of Würzburg's Faculty of Philosophy. Since September 2022, she has contributed to music teacher education while maintaining connections to school practice. Education: MA in music education, modern and contemporary history, and history didactics from Ludwig Maximilian University of Munich Studies in school music at the University of Music and Performing Arts Munich Completed doctoral project in music education and school pedagogy in 2021 through the Bavarian State Ministry's 'Support for Young Academics' program Completed teaching internship in 2012 Dr. Unterreiner's research centers on recognition theory in music education, exploring how recognition mechanisms operate in heterogeneous classroom settings across primary, secondary, and special education contexts. Her work bridges theory and practice through design-based research approaches, with growing emphasis on digital media integration and AI applications in music education. She investigates community music practices, popular music didactics, and prejudice-conscious teaching approaches that address cultural participation and educational equity. Analysis of her recent publications (2020-2025) reveals a clear trajectory from foundational work on recognition theory toward contemporary challenges of digital transformation in music education. Her scholarship increasingly examines AI music generators, digital-analog tensions in teaching practice, and critical perspectives on whiteness and recognition in music classrooms. This evolution demonstrates her responsiveness to technological shifts while maintaining commitment to inclusive educational practices. As a practitioner-scholar, Dr. Unterreiner maintains strong connections between university teacher education and school practice. Her background as a secondary school teacher (2010-2017, 2020-2022) informs her research on bridging the gap between academic training and classroom realities. Her work with refugee populations and community music initiatives reflects commitment to music's role in social inclusion.

Cason Schmitمشاهده پروفایل

دانشیار

• Public Health Law
• Health Policy
• Health Informatics
• +۵ مورد دیگر

Cason Schmit serves as Associate Professor and Director of the Program in Health Law and Policy at Texas A&M University School of Public Health, where he bridges legal scholarship with public health practice through interdisciplinary research in health informatics, ethics, and policy. His work examines law as a structural determinant of health with a decade of expertise in legal epidemiology. His educational foundation includes a Juris Doctor from Arizona State University's Sandra Day O'Connor College of Law (2012) and a BA in Mathematics and Psychology from Willamette University (2007), complemented by professional certifications in Health Law, Intellectual Property, and Genomics and Biotechnology Law. Schmit's research program investigates health information technology policy through the lens of public health ethics, with particular focus on AI governance, privacy frameworks, and data sharing systems. His seminal work establishes law as a critical social determinant of health, examining how vaccination laws, telehealth regulations, and community health worker policies impact population outcomes. Current projects explore alignment between legal structures and ethical imperatives in health data systems, including his active role in IEEE AI governance standards development. Analysis of his 2021-2025 publications reveals consistent thematic focus on legal epidemiology's application to health information systems, with increasing emphasis on AI governance and ethical data sharing. His scholarship directly addresses tensions between privacy protections and public health data utility, particularly during emergencies like the COVID-19 pandemic, while developing practical frameworks for legal measurement in policy evaluation. Scientific awards are not documented in the provided materials. Schmit actively advises federal and state policymakers through collaborations with the CDC, Council for State and Territorial Epidemiologists, and National Committee on Vital and Health Statistics, translating research into actionable guidance for public health data modernization. His grant-funded work has directly shaped proposed federal policies on health data infrastructure. He leads the Program in Health Law and Policy and MPH program at Texas A&M while contributing to IEEE's AI governance standards workgroup, positioning his research at the critical intersection of emerging technologies and population health protection.

Ziang Xiaoمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Natural Language Processing
• Human-AI Interaction
• +۵ مورد دیگر

