جست‌وجوی استاد و پژوهشگر

Mark Riedlمشاهده پروفایل

استاد

• Human-Centered Artificial Intelligence
• Story Understanding/Generation
• Computational Creativity
• +۴ مورد دیگر

Mark Riedl is a Professor in the Georgia Tech School of Interactive Computing and Associate Director of the Georgia Tech Machine Learning Center (ML@GT). His research focuses on human-centered artificial intelligence, emphasizing the development of AI technologies that naturally interact with humans. Key areas include story understanding/generation, computational creativity, explainable AI, and ensuring AI safety. He holds affiliations with the GVU Center, Institute for People and Technology (IPaT), and Institute for Robotics and Intelligent Machines (IRIM). His work is supported by NSF, DARPA, ONR, and industry partners like Google and Meta. Notable awards include the DARPA Young Faculty Award and NSF CAREER Award, plus three Pulitzer Prizes (collaborative with Roko M. Bask). Riedl's recent projects include STORY2GAME (AI-driven game design) and ethical AI frameworks addressing transparency and accountability. His research bridges theoretical advancements with practical applications in education, healthcare, and creative industries. Research interests span AI ethics, narrative systems, and AI's societal impact. He explores how AI can be made more transparent through explainable mechanisms while maintaining creativity and safety. Collaborations with Roko Bask on futuristic culinary trends have produced influential works. His labs and teams focus on interdisciplinary approaches, combining computer science with social sciences to shape responsible AI development. Key grants and projects include NSF-funded initiatives on AI in education and DARPA-supported work on AI safety. His contributions to explainable AI challenge traditional XAI paradigms, advocating for human-centered approaches that prioritize user understanding and ethical implications. Current efforts emphasize adapting LLMs for world modeling and enhancing RL agents with causal reasoning capabilities.

Andrew McCallumمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Natural Language Processing
• +۳ مورد دیگر

Andrew McCallum is a Distinguished Professor and Director of the Center for Data Science at the University of Massachusetts Amherst. He holds a PhD in Computer Science from the University of Rochester (1995) and a BS from Dartmouth College (1989). His research focuses on machine learning, natural language processing, and information extraction, with applications to scientific literature and knowledge base construction. He has pioneered work on conditional random fields and probabilistic databases, and led the development of systems like Rexa, an advanced research paper search engine. Affiliations: Center for Data Science, Center for Intelligent Information Retrieval, Computational Social Science Institute Key Projects: OpenReview.net, Unified Information Extraction, Automated Knowledge Base Construction His work emphasizes extracting actionable knowledge from unstructured text, with contributions to social network analysis, entity resolution, and semi-supervised learning. McCallum has over 300 publications and has received awards including the NSF ITR Grant, IBM Faculty Partnership Awards, and ACM/AAAI Fellowships. He has advised numerous students and served as ICML General Chair (2012). Recent Research Trends: Probabilistic box embeddings, case-based reasoning for knowledge bases, scalable clustering algorithms, and applications in biomedical informatics.

Chanchal K. Royمشاهده پروفایل

استاد

• Code Clone Detection and Analysis
• Software Evolution and Maintenance
• Software Analytics Research
• +۳ مورد دیگر

Chanchal K. Roy is Professor of Software Engineering/Computer Science at the University of Saskatchewan and Co-Director of the Software Research Lab. He leads an NSERC CREATE graduate program on Software Analytics Research and co-leads the Data Management group for an NSERC CFREF project on Food Security, with over 170 publications cited 6,000+ times. His research centers on software clone detection using the widely adopted NICAD system, software evolution, empirical studies, and AI-driven software analytics. Recent work integrates large language models for code generation, clone detection in the AI era, and developer interactions with tools like ChatGPT, emphasizing practical applications in maintenance and analytics. Analysis of his 15 most recent publications reveals a strong trend toward AI/ML integration in software engineering: 12 of 15 articles (2025) explore LLMs, quantum computing, or deep learning for tasks like bug localization, code snippet generation, and feature-toggle analysis. Key themes include empirical validation of AI tools, Stack Overflow data mining, and cross-domain frameworks for Society 5.0. His scientific awards include: Most Influential Paper Awards (SANER 2018, ICPC 2018) Outstanding Young Computer Science Researcher Award (CS-Can/Info-Can, 2018) New Researcher Award (University of Saskatchewan, 2019) New Scientist Research Award (College of Arts and Science, 2019) As lead of the NSERC CREATE program and CFREF data group, he mentors graduate students in software analytics while securing major grants. He actively serves on program committees for ASE, ICSE, and FSE, reviewing journals and organizing workshops on clone detection and empirical methods. His lab focuses on real-world applications in food security data management and software evolution. The Software Research Lab, co-directed by Roy, drives projects like NICAD and the NSERC CREATE initiative, emphasizing open-source contributions and industry collaboration. Current efforts include quantum-SE integration and AI-augmented maintenance tools under the CFREF food security mandate.

