جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction (HCI)
• Computer Supported Cooperative Work (CSCW)
• Ubiquitous Computing
• +۳ مورد دیگر

Tony Tang is an Associate Professor in the School of Computing and Information Systems at Singapore Management University (SMU), where he leads the RICELab (Rethinking Interaction, Collaboration, and Engagement). Previously, he held roles at the University of Toronto and University of Calgary. His research focuses on Human-Computer Interaction (HCI), including Human-AI interaction, mixed reality interfaces, and ubiquitous computing. Education : PhD in Electrical and Computer Engineering, University of British Columbia (2010) MSc in Computer Science, University of Calgary (2005) BSc in Computer Science and Psychology, Simon Fraser University (2002) Research Interests : Tang’s work bridges theoretical and applied HCI, emphasizing systems that enhance human collaboration and interaction with technology. His lab explores topics like AI feedback mechanisms, mixed reality environments, and interfaces for distributed teams. Awards & Grants : ACM CHI Academy Member (2014) Funded by NAVER ($1.25M over 5 years), Meta ($30K), and SMU-SUTD Tier 1 Grant (S$100K) Advising & Grants : Supervised 26 graduate students and multiple postdoctoral fellows. His grants include work on immersive analytics and teleconferencing tools for physiotherapy. Labs & Teams : Directs the RICELab, which designs novel interaction systems for collaboration and learning. Active in the HCI community, serving as General Co-chair for CSCW 2022.

Ivett Orsolya Bacskayمشاهده پروفایل

استادیار

• Analytical Chemistry
• Separation Science
• Chromatography
• +۱۱ مورد دیگر

Dr. Ivett Orsolya Bacskay is an Assistant Professor at the Department of Analytical and Environmental Chemistry, Institute of Chemistry, Faculty of Science, University of Szeged. Her research focuses on fundamental and applied aspects of separation science, particularly in liquid chromatography, with expertise in retention mechanisms, mass transfer, and stationary phase characterization. Research Interests: Her work spans several key areas in analytical chemistry, including hydrophilic interaction liquid chromatography (HILIC), size-exclusion chromatography, chiral separations, pore size distribution analysis, and molecular imprinting for artificial antibody development. She investigates both theoretical models and practical applications in chromatographic systems. An analysis of her recent publications (2010–2025) reveals a strong emphasis on improving chromatographic efficiency and understanding molecular interactions in separation processes. Her studies frequently address challenges in hold-up volume determination, overloading effects, and mass transfer in various stationary phases, contributing significantly to the advancement of HPLC and LC-MS methodologies. Scientific Awards: No awards mentioned in the provided text. Advising and Grants: While specific details about students or funded projects are not listed, her active research output and faculty position suggest involvement in mentoring graduate students and securing research support. She has contributed to interdisciplinary studies involving neuropharmacology and plant biochemistry, indicating collaborative research efforts. Labs and Teams: Dr. Bacskay is part of the Institute of Chemistry at the University of Szeged, where she conducts research within the Department of Analytical and Environmental Chemistry. Her work likely involves collaboration with analytical chemistry research groups focusing on method development, column technology, and environmental or pharmaceutical analysis.

Dolorès Bertraisمشاهده پروفایل

پژوهشگر ارشد

• Urban Planning
• Environmental Justice
• Socio-spatial Justice
• +۶ مورد دیگر

Dolorès Bertrais is a Post-Doctoral Fellow at the University of Geneva's Department of Geography and Environment (UNIGE, Switzerland). Her work focuses on the political ontology of the living in urban contexts, materiality of cities (especially sand and aggregates), and environmental/socio-spatial justice across Southeast Asia and East Africa (Rwanda). After defending her 2024 thesis on Green City models in Phnom Penh and Kigali, she continues researching urban dynamics and production of space. Teaching: Courses on urban history, territorial projects, and globalization in the Global South Key Conferences: Presented at Geneva, Montreal, Mexico City, and Málaga events on Green City discourse and urban materiality Publications: 15+ works on urban ecology, including 2024 article on Phnom Penh policy analysis and 2025 book chapter on graphical ethnography