Ziang Xiao is an Assistant Professor in the Department of Computer Science at Johns Hopkins University's Whiting School of Engineering and a member of the Data Science and AI Institute. His research bridges human-computer interaction, natural language processing, and social psychology to understand human behavior at scale through AI systems. His educational background includes a Ph.D. in Computer Science from the University of Illinois Urbana-Champaign (co-advised by Prof. Hari Sundaram and Prof. Karrie Karahalios), where he also earned dual Bachelor's degrees in Psychology and Statistics & Computer Science under Prof. Dov Cohen. Prior to joining JHU, he was a postdoctoral researcher in the Fairness, Accountability, Transparency, and Ethics group at Microsoft Research Montréal. Xiao's research focuses on three interconnected areas: AI for Social Science (using LLMs to simulate human behavior), Human-centered Model Evaluation (developing frameworks like ECBD for evidence-centered benchmark design), and Information Seeking (studying how AI systems affect information diversity). His work emphasizes democratizing technology to operationalize human intuitions about behavior and decision-making, with notable contributions to LLM evaluation metrics and ethical AI design. Analysis of his recent publications reveals a strong trend toward human-centered AI evaluation, with increasing focus on LLM safety, value alignment, and interdisciplinary applications across social science domains. His work consistently appears in top-tier venues including CHI, ACL, and NeurIPS, with a 2024 CHI Best Paper Award for research on LLM-powered search systems. Best Paper Award at CHI 2024 for 'Generative Echo Chamber? Effect of LLM-Powered Search Systems on Diverse Information Seeking' Multiple publications in ACM/IEEE flagship conferences (CHI, ACL, NeurIPS) Research featured in Johns Hopkins news for social robot interruption handling and chatbot bias studies Xiao actively advises doctoral students and postdocs, with current advisees including Yu Lu Liu, Nikhil Sharma, and Han Jiang. His teaching includes graduate courses on Human-Computer Interaction and Advanced HCI Research Methods. He co-leads research initiatives at the intersection of AI and social science, collaborating with the Data Science and AI Institute to develop frameworks for responsible AI deployment. Current projects examine LLM vulnerabilities in GUI agents, multilingual information disparities, and adaptive decision support systems that balance automation with user control.

Jonathan H Chenمشاهده پروفایل

استادیار

• Molecular Pathology
• Clinical Informatics
• Machine Learning in Medicine
• +۲ مورد دیگر

Jonathan H Chen, MD, PhD, is an Assistant Professor in the Department of Pathology at Northwestern University's Feinberg School of Medicine, specializing in Molecular Pathology. Board-certified in Anatomic Pathology and Molecular Genetic Pathology by the American Board of Pathology, he bridges clinical pathology with computational innovation. Education: BS: The University of Chicago (2003) PhD: Yale School of Medicine (2012) MD: Yale School of Medicine (2013) Residency: Massachusetts General Hospital, Anatomic Pathology (2016) Fellowship: Harvard Medical School, Molecular Genetic Pathology (2018) Dr. Chen's research pioneers machine learning applications in clinical diagnostics, focusing on real-time genomic prediction, antimicrobial resistance surveillance through EHR mining, and continuous model evaluation for clinical decision support. His work integrates molecular pathology with data science to enhance diagnostic precision and therapeutic interventions in cancer and infectious diseases. Recent publications reveal a strong trend toward operationalizing AI in live clinical workflows, particularly in next-generation sequencing prediction and antimicrobial resistance resource development. These studies emphasize practical implementation challenges including model monitoring, real-world validation, and seamless integration into pathology practice. Scientific Awards: 2025 Young Physician-Scientist Award As a member of the College of American Pathologists (2025-present), Dr. Chen contributes to professional standards while advancing computational pathology through affiliations with Northwestern's Center for Human Immunobiology and Robert H. Lurie Comprehensive Cancer Center. His quality improvement initiatives demonstrate commitment to optimizing medication transitions in hospital settings.

Nicole van Nesمشاهده پروفایل

استاد

• Human-Centered Design
• Smart Mobility
• Human-Technology Interaction
• +۴ مورد دیگر