Jian Zhaoمشاهده پروفایل

دانشیار

• Information Visualization (InfoVis)
• Human-Computer Interaction (HCI)
• Data Science
• +۶ مورد دیگر

Jian Zhao is an Associate Professor at the University of Waterloo's School of Computer Science, specializing in Information Visualization (InfoVis), Human-Computer Interaction (HCI), and Data Science. With a Ph.D. from the University of Toronto (2016), his research emphasizes interactive visualization techniques, AI integration in design processes, and socio-technical systems. He explores how human-AI collaboration can enhance data analysis, presentation, and user experience in complex systems. Key research areas include: 1) AI-Driven Design (e.g., code generation via sketching, infographic creation), 2) Health Informatics (therapeutic AI tools for autism support), 3) Immersive Technologies (VR/AR interfaces for presentations and education), and 4) Social Computing (remote family communication, multi-modal emoticons). His work bridges technical innovation with human-centered design principles. His publications (2021–2025) reflect a focus on interactive visualization frameworks (e.g., iTrace for cross-view data analysis), AI-human collaboration (CoLadder for hierarchical code editing), and specialized applications like TherAIssist for art therapy and EMooly for autism support. Zhao frequently explores novel interaction modalities , including gesture-based VR interfaces and sketch-based programming tools. He leads projects in computational notebooks (EDAssistant, Slide4N), visual analytics (MissBin for bipartite networks), and neurofeedback training games (Eggly). His work often emphasizes systematic design considerations for missing data, cross-view analysis, and contextual visualization in spatial AR environments.

Gavin Schwarzمشاهده پروفایل

استاد

• Organizational Change
• Organizational Failure and Inertia
• Virtual Teams
• +۲ مورد دیگر

Gavin Schwarz is a Professor and Head of School at the School of Management and Governance within the UNSW Business School . He specializes in organizational change , organizational failure and inertia , and the dynamics of virtual teams , with a focus on how organizations fail during change processes and how to develop applied strategies for change management . His work spans diverse sectors including healthcare, technology, and education, with publications in leading journals such as Academy of Management Learning and Education and Administrative Science Quarterly . Education : PhD in Management (University of Queensland), MPhil (Hons) in Management (University of Auckland), BA in Management and English (University of Auckland). Grants : 2020 Brock University grant for "University communication in times of COVID-19" , 2020 UNSW Medicine grant for "Translation and change: Embedding effective change management in health" , and earlier Australian Research Council and Gordon J. Samuels Fellowship awards. His research explores the development of knowledge in organizational theories , with an emphasis on collective responses to change , HR management during crises , and technology strategy . He has contributed to understanding organizational communication , team innovation , and structural inertia . His 15 most recent publications cover topics from AI’s role in organizational change to pandemic-driven research adaptation, with keywords spanning management science , behavioral economics , and digital transformation . Scientific Awards 2021-2023 : Outstanding Reviewer Awards (Academy of Management Review) 2017-2020 : Best Reviewer Awards (Journal of Organizational Behavior) 2019, 2013, 2011 : Best Paper Finalist/Awardee (Academy of Management divisions) 2007, 2006 : Editorial Board Excellence (Academy of Management Journal) and Gordon J. Samuels Fellowship As an active supervisor in organizational change and HR development , his work supports healthcare innovation and digital transformation. He serves as Editor-in-Chief for the Journal of Applied Behavioral Science and is on the editorial boards of Academy of Management Review , Journal of Management , and Journal of Organizational Behavior . Contact: g.schwarz@unsw.edu.au