• Human-AI Interaction
• Explainable AI
• Ethical AI
• +۵ مورد دیگر

Chiara Natali is a PhD Student in Computer Science at University of Milan-Bicocca (2022-present) and a Visiting Research Fellow at the Dalle Molle Institute for Artificial Intelligence USI-SUPSI, supported by a Swiss Government Excellence Research Fellowship. She serves as a Lecturer for Interaction Design Lab and Human-Computer Interaction courses at University of Milano-Bicocca, and as a Tutor for Advanced Data Management and Decision Support Systems and Human-System Interaction courses across multiple Italian universities. Her educational background includes: MA in Politics, Philosophy and Public Affairs at University of Milan (2020-2022) Master's in Digital Communication Strategy at IED, Milan (2019-2020) BSc in International Politics and Government at Bocconi University, Milan (2016-2019) Natali's research centers on the complex relationship between humans and AI systems, with particular focus on Human-AI Interaction, Explainable AI (XAI), Ethical AI, and her signature concept of Frictional AI. She investigates the multidirectional effects of AI on human cognitive faculties, examining the tension between Augmentation and Deskilling. Her work explores how intentional design friction can serve as a debiasing strategy against Automation Bias, promoting more thoughtful human-AI collaboration while preserving human agency and critical thinking. Her publication record reveals a strong emphasis on practical applications of XAI in high-stakes domains like healthcare, with particular attention to medical decision-making processes. Her research consistently addresses the challenge of designing AI systems that support rather than replace human expertise, exploring how explanations impact accuracy in hybrid decision-making and how to measure technology dominance in AI-supported environments. Her significant contributions have been recognized with: Best Paper Award at the World Conference on Explainable Artificial Intelligence (2024) Best Doctoral Consortium Award at CEUR Workshop Proceedings (2023) Natali actively shapes her field through academic service, serving as PUBLICITY & PROCEEDINGS CHAIR for HHAI 2025 and organizing multiple workshops on Human-Centred Machine Learning, Algorithmic Authority, and Frictional AI. She also contributes to gender equality in STEM as a Science Ambassador for her institution's Gender Equality Plan and previously served as PhD co-representative at the Department Board. Her interdisciplinary approach extends into creative domains, where she is developing an Interactive AI Opera on 'The Garden of (Un)Earthly AI's' funded by the University of Edinburgh's Generative AI Laboratory, and has curated projects exploring Human-AI Music Co-Creation and live-coding music performances.

Bruce M. McLarenمشاهده پروفایل

استاد

• Learning Sciences
• Educational Technologies
• Human-Centered AI
• +۷ مورد دیگر

Bruce M. McLaren is a Professor at Carnegie Mellon University's Human-Computer Interaction Institute (HCII), where he heads the McLearn Lab. He previously served as President of the International Artificial Intelligence in Education Society (2017-2019) and has been elected to the Executive Committee of the AI-ED Executive Committee for two separate terms (2012-2017 and 2022-2027). Dr. McLaren's research focuses on how technology can support education through digital learning games , intelligent tutoring systems , and collaborative learning environments. His work has demonstrated that students can learn decimals more effectively through Internet-based learning games compared to conventional methods. He has also conducted significant research on erroneous examples in learning, showing how students benefit from working with incorrect solutions alongside intelligent tutors. His publications reveal a strong trend toward integrating artificial intelligence with educational technologies, particularly in analyzing student learning patterns, developing adaptive educational games, and creating tools that support both students and teachers in classroom settings. Recent work increasingly focuses on the application of generative AI like ChatGPT in educational contexts. Best Paper Award at ECTEL 2023 for research on ChatGPT in decimal learning Fulbright Scholarship recipient for educational technology work in Chile (2019) Multiple best paper awards at major AI in Education conferences Erskine Fellowship for teaching Intelligent Tutoring Systems in New Zealand As an advisor, Professor McLaren has mentored numerous students in the HCII program and has secured significant research funding, including NSF grants for projects like AdaptErrEx and LASAD. His lab, the McLearn Lab, serves as a hub for interdisciplinary research at the intersection of learning sciences and artificial intelligence. Beyond academia, he brings over 20 years of commercial sector experience, having served as Director of eCommerce Technologies at OpenWebs Corporation and leading expert system projects at Carnegie Group, Inc.