Nicole van Nes serves as Full Professor of Human-Centered Design for Smart Mobility at Delft University of Technology's Faculty of Industrial Design Engineering, while directing the Delft Design Lab on Automated Mobility and holding a board position at the TU Delft Transport and Mobility Institute (TMI). Her academic foundation combines a Master's in Industrial Design Engineering from TU Delft with a PhD in Social Science from Rotterdam University, enriched by research fellowships at Monash University Accident Research Centre in Melbourne and the Australian Road Research Board (ARRB) in Sydney. Nicole's research centers on designing seamless human-technology interactions for mobility systems, with deep focus on smart mobility solutions that enhance sustainability, safety, and inclusivity. Her interdisciplinary methodology bridges engineering and social sciences to create user-centered transportation innovations that address real-world behavioral challenges and systemic inefficiencies. Recent publications (2022-2025) reveal consistent advancement in human factors for automated driving, including driver fitness assessment frameworks, mode awareness interfaces, and naturalistic driving analyses. These works collectively pioneer safer transition strategies between automation levels while developing future mobility scenarios that prioritize human needs within evolving technological landscapes. Scientific Awards: No specific awards are documented in the provided materials. Nicole has led major European initiatives including UDRIVE (naturalistic driving data collection) and MEDIATOR (human factors in vehicle automation), with current engagements spanning the Automated Mobility Lab, MeBeSafe project (traffic safety behavior), and Taking the fast lane initiative (traffic congestion solutions). As Director of the Delft Design Lab on Automated Mobility, she spearheads research integrating generative AI with mobility design while fostering cross-disciplinary collaboration through the Transport and Mobility Institute to develop inclusive transportation systems for diverse user populations.

Günter Rudolphمشاهده پروفایل

استاد

• Computational Intelligence
• Evolutionary Algorithms
• Optimization
• +۵ مورد دیگر

Prof. Günter Rudolph is a Professor of Algorithmic Foundations and Education in Computer Science at the Technical University of Dortmund's Department of Computer Science. He leads Chair 11: Algorithm Engineering, focusing on Computational Intelligence (CI), Evolutionary Algorithms, and their applications in optimization and gaming. His research emphasizes theoretical analysis of CI methods, practical guidelines for operationalization, and applications in engineering, energy systems, and entertainment. Key research areas include multi-objective optimization, evolutionary robotics, and computational intelligence in games such as StarCraft and car racing simulations. He has advised numerous students on topics ranging from autonomous driving systems to procedurally generated game content. Rudolph collaborates internationally, including with CINVESTAV-IPN (Mexico) on multiobjective control methods and BMWi-funded projects on energy systems and forming process predictions. His work spans academic publications in journals like Genetic Programming and Evolvable Machines and conferences such as IEEE CIG. Notable projects include developing adaptive car racing controllers, optimizing energy supply systems in industrial parks, and advancing AI strategies in real-time strategy games. Rudolph's group actively contributes to game AI research through competitions like the StarCraft AI Competition and the Simulated Car Racing Championship, emphasizing the intersection of computational intelligence and entertainment.