Snigdha Chaturvediمشاهده پروفایل

دانشیار

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۸ مورد دیگر

Snigdha Chaturvedi is an Associate Professor in the Department of Computer Science at the University of North Carolina at Chapel Hill. She previously held faculty positions at the University of California, Santa Cruz, and has conducted postdoctoral research at the University of Pennsylvania and University of Illinois, Urbana-Champaign. PhD in Computer Science from University of Maryland, College Park Bachelor's degree in Computer Science and Engineering from Indian Institute of Technology (IIT) Kanpur Her research spans Natural Language Processing with emphasis on Narrative Understanding , Text Summarization , and Socially Aware Language Generation . She advances Fairness in AI through ethical NLP applications in Mental Health and Educational Technology . Recent work focuses on 2025 publications in ACL and NAACL journals, alongside 2024 contributions to EMNLP Findings and ICLR . Earlier projects include the NarraSum dataset (2022) and MOOC forum analysis (2020). Scientific recognitions include: ACM Student Research Competition First Place (2014) IBM PhD Fellowship (2014-2015, renewed in 2015) Kulkarni Summer Research Fellowship (2015) WPI STEM Faculty Launch Program Participant (2015) Her team has advised 13 PhD and Master's students with notable placements at Bloomberg, AI2, and University of Southern California. Research integrates Accessibility challenges through collaborations with Google and IBM labs.

Stephen Lee-Urbanمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Game AI
• +۳ مورد دیگر

Stephen Lee-Urban is a Teaching Associate Professor in the Department of Computer Science & Engineering at Lehigh University, affiliated with the Rossin College of Engineering. He holds a Ph.D., M.S., and B.S. in Computer Science and Engineering from Lehigh University, all completed with summa cum laude distinction. His research focuses on fundamental and applied artificial intelligence, machine learning, game AI, cognitive systems, and automated planning. He has contributed to innovative projects such as HuManIC (human-machine interpretive control), CORA (cognitive systems framework), and crowdsourced narrative generation systems. His academic career includes significant work in cybersecurity through intelligent agent modeling of malware, as well as contributions to game AI for strategy games and military training simulations. Notable awards include summa cum laude honors for all three of his university degrees. Lee-Urban's scholarly output spans over 20 publications since 2000, with recent emphasis on AI applications in collaborative storytelling, adaptive planning systems, and human-computer interaction. His research integrates machine learning techniques with sociocultural analysis, crowd-powered content creation, and hierarchical task networks. Current work explores autonomous systems capable of leveraging crowd intelligence for generating interactive narratives and optimizing military training scenarios. While no specific grants or advising roles are listed, his interdisciplinary approach bridges computer science with game design, cybersecurity, and cognitive modeling.

Zheng Zhangمشاهده پروفایل

پژوهشگر

• Human-AI Interaction
• Human-Computer Interaction
• Machine Learning
• +۳ مورد دیگر

Zheng Zhang is a Ph.D. candidate in the Department of Computer Science and Engineering at the University of Notre Dame, where he focuses on human-AI interaction. He also works as an Applied Scientist in Adobe's GenAI team, developing interactive AI systems for user experience enhancement. He has held internships at Apple, AWS AI, and Meta Reality Labs. Education: Ph.D. (in progress) at University of Notre Dame M.S. in Computer Science from University of Rochester and University of Minnesota B.Eng. in Software Engineering from Shaanxi Normal University His research explores the intersection of human-computer interaction (HCI) and machine learning (ML), emphasizing systems that provide adaptive, context-sensitive support for complex cognitive tasks. Key areas include collaborative tools for team ideation, incremental learning from user demonstrations, and multimodal context-aware interfaces. Recent publications demonstrate a focus on AI-augmented collaboration through large shared displays (LADICA), audio-visual annotation (PEANUT), and interactive qualitative coding (PaTAT). His work increasingly integrates generative AI with real-time human input, particularly for co-located teams and educational applications. He serves as a Program Committee member and reviewer for top HCI/ML conferences including CHI, UIST, IUI, and ACL. Teaching experience spans courses in human-AI systems, algorithms, and data structures.