Helen Armstrongمشاهده پروفایل

استاد

• Inclusive Design
• Machine Learning
• Digital Rights
• +۳ مورد دیگر

Helen Armstrong serves as Professor of Graphic & Experience Design and Director of the Graduate Program in Graphic & Experience Design at North Carolina State University's College of Design. Her academic leadership spans research, publication, and industry collaboration at the intersection of design and artificial intelligence. Her educational background includes an MA in English Literature from The University of Mississippi, an MA in Publication Design from the University of Baltimore, and an MFA in Graphic Design from The Maryland Institute College of Art. Armstrong's research focuses on digital rights, human-machine teaming, and accessible design, driven by her advocacy for inclusive interfaces as a parent of a child with disabilities. She explores how designers can establish leadership in AI development through human-centered approaches, particularly in explainable AI systems and trust calibration between humans and machines. Analysis of her recent publications reveals a dominant trend toward applying design principles to artificial intelligence challenges, with increasing emphasis on visualization techniques for uncertainty representation, ethical considerations in AI, and inclusive design methodologies. Her work consistently bridges theoretical frameworks with practical industry applications across diverse domains including intelligence analysis, financial services, and assistive technologies. Scientific recognition includes: University Faculty Scholar at NC State (2018) Armstrong actively mentors graduate and undergraduate students through studio courses and research projects while securing substantial industry funding. Her sponsored research portfolio features partnerships with SAS Analytics, IBM, REI, Advance Auto Parts, Sealed Air, Fidelity Investments, and the Laboratory for Analytic Sciences. Current projects address critical challenges in human-AI teaming, including visualizing confidence scores for speaker models, knowledge transfer in wealth management, and personalized shopping experiences. She maintains deep collaboration with the NC State Laboratory for Analytic Sciences (LAS) and contributes to the K-12 Design Lab initiative, extending her expertise in inclusive design to educational outreach programs and community engagement efforts.

Breffni Nooneمشاهده پروفایل

دانشیار

• Revenue Management
• Profit Optimization
• Consumer Behavior
• +۳ مورد دیگر

Breffni Noone serves as an Associate Professor in the School of Hospitality Management within Pennsylvania State University's College of Health and Human Development, specializing in revenue management and profit optimization across hospitality assets including hotels, restaurants, golf facilities, and spas. Her work bridges theoretical research with practical industry applications through data-driven decision frameworks. Dr. Noone earned her Ph.D. in Operations Management from Cornell University (2004), an M.B.S. from Dublin City University, Ireland (1996), and a B.Sc. in Management/Higher Diploma in Hotel & Catering Management from University of Dublin, Trinity College and Technological University Dublin, Ireland (1994). Her academic journey reflects deep integration of operations research and hospitality management. Her research centers on revenue management systems, consumer behavior in pricing contexts, and sustainable profit optimization. Key investigations include scarcity-based promotions, menu engineering, online booking psychology, and non-traditional revenue applications in golf. She emphasizes data visualization and operational design to balance profitability with social and environmental responsibility, examining how non-price information shapes consumer decisions across service encounters. Analysis of her 15 most recent publications reveals expanding research scope from core hotel revenue management into crisis resilience, social inclusion, and cross-industry applications. Recent work addresses waiting-time psychology, employment biases against houseless individuals, and AI-driven commercial talent development, demonstrating adaptation to contemporary industry challenges while maintaining methodological rigor in experimental and field studies. No scientific awards were documented in the provided materials, though her consistent publication record in top-tier journals like Journal of Hospitality and Tourism Research and International Journal of Hospitality Management indicates significant scholarly impact. Dr. Noone's grant-funded research focuses on pricing strategy effectiveness, non-price information processing in consumer decisions, service encounter management frameworks, and revenue management decision tools. Her projects generate actionable insights for hospitality operators through empirical analysis of consumer responses to scarcity cues, photograph content, and cultural variables in booking behavior, directly informing industry revenue optimization practices.