Christian Kurtzمشاهده پروفایل

پژوهشگر

• Information Systems
• Socio-technical Ecosystems
• Data Privacy
• +۴ مورد دیگر

Dr. Christian Kurtz is a Postdoctoral Researcher and research project coordinator at the IT Management and Consulting working group within the Department of Informatics, Faculty of Mathematics, Informatics and Natural Sciences at the University of Hamburg. He has held this position since 2022, following his role as a Research Associate at the same institution from 2017-2022. His academic career is complemented by industry experience as an IT Consultant at NTT DATA Deutschland GmbH. Dr. Kurtz's educational background includes: M.A. in Management & Controlling / Information Systems from Leuphana University of Lüneburg (2013-2016) B.Sc. in Business Administration and Economics from Paderborn University (2010-2013) His research is grounded in Information Systems (IS), with a focus on societal values and regulations in the design and governance of socio-technical ecosystems. He examines how regulations—such as the GDPR and the AI Act—and their underlying protective aims (e.g., privacy, transparency) can be operationalized within platform, service, and data ecosystems. This includes translating abstract legal norms into IS design—and, in turn, using insights from IS research to inform policy and regulatory development. To support this bidirectional relationship of IS and normative frameworks, he investigates how interdisciplinary collaboration—particularly between IS, law, and ethics—can be enabled, with a key focus on the use of boundary objects, such as architectural models, that help bridge disciplinary perspectives and support shared understanding. Dr. Kurtz's recent publications demonstrate a strong focus on regulatory compliance in digital ecosystems, particularly examining how information systems can be designed to meet legal requirements while maintaining functionality. His work spans multiple domains including platform accountability, GDPR implementation challenges, and the development of interdisciplinary methods for ecosystem architecture that inform regulatory reasoning. There's a clear trend toward increasingly sophisticated approaches to bridging the gap between technical systems design and legal/ethical requirements. Dr. Kurtz has received numerous academic and professional awards: Best Paper award at HICSS 54 (2021) Hamburg Teaching Prize for outstanding and innovative teaching (2021) Best Paper Nomination at HICSS 52 (2019) 3rd prize in Digital Science Slam on Computational Propaganda (2021) Class of the Year award at Leuphana University of Lüneburg (2016) Entrepreneurship Award at Leuphana University of Lüneburg (2015) Lower Saxony scholarship for talented students (2014) Innovation Award at NTT DATA Open Innovation Challenge (2017) Idea Competition Prize from Chamber of Skilled Crafts (2014) Finalist in Lüneburg Business Awards (2014) As a dedicated mentor, Dr. Kurtz has supervised numerous Master's and Bachelor's theses focusing on cutting-edge topics in AI, data privacy, and digital transformation. His academic service includes representation roles in the Ethics Commission and examination boards. He has been actively involved in multiple research projects including "Informing Regulatory Reasoning on Algorithmic Systems in Societal Communication with STEAM" (2022-2025), "DL2030 - Digitale Dienstleistungen als Erfolgsfaktor für die Wertschöpfung der Zukunft" (2019-2023), and "Developing the socio-technical architecture method to inform policy choices in the shaping of COVID-19 digital infrastructure" (2021-2022). Dr. Kurtz is actively engaged in the academic community through various leadership roles including Track Chair for ECIS 2026, Minitrack Chair for HICSS 58 and 59, and Associate Editor for multiple conference tracks. He serves as a reviewer for prestigious journals including Business Research, Communications of the Association for Information Systems, and Journal of Information Technology.

Chikaodi Gloria Ubaمشاهده پروفایل

پژوهشگر ارشد

• Digital Transformation
• Artificial Intelligence
• AI Management
• +۳ مورد دیگر

Chikaodi Gloria Uba serves as a Scientific Associate (Research Fellow) in the Department of Computer Science at the University of Hamburg's Faculty of Mathematics, Informatics and Natural Sciences. Her work centers on the digital transformation of organizations through artificial intelligence, with specific expertise in AI management, lifecycle processes, and MLOps implementation. Education: M.Sc. in Business Engineering Her research explores the strategic integration of AI into enterprise operations, focusing on commissioning frameworks and operationalization through MLOps. She investigates how organizations navigate AI-driven transformation using models like the 3D-Model for enterprise-wide change, bridging technical AI capabilities with business strategy and organizational adaptation. Her scholarly output demonstrates significant contributions to AI transformation literature, highlighted by a Best Paper Award-winning publication at HICSS 2023. This work establishes connections between AI strategy development, implementation challenges, and organizational change management within complex business environments. Awards: Best Paper Award at Hawaii International Conference on System Sciences (HICSS) 2023 She actively supervises bachelor's and master's theses on digital transformation topics, particularly through the Data-driven Solutions for the Smart City Hamburg (D²S²C Hamburg) initiative. Her teaching portfolio shows consistent involvement in innovation-focused courses since 2021, though specific grant funding details remain undisclosed in available materials. As a core member of the IT Management and Consulting (ITMC) research group, she collaborates on interdisciplinary projects addressing real-world technology management challenges, with recent emphasis on smart city applications and AI-driven business innovation.