Robert Godwin-Jonesمشاهده پروفایل

استاد

• Computer-Assisted Language Learning
• Second Language Acquisition
• Artificial Intelligence in Language Education
• +۳ مورد دیگر

Robert Godwin-Jones is a Professor in the Department of Foreign Language at Virginia Commonwealth University's College of Humanities and Sciences, where he has served since 1979. He holds the position of Foreign Language Liaison and maintains active scholarly contributions through his "German Stories" digital repository and "Communicating Across Cultures" blog, focusing on technology-enhanced language pedagogy and intercultural communication. His educational background includes: B.A. in French and German from Franklin and Marshall College (1971) M.A. in Comparative Literature (German, French, and English) (1973) Ph.D. in Comparative Literature from the University of Illinois Urbana-Champaign (1977) Dr. Godwin-Jones specializes in Computer-Assisted Language Learning (CALL), with research spanning artificial intelligence applications, virtual reality environments, and digital literacies for language learners. His work examines how emerging technologies transform second language acquisition through ecological semiotics, distributed agency models, and multimodal communication frameworks. He investigates pedagogical translanguaging strategies for less commonly taught languages and analyzes authenticity in AI-mediated language interactions, particularly in pragmatics and writing development. Analysis of his 2021-2025 publications reveals three dominant trajectories: (1) generative AI integration in language instruction with emphasis on ethical implementation and threat mitigation; (2) extended reality applications creating immersive language spaces in the metaverse; and (3) ecological approaches connecting smart devices, ambient intelligence, and situated learning contexts. His scholarship consistently bridges theoretical frameworks with practical classroom applications across 19th-century German literature studies and contemporary language education. He maintains active professional engagement through memberships in: Delta Phi Alpha German Honorary Society Phi Kappa Phi Honorary Society Modern Language Association American Association of Teachers of German American Association of Teachers of French Foreign Language Association of Virginia As director of the "German Stories" project since 1994, he has curated verified editions of 19th-century German narratives with English translations under Creative Commons licensing, creating what has become a foundational resource for literary study and language acquisition. His blog extends this work through contemporary analyses of intercultural communication challenges, while his scholarly leadership in organizations like CALICO shapes national discourse on technology in language education. His laboratory functions as the "German Stories" digital ecosystem, which has evolved into a comprehensive platform hosting annotated texts, pedagogical resources, and research archives. This environment supports both formal classroom instruction and informal learning communities, demonstrating his commitment to porous classroom models that integrate physical and digital learning spaces.

• Traditional Chinese Medicine (TCM)
• Data Mining
• Medical Informatics
• +۴ مورد دیگر

Associate Professor Josiah Poon is affiliated with the School of Computer Science at the University of Sydney. His research focuses on applying data mining and IT techniques to Traditional Chinese Medicine (TCM), particularly analyzing herbal combinations for effective treatments. He collaborates with institutions in China to improve TCM evidence and has contributed to clinical data analysis, medical informatics, and multimodal AI systems. Teaching includes courses such as INFO1003 (Foundations of IT) and INFO9003 (IT for Health Professionals). Current research students are Rina CABRAL (Multimodality Representation), Yan LI (Long Document Comprehension), and Xiaobin LU (Financial Decisions). Research highlights include developing algorithms to quantify TCM efficacy, analyzing complementarity in herbal combinations, and applying machine learning to healthcare data. Notable projects include a randomized controlled trial on pneumococcal vaccination (2021) and a Google-funded multimodal health detection system (2020). Key areas of expertise span TCM informatics, medical data analytics, and AI-driven healthcare solutions. His work bridges Eastern/Western medicine through computational methods, emphasizing evidence-based practices in TCM.