Rianne Conijnمشاهده پروفایل

استادیار

• Learning Analytics
• Human-Technology Interaction
• Artificial Intelligence
• +۶ مورد دیگر

Rianne Conijn is an assistant professor in the Human-Technology Interaction group at Eindhoven University of Technology (TU/e), Netherlands. Her research bridges data-driven methodologies (machine learning, statistical modeling) with human-centered design to enhance learning analytics, explainable AI, and writing process analysis. She holds a joint PhD (cum laude) from Antwerp University and Tilburg University, and an MSc (cum laude) in Human-Technology Interaction from TU/e. Academic Background: MSc (2015, TU/e, cum laude), PhD (2020, Antwerp University & Tilburg University, cum laude). Research Focus: Learning analytics, keystroke logging, explainable AI for education, data dashboards, and self-regulated learning dynamics. Teaching: Courses in Advanced Research Methods, Human-AI Interaction, Behavioral Research Methods, and AI ethics in education. Her recent publications explore parallel language planning in writing, longitudinal self-regulated learning strategies, and generalizability of academic performance prediction models. She leads an NWO Veni project on Human-Centered AI in education, emphasizing tailored explanations for student-AI collaboration. Scientific awards include cum laude distinctions for her MSc and PhD, and the NWO Veni grant. Collaborative work spans institutions in the Netherlands, Norway, and the U.S., with applications in intelligent tutoring systems and ethical AI deployment in exams. Key trends across her work: integration of machine learning with educational theory, leveraging keystroke data for cognitive process insights, and prioritizing actionable, explainable AI systems for student support. Publications span journals like the Journal of Experimental Psychology: General , Computers and Education , and IEEE Transactions on Learning Technologies . Scientific Awards: NWO Veni grant for Human-Centered AI in education Cum laude for MSc and PhD Grants & Collaborations: National Science Foundation grants (2016868, 2302644) for biometric feedback in writing UK Research and Innovation grant (ES/W011832/1) for real-time AI scaffolding TU/e Boost! Program grant for self-regulated learning analysis Labs & Teams: EAISI Foundational (Eindhoven AI Systems Institute) Human Technology Interaction group at TU/e Collaboration with Norwegian Reading National Center (University of Stavanger) Project teams for Waterproof ITS and ProWrite grants

Rui Pradaمشاهده پروفایل

استاد

• Artificial Intelligence
• Game Development
• Affective Computing
• +۴ مورد دیگر

Rui Prada is a Full Professor at the Department of Computer Engineering, Instituto Superior Técnico, University of Lisbon. His research focuses on Artificial Intelligence , Game Development , and Human-Machine Interaction , with emphasis on socially intelligent agents and affective computing. His work explores Multi-Agent Systems , XR Testing , and Educational Game Design , particularly for neurodiverse populations. Recent publications highlight Procedural Content Generation , Human-AI Collaboration , and Social Power Dynamics in agent-based systems. Scientific contributions include the Best Poster Award and leadership in projects like PartiPlay and RAGE , advancing Inclusive AI and Game Technologies Marketplace frameworks.

Simeon Chavelمشاهده پروفایل

دانشیار

• Bible
• Hebrew Bible Studies
• History of Judaism
• +۸ مورد دیگر

Simeon Chavel is Associate Professor of Hebrew Bible at the University of Chicago Divinity School, with additional appointments as Associate Faculty in the Department of Near Eastern Languages and Civilizations and the Center for Middle Eastern Studies. His academic work bridges biblical studies, ancient Near Eastern history, and literary theory. His educational background includes: PhD from The Hebrew University of Jerusalem Professor Chavel's research focuses on the genres, techniques, ideas, and history of the Hebrew Bible, integrating archaeology, ancient Southwest Asian context, early Jewish interpretation, and modern theory. His work examines how text functioned as an agent of religious experience in ancient Israel and Judea, influencing concepts of family, region, royalty, and nationhood. He approaches biblical criticism through both historical and literary lenses, addressing fundamental questions about coherence in biblical texts. His scholarly output demonstrates consistent focus on biblical law, narrative structure, and the historical development of religious thought, with particular attention to how ancient readers interpreted biblical poetry and prophecy. His analytical approach often reveals complex layers of quotation and meaning in biblical texts. Professor Chavel serves on multiple academic boards including the Greenberg Center for Jewish Studies and the CEDAR digital humanities project. He is a member of the Core Faculty of The Institute on the Formation of Knowledge and Editor of Maarav: A Journal for the Study of the Northwest Semitic Languages and Literatures. Beyond his formal academic roles, Professor Chavel maintains an active scholarly presence through his 'Bible Sleuth' blog, where he provides accessible analyses of biblical texts, particularly examining poetic structures, narrative techniques, and interpretive challenges in books like Isaiah, Esther, and Proverbs.