Sara Perssonمشاهده پروفایل

پژوهشگر

• Sustainability Discourses
• Corporate Social Responsibility
• Circular Economy
• +۴ مورد دیگر

Sara Persson is a Project Researcher at the Department of Social Sciences, School of Social Sciences, Södertörn University. Her work critically examines how sustainability and corporate social responsibility (CSR) are operationalized in extractive industries, focusing on power dynamics between corporations and local communities. Awarded Wallander Scholarship (2021) for postdoctoral research on Swedish mining and sustainability discourses Involved in Formas-funded project 'Leading the circular transition – bridging implementation gaps in sustainable public procurement' Guest Editor for a special issue on creative academic writing in Culture and Organization Member of Södertörn's EcoJust research platform and Energy and Climate Group Her research bridges Gramscian hegemony theory and Political Discourse Theory to analyze sustainability standards in the Albanian oil industry and Swedish 'green mineral' extraction. She also advocates for creative academic writing methods, including autoethnography. Recent publications focus on corporate hegemony in sustainability discourses, gender dynamics in extractive industries, and critical CSR practices. Key themes include environmental justice, community resistance, and the paradoxes of green transitions. Recipient of Wallander Scholarship for full-time research (2021) Active participation in national AI and welfare state research initiatives via Wallenberg Foundations Persson teaches in the master's program 'Leadership for sustainable development' and contributes to debates on climate policy through her affiliations.

• Ethics of AI
• Neurotechnology Ethics
• Applied Ethics
• +۳ مورد دیگر

Dr. Giulio Mecacci is an Associate Professor at the Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen. His research focuses on ethical, legal, and societal implications of AI and neurotechnologies, particularly operationalizing the concept of Meaningful Human Control to address responsibility gaps in human-AI interaction. He holds academic appointments at the Donders Centre for Cognition and the Donders Institute. Teaching responsibilities include courses on AI ethics, societal impacts of AI, and Neurophilosophy within the CNS master’s programme. He actively promotes dialogue between science, technology, and society through education. Recipient of the 2021 Education Award from the Faculty of Social Sciences, his work bridges applied ethics with technological development. His research outputs span AI governance frameworks, neurotechnology ethics, and responsibility gaps in autonomous systems.

• Artificial Intelligence
• Machine Learning
• Edge Computing
• +۴ مورد دیگر

Sergio Moreschini is a Postdoctoral Researcher in Computing Sciences, focusing on Artificial Intelligence, Edge Computing, and MLOps. His research explores the integration of AI techniques in microservices, cloud-edge continuum systems, and distributed home automation frameworks. He has contributed to foundational studies such as a Systematic Mapping Study on AI in Microservices Life-Cycle and developed frameworks like Flexconnect for mobile computational offloading. Education: He holds a Bachelor of Science in Technology (2012) and a Higher-Degree in Computing from Università Degli Studi Roma Tre (2016). His work aligns with UN Sustainable Development Goal 4 (Quality Education) through contributions to educational tools and methodologies. Research Interests : Moreschini investigates AI lifecycle management, edge-cloud system orchestration, vulnerability analysis in open-source components, and generative AI applications in software architecture. Key areas include fault-tolerant distributed systems, cognitive cloud continuum frameworks, and MLOps tool ecosystems. Recent Trends in Publications : Recent work emphasizes MLOps adoption challenges, self-organizing edge computing for visual SLAM, and best practices in resource provisioning for cognitive systems. He has explored trade-offs between continuous training and transfer learning in edge environments, and evaluated vulnerability severity metrics in open-source software. Awards : Won the Best Paper Award in 2022 for contributions to industrial edge service scheduling. Data Contributions : Co-created datasets like RARE (cloud-native memory anomalies) and CIVIT (integral microscopy recordings). His collaborative projects include the 6GSoft initiative for edge-cloud continuum systems and the OSSARA tool for open-source component risk assessment. Active in international conferences like IoT and SEAA, he bridges academic research with industrial applications in edge computing and AI infrastructure.