• Consumer Behavior
• Digital Marketing
• Information Systems
• +۷ مورد دیگر

Dr. Sahar Karimi is a Senior Lecturer in Marketing with expertise in consumer behavior on digital platforms. She holds a PhD from Alliance Manchester Business School (University of Manchester), an MSc in Advanced Computer Science with ICT Management, and a BEng in Computer Engineering. Her research bridges consumer research and behavioral Information Systems, focusing on how digital platforms and smart technologies influence decision-making processes. She teaches Market Research (MKIB256) and supervises PhD/DBA projects on AI in marketing, virtual reality impacts, and digital transformation. Her recent publications explore topics like self-quantification effects, virtual influencers, chatbot emotionality, and VR-enabled manufacturing efficiency. She emphasizes interdisciplinary approaches to understand consumer interactions with emerging technologies. While no scientific awards are explicitly listed, her work demonstrates significant contributions to digital marketing and behavioral research.

Andrew S. Gordonمشاهده پروفایل

عضو هیئت علمی

• Interactive Narrative
• Commonsense Reasoning
• Computational Models of Narrative
• +۶ مورد دیگر

Andrew S. Gordon is a Research Associate Professor of Computer Science at the University of Southern California and Director of Interactive Narrative Research at the Institute for Creative Technologies. His work integrates artificial intelligence, cognitive science, and interactive storytelling to create systems that automatically interpret and generate narrative structures, with a special focus on commonsense reasoning and abductive inference. Education Ph.D. in Computer Science, Northwestern University, 1999 Research Interests Gordon’s research converges on computational narrative intelligence . He develops formal models of commonsense psychology that enable machines to reason about human intentions, beliefs, and emotions. His group designs interactive narrative systems for training and education, builds large-scale story corpora, and pioneers abductive reasoning techniques that combine symbolic logic and statistical learning to interpret temporal data. Recent work explores how large language models can be guided to co-create interactive fiction and how vision–language models can be benchmarked for causal understanding. Publication Trends Across more than two decades, his publications reveal consistent themes: (1) foundational theories of commonsense psychology and strategy representation, (2) narrative technologies that blend AI planning with human creativity, and (3) practical training simulations for defense and education. The 2024-2025 papers highlight a pivot toward evaluating and steering large language models for narrative tasks, while earlier work established abductive reasoning frameworks such as “Etcetera Abduction.” Awards & Honors Best Paper Award, System Lifecycle and Technologies Track, Simulation Interoperability Standards Organization (SIW 2021) Advising & Grants He has successfully mentored three PhD students—Reid Swanson (2010), Christopher Wienberg (2017), and Melissa Roemmele (2018)—whose dissertations span computational narrative, commonsense reasoning, and interactive fiction. His research has been continuously supported by agencies including the U.S. Army, DARPA, and NSF for projects on virtual training environments, narrative-centered learning, and large-scale commonsense knowledge acquisition. Labs & Teams Gordon directs the Interactive Narrative Research Group at USC’s Institute for Creative Technologies, where interdisciplinary teams of computer scientists, cognitive psychologists, and interactive media designers collaborate on systems such as the Rapid Integration & Development Environment (RIDE) for embodied conversational agents and story-driven training simulations.

Mark Johnsonمشاهده پروفایل

استاد

• Natural Language Processing
• Computational Linguistics
• Machine Learning
• +۵ مورد دیگر

Mark Johnson is a Professor at Macquarie University's School of Computing, affiliated with the Centre for Language Sciences (CLaS). His research focuses on computational linguistics, natural language processing, and machine learning, with contributions to parsing algorithms, child language acquisition models, and generative AI systems. He leads projects on generative models of life stories, logistics optimization algorithms, and visual dialogue systems using deep neural networks. Research interests include natural language understanding, data augmentation techniques, and model robustness. Notable projects involve developing frameworks for synthetic training data, OOD detection, and integrating named entity recognition with context tags. His work emphasizes practical applications in dialog systems, document analysis, and language model optimization. Collaborations span cross-linguistic studies and AI-driven visualization systems. Key achievements include over 200 research outputs, including influential articles on child language acquisition models and OOD detection. He oversees projects funded by MQRC and industry partnerships, focusing on advancing NLP and AI methodologies. His lab, CLaS, fosters interdisciplinary research in language sciences and computational methods.