Spencer Williamsمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Business Law
• Contract Law
• +۴ مورد دیگر

Spencer Williams is an Associate Professor of Law at California Western School of Law and Golden Gate University School of Law , where he researches and teaches at the intersection of business law and technological innovation . His work focuses on AI applications in legal practice , complex systems theory , and venture capital financing . He holds a JD from Stanford Law School and a BS in Economics from MIT . Prior to his academic career, Professor Williams practiced corporate and securities law at Wilson Sonsini Goodrich & Rosati and served as General Counsel for a Y Combinator-backed technology startup . Current Research Interests: AI-driven contract modeling Algorithmic price regulation Network theory in legal systems Smart contract frameworks Venture capital term optimization Legal informatics His recent publications analyze generative AI in contract design (2024), LLM benchmarking (2023), and edge computing contracts (2023). He contributes to the CodeX - Center for Legal Informatics and Stanford Legal Design Lab . Contact: swilliams@ggu.edu | Office: 415-442-6651

Liu Hongyanمشاهده پروفایل

استاد

• Big data management and analysis
• machine learning
• data mining
• +۷ مورد دیگر

Professor Liu Hongyan is a full-time Professor in the Department of Management Science and Engineering at Tsinghua University's School of Economics and Management, where he has served since 1994, achieving the rank of Professor in 2011 after previously holding positions as Associate Professor (2003-2011) and Teacher. His research bridges theoretical data science with practical applications across e-commerce, healthcare, and social media platforms. Education: PhD in Management, School of Economics and Management, Tsinghua University (2001) His research focuses on big data management , machine learning , and business intelligence with specialized expertise in personalized recommendation systems , medical/financial data analysis , and computer vision applications . Recent work integrates large language models and causal inference to solve complex problems in short video platforms, live streaming, and healthcare analytics, emphasizing real-world impact through industry collaborations. Analysis of his 15 most recent publications (2023-2025) reveals a strong trajectory toward multimodal AI systems combining recommendation engines with computer vision, particularly in 3D animation for advertising and healthcare. Key trends include LLM-enhanced display advertising, emotion-aware facial animation, and medical image annotation using adversarial learning, while maintaining core contributions to behavioral data mining in social networks. Scientific recognition includes: National Archives Administration's Outstanding Scientific and Technological Achievement Award Multiple Best Paper Awards at international conferences Outstanding Doctoral Dissertation Supervisor designation from the Society for Management Science and Engineering Special Award for National Natural Science Foundation project on user behavior pattern discovery Professor Liu has secured leadership roles in major National Natural Science Foundation projects including Innovation Research Groups and international cooperation initiatives. His industry impact is demonstrated through patented recommendation systems adopted by multiple companies, particularly in personalized content delivery for live streaming and short video platforms. As an Outstanding Doctoral Dissertation Supervisor, he mentors the next generation of data science researchers. He serves as Deputy Director of Tsinghua University's Center for Artificial Intelligence and Management Research and holds key positions in national academic societies including the E-Commerce and Cyberspace Management Committee (China Management Modernization Research Association) and the Information Systems Engineering Committee (Chinese Society for Systems Engineering).

Bradley Schmerlمشاهده پروفایل

پژوهشگر

• Software Engineering
• Software Architecture
• Self-Adaptive Systems
• +۵ مورد دیگر