Grace Haafمشاهده پروفایل

دانشیار بالینی

• Human-AI Joint Decision Making
• Decision-Making Under Uncertainty
• Business Analytics
• +۷ مورد دیگر

Grace Haaf is a Clinical Associate Professor in the Department of Technology, Operations, and Statistics at the Leonard N. Stern School of Business, New York University, where she rejoined in 2025. She previously taught business analytics at NYU Shanghai and has extensive industry experience in data science and analytics strategy. Her educational background includes a Ph.D. in Mechanical Engineering from Carnegie Mellon University (2014), an M.S. in Mechanical Engineering from Carnegie Mellon University (2012), and a B.S. in Mechanical Engineering from Northwestern University (2008). Her research centers on human-AI collaborative decision-making, decision theory under uncertainty, and the integration of technology, business, and product design. She applies game-theoretic models to analyze agent behavior in mixed human-algorithm environments. Grace Haaf teaches courses including Business Analytics, Databases for Business Analytics, Marketing Analytics, Projects in Programming, and Statistics for Business and Economics. She has held significant roles in industry, including rapid evaluator at Google X and analytics consultant at McKinsey & Company, where she developed training programs for advanced analytics. Her expertise includes analytics program strategy, model operationalization, and organizational design for data science teams.

Tonya Schneidereithمشاهده پروفایل

دانشیار

• Medication Safety Research
• Simulation-Based Education
• Artificial Intelligence in Nursing
• +۳ مورد دیگر

Tonya Schneidereith is an Associate Professor at Johns Hopkins University School of Nursing, specializing in medication safety research and simulation-based education. With dual clinical certifications as a Pediatric Critical Care Nurse Practitioner (PPCNP-BC and CPNP-AC), she pioneered the use of Google Glass in nursing education and authored key simulation resources for the National League for Nursing. Her work focuses on optimizing dosage calculation teaching methods and advancing simulation pedagogy. Education: BSN (Florida State University), MSN (University of Pennsylvania), MBA (University of Maryland), PhD (Johns Hopkins University) Research interests include medication safety , artificial intelligence in nursing , and standardization of simulation education . Her publications demonstrate expertise in wearable technology applications (Google Glass), simulation program operationalization, and terminology harmonization across healthcare education. Recent work explores AI integration and social media recruitment methods in nursing education. Scientific awards include: Fellow, Society for Simulation in Healthcare Academy (FSSH) Fellow, American Academy of Nursing (FAAN) 2015 Innovative Teaching with Technology Award (Stevenson University) She serves as Associate Editor for National Organization of Nurse Practitioner Faculties Simulation Guidelines and created the 2020 Annual Review of Nursing Research: Healthcare Simulation. Her simulation expertise is recognized internationally through advanced certifications (CHSE-A) and leadership roles.

Eliana Brianzaمشاهده پروفایل

پژوهشگر

• Educational Technology
• Teacher Education
• Media Didactics
• +۲ مورد دیگر

Eliana Brianza serves as a Teaching and Research Assistant at the University of Zurich's Chair of General Didactics and Media Didactics since 2019, contributing to educational technology research and teacher training programs. Her academic credentials include a Certificate of Advanced Studies (CAS) in University Teaching from UZH (2021-2024), an M.Sc. in Psychology (2018), and a B.Sc. in Psychology (2015), all from the University of Zurich. 2021-2024: CAS in University Teaching, University of Zurich 2018: M.Sc. Psychology, University of Zurich 2015: B.Sc. Psychology, University of Zurich Dr. Brianza's research focuses on Technological Pedagogical Content Knowledge (TPACK), examining how contextual factors influence technology integration in teaching. Her work spans systematic literature reviews, empirical studies on preservice teacher development, and emerging areas like AI readiness and virtual reality applications. She investigates pandemic impacts on digital teaching practices and experience-based knowledge evolution, revealing a clear trajectory toward contextual and adaptive technology frameworks in education. Her publication analysis shows concentrated expertise in TPACK validation, contextual knowledge operationalization, and innovative training tools like ClassVRoom. Recent work increasingly addresses AI integration challenges and virtual environment efficacy, reflecting responsiveness to technological shifts in educational landscapes. As part of UZH's Chair of General Didactics and Media Didactics, she collaborates on developing digital literacy frameworks and the ClassVRoom virtual reality platform for preservice teacher practice, contributing to next-generation educator preparation through technology-enhanced pedagogical innovation.