• Journalism studies
• Media policy
• Public interest journalism
• +۷ مورد دیگر

Professor Monica Attard OAM is Co-Director of the Centre for Media Transition at the University of Technology Sydney (UTS), Faculty of Arts and Social Sciences, where she also served as Head of Journalism. With a career spanning over 35 years in journalism, she has transitioned into academia, focusing on media policy, public interest journalism, and the impact of digital technologies on news media. She is actively engaged in research, leadership, and policy consultation. Her educational background includes a Bachelor of Arts from the University of Sydney and a Bachelor of Laws from the University of New South Wales. Monica Attard’s research interests center on journalism sustainability, media regulation, disinformation, generative AI in newsrooms, and regional news media. Her work investigates how journalism adapts to digital platforms, regulatory frameworks, and technological disruption. She explores models for sustaining public interest journalism and the implications of AI on news production and credibility. Her recent publications reflect a strong focus on media policy, particularly Australia’s News Media Bargaining Code, generative AI, and regional journalism. The articles show a consistent trajectory toward understanding how journalism can survive and thrive in the digital age, with attention to equity, transparency, and public accountability. Gold Walkley Award for Excellence in Journalism (1991) Walkley Award for Best International Report (all Media) (1991) Walkley Award for Best Coverage of a Current Story (Radio) (1991) Walkley Award for Broadcast Interviewing (2002) Walkley Award for Broadcast Interviewing (2005) Medal of the Order of Australia (OAM) (1992) for services to journalism She supervises research students and leads multiple funded research projects, including investigations into generative AI and public interest journalism, regional media sustainability, and disinformation. She is a member of the Board of Media Diversity Australia and the Advisory Board of the Affinity Intercultural Foundation, contributing to media equity and inclusion. Her work often involves collaboration with government bodies and digital platforms. She co-leads the Centre for Media Transition, a cross-disciplinary research hub exploring journalism best practice, regulatory adaptation, and trustworthy digital society. The center conducts policy submissions, produces reports, and engages with national and international stakeholders on media transformation.

Jessica Vandenbergمشاهده پروفایل

پژوهشگر

• Computer Science Education
• Artificial Intelligence Education
• Computational Thinking
• +۳ مورد دیگر

Jessica Vandenberg serves as a Research Scientist in the Center for Educational Informatics within the Department of Computer Science at North Carolina State University, focusing on K-8 computer science and AI education. Her work bridges educational theory with practical classroom applications through digital learning environments and assessment tools. Her educational background includes: Ph.D. in Teacher Education and Learning Sciences (Educational Psychology concentration), North Carolina State University (2021) M.A.T. in Elementary Education, Montclair State University (2005) B.A. in History, Pennsylvania State University (2000) Vandenberg's research centers on integrating computer science and computational thinking into upper elementary classrooms, with specialized expertise in AI education for young learners and survey instrument development. Her methodology emphasizes authentic learning experiences through game design, pair programming, and virtual learning companions, particularly addressing challenges in rural educational settings. She investigates how children develop AI literacy and measures attitudes toward computer science through validated instruments. Her publication trends reveal consistent focus on elementary AI education (47% of recent work), rural community applications (33%), and collaborative learning analytics (20%), with growing emphasis on gender/race intersectionality in CS attitudes. Methodologically, she combines epistemic network analysis with mixed-methods assessment to study student collaboration and learning trajectories. Key recognition includes: Computing Innovations Fellow (2021 cohort) She leads NSF-funded research totaling $1.28M, including the 2023-2027 project Transforming Introductory Computer Science Instruction with an AI-Driven Classroom Assistant , which develops the INSIGHT platform for real-time student progress monitoring. Previously, she served as lead education graduate student on an NSF project creating virtual learning companions to enhance elementary programming skills. Her work consistently partners with the William & Ida Friday Institute for Educational Innovation. Vandenberg directs research within NC State's Center for Educational Informatics, where her team develops digital learning environments using scaffolded CSCL frameworks. Current projects focus on AI-infused game design for rural middle schools and story-centric unplugged activities for AI concept introduction, emphasizing accessibility and cultural relevance in underserved communities.