Bradley Schmerl serves as a Principal Systems Scientist in the Software and Societal Systems Department (S3D) within Carnegie Mellon University's School of Computer Science. His research advances software engineering practices for modern challenges in distributed heterogeneous systems, self-adaptation, and cyber-physical integration. He leads the ABLE research group and actively mentors students in the Masters in Software Engineering program while teaching core courses like Software Architecture and Software Engineering Practicum. Dr. Schmerl's work addresses critical challenges in composing continuously evolving software systems, including components from untrusted third parties and on-the-fly recomposition for environmental changes. His research develops reusable, analyzable tools for software composition with emphasis on model-based adaptation, uncertainty management, and cross-language integration. Key projects include Rainbow for runtime architecture reflection, Acme for formal architectural foundations, and Cyber-physical Systems research linking software models with physical dynamics. Analysis of his 2023-2025 publications reveals intensifying focus on robotics software architecture (particularly ROS-based systems), explainable AI for architectural tradeoff analysis, and configuration management in adaptive systems. Trends show growing integration of machine learning for auto-tuning, empirical studies of misconfigurations, and dimensionality reduction techniques for visualizing design spaces—consistently bridging theoretical rigor with practical tool development for real-world applications. Scientific Awards: No specific awards were documented in the source materials. Dr. Schmerl serves as Practice Area Lead and mentor in CMU's Masters in Software Engineering program, guiding client projects including Rainbow UI for self-adaptive framework interfaces, CoBot UI for telepresence robots, and Educational Telepresence Tasking Language development. His research receives support through ABLE group projects funded by grants targeting software architecture foundations, adaptation mechanisms, and cyber-physical system validation. As a core member of the ABLE research group, he directs investigations into architecture-based self-adaptation with active projects spanning Rainbow (runtime architecture models for dynamic adaptation), Acme (formal architectural styles and tools), and Cyber-physical Systems (software-physical model integration). The group also maintains legacy work in End-User Architecting, Architecture Evolution, and service-oriented platforms for intelligence analysis through SORASCS.

• Business Administration
• Operations Research
• Supply Chain Management
• +۶ مورد دیگر

Prof. Dr. Julia Rieck is a Full Professor of Business Administration at the University of Hildesheim , leading the Department of Business Administration and Operations Research within the Faculty of Mathematics, Natural Sciences, Economics and Computer Science. As Dean of the Faculty , she oversees academic programs, quality management, and research initiatives. Her roles include academic advising for the Business Information Systems (B.Sc./M.Sc.) programs and active participation in examination boards and quality committees. Education: PhD in Political Science (Dr. rer. pol.) with summa cum laude (2008), Habilitation at Clausthal University of Technology (2014), and studies in Business Mathematics (Diploma, University of Hamburg, 2003) and Mathematics (Georg-August-University Göttingen, 2000). Research: Focuses on Operations Research , Supply Chain Management , Project Planning , and Logistics . Her work integrates mathematical modeling , machine learning , and real-world applications , particularly in disaster response , dynamic transportation , and sustainable e-commerce . Projects: Leads third-party funded initiatives like "IT für die sorgende Gesellschaft" (AI in healthcare/social sectors) and contributes to the HULLS real-lab (AI in aging societies). Collaborates with regional companies (e.g., Youco, ADITUS) and institutions (HAWK, University of Hannover). Teaching: Emphasizes practical application through case studies, industry partnerships, and the IT-Speed Dating event for student-company connections. Her courses cover project resource planning , logistics , and digital transformation . Labs & Teams: Active in the Institute of Business Administration & Business Information Systems , contributing to the KET Kompetenzwerkstatt (entrepreneurship support) and interdisciplinary teams in AI and sustainability research.

• Biosecurity
• Synthetic Biology
• Conservation Biology
• +۷ مورد دیگر

Stephen Turner is an Associate Professor of Data Science and Assistant Dean for Research at the University of Virginia School of Data Science . His work bridges genomics, data science, and national security , focusing on biosecurity, synthetic biology, conservation, and bioinformatics applications in human health . Previously, he was a faculty member in the UVA School of Medicine’s Department of Public Health Sciences (2011–2019) and directed the UVA Bioinformatics Core . Ph.D., Human Genetics, Vanderbilt University M.S., Applied Statistics, Vanderbilt University B.S., Biology, James Madison University Turner’s research spans computational approaches to biosecurity, biodiversity conservation, and human health . Recent publications highlight tools like the qqman and kgp R packages, PLANES for epidemiological modeling, and biorecap for bioRxiv preprint summarization. His work integrates large-scale sequencing, genome editing, and machine learning in conservation biotechnology and public health forecasting. Scientific contributions include applications in infectious disease forecasting , forensic genomics , and maternal-fetal biology . He has mentored interdisciplinary students and collaborated on NIH-funded research , while advising biotech startups at the intersection of academia, industry, government, and policy .