جست‌وجوی استاد و پژوهشگر

Frank van Harmelenمشاهده پروفایل

استاد

• Artificial Intelligence
• Semantic Web
• Knowledge Representation
• +۳ مورد دیگر

Prof. Frank van Harmelen is a Full Professor at Vrije Universiteit Amsterdam, holding positions in the Faculty of Science (Artificial Intelligence), Network Institute, and Knowledge Representation and Reasoning department. He also serves as an Adjunct Professor at Wuhan University of Science and Technology and Wuhan University Faculty of Information Sciences since 2014 and 2015, respectively. He earned his PhD in Artificial Intelligence from the University of Edinburgh (1985–1989), focusing on meta-level inference efficiency. His research spans Semantic Web, Knowledge Representation, Ontology Engineering, and neurosymbolic AI, with contributions to UN Sustainable Development Goals related to technological innovation. His recent work emphasizes knowledge graphs (e.g., KG4NH for nutrition/health, OfficeGraph for IoT), neurosymbolic integration, and applications in healthcare, sustainability, and education. He has led projects like the HumanE AI Network and contributed to datasets such as MetaLink and equivalence class analyses in LOD. Awards: Fellow of European AI Society (2007), Member of Royal Dutch Academy of Sciences (2017), Ten Year Impact Award (2012) Activities: Steering roles in international conferences, member of prestigious academies, and involvement in EU/US Agent Markup initiatives. Teaching: Courses on AI in Health and Introduction to AI. Grants/Projects: Principal Investigator for HumanE AI Network (2020–2024), contributed to IoT and smart grid solutions. His 292+ publications include foundational texts like the Semantic Web Primer and recent advancements in knowledge graph completion and guideline-informed reinforcement learning.

John Stouby Perssonمشاهده پروفایل

دانشیار

• Information Systems
• Agile Software Development
• Pragmatism
• +۷ مورد دیگر

John Stouby Persson is an Associate Professor in the Department of Computer Science at Aalborg University's Technical Faculty of IT and Design, specializing in Human-Centered Computing. His research focuses on practical problems experienced by software engineers, interaction designers, and IT professionals, with particular interest in agile development, user experience integration, and digitalization challenges. His research interests span information systems, agile software development, pragmatism, action research, digitalization, IT project management, and big data analytics. Persson approaches research as a collaborative practice of understanding and solving problems in organizing and leading system development, working with both public and private organizations. He has been particularly concerned with how information systems and digitalization are shaped by globalization, sustainability, value complexity and pragmatism. His recent publications show a strong trend toward the integration of AI tools in software development, UX practices, and addressing energy-related challenges through digital solutions. His work bridges practical software engineering concerns with theoretical frameworks, often using action research methodologies to develop solutions grounded in real-world contexts. Scientific Awards: Best paper award at the 12th Scandinavian Conference on Information Systems (SCIS 2021) Persson actively engages with both academic and public discourse, having participated in numerous conferences and provided expert commentary on digitalization initiatives including the Danish CoronaPass system. His consulting work demonstrates practical application of his research, particularly in realizing benefits from digitalization projects. His research aligns with UN Sustainable Development Goals, particularly those related to sustainable communities and responsible consumption.

• Machine Learning
• Data Analysis
• Predictive Modeling
• +۴ مورد دیگر

Rikard König is an Associate Professor at the University of Borås, Faculty of Librarianship, Information, Education and IT, Department of Information Technology. His research focuses on finding stories and connections hidden in large datasets, with specialization in machine learning, data analysis, and predictive modeling techniques. Dr. König's research interests include: Machine Learning and Predictive Analysis Genetic Programming and Rule Extraction Data Stream Mining and Real-time Analytics Sports Analytics, particularly Golf Swing Analysis Retail Analytics and Customer Understanding Model Interpretability and Constraint-based Learning His work demonstrates a consistent theme of developing machine learning tools that balance accuracy with interpretability while incorporating domain-specific constraints. His publications reveal a diverse application portfolio including golf swing analysis using radar data, fuel consumption modeling in trucks, and sales forecasting in the apparel industry. This cross-domain applicability highlights the generalizability of his research approaches. Dr. König has led and participated in several significant research projects including Big Data Analytics by Online Ensemble Learning (BOEL) and Golf data analysis (GOATS), funded by the Knowledge Foundation. His work often involves collaboration with industry partners, particularly in the automotive and sports technology sectors. His research methodology emphasizes creating models that adhere to domain expert constraints while maintaining predictive performance, as demonstrated in his 2015 paper on regression trees with variable restrictions that was validated in both golf instruction and truck fuel consumption contexts.

Filip Ilievskiمشاهده پروفایل

استادیار

• Commonsense Reasoning
• Neurosymbolic AI
• Analogy and Abstraction
• +۱۱ مورد دیگر

Filip Ilievski serves as an Assistant Professor of Commonsense AI (Sr.) at Vrije Universiteit Amsterdam, where he leads the Learning and Reasoning Group. He holds additional affiliations as an Affiliated Scientist at USC Information Sciences Institute and Amsterdam Sustainability Institute, and serves as Scientific Coordinator of the Digital Sustainability Institute (DiSC). His academic journey includes a PhD from Vrije Universiteit Amsterdam (2015-2019), research positions at USC (2019-2023), and a research visit to Carnegie Mellon University (2017). Dr. Ilievski's research focuses on advancing human-centric AI with common sense for social good applications. His work spans three interconnected areas: commonsense reasoning (including situational awareness, numeracy, and modeling of other agents), analogy and abstraction (studying cognitive generalization mechanisms through narratives and lateral thinking puzzles), and AI for social good (interpreting complex online media like internet memes and developing knowledge-based solutions for sustainable policies). He employs neuro-symbolic methods including prototype-based networks, combining LLMs with deterministic engines, and reasoning with scene knowledge graphs to create robust, interpretable AI systems. His publication record shows a strong trend toward multimodal reasoning and practical applications of commonsense AI, particularly in understanding internet memes, developing sustainable AI solutions, and creating robust evaluation frameworks like the MARVEL benchmark. Recent work increasingly integrates cognitive theories with neural architectures to address limitations in current foundation models, with particular emphasis on explainability and cultural context awareness. Best Student Paper Award at K-CAP for 'Knowledge-enhanced Agents for Interactive Text Games' Best Paper and Best Presentation Award at Workshop on Multimodal Content Analysis for Social Good (MM4SG) Book 'Human-Centric AI with Common Sense' published in Springer Nature Synthesis series Dr. Ilievski actively supervises a growing team of PhD students and postdocs, with current projects focusing on visual commonsense reasoning, meme semantics, analogical abstraction, multimodal alignment, and architectures for human-centric AI. His Digital Sustainability Institute (DiSC) coordinates research on knowledge-driven AI for sustainable policies, while his Situated AI minor program develops next-generation AI education. He maintains active collaborations with institutions including USC, CMU, RPI, University of Lyon, UvA, University of Bielefeld, and industry partners like Bosch Research, NEC Labs, Merit Technologies, and Tencent.

Alena Denisovaمشاهده پروفایل

مدرس ارشد

• Video Game Player Experience
• Human-Computer Interaction
• Game Design and Development
• +۳ مورد دیگر

Dr Alena Denisova is a Senior Lecturer in the Department of Computer Science at the University of York, specializing in player experience research in video games and interactive media. She holds a PhD in Computer Science from the University of York (2024–Present) and has held academic roles including Lecturer at the University of York (2022–2024) and City, University of London (2019–2021). Her research focuses on understanding player experiences, developing evaluation tools for interactive systems, and designing educational/persuasive media. She is a Fellow of the Higher Education Academy (FHEA) and holds a PG Cert in Higher Education from Swansea University. Education: BSc/MSc/PhD in Computer Science (University of York) Professional Qualifications: PG Cert in Higher Education, FHEA Roles: Outreach Academic Coordinator, Senior Lecturer Her research interests span game audio design, AI-driven gameplay mechanics, and the psychological impact of games. Recent work explores placebo effects in AI-powered dialogue systems, non-Euclidean game spaces, and emotional challenges in games for older adults. She has published widely on player experience measurement frameworks, adaptive game systems, and the convergence of HCI with game studies. Her 2024–2025 publications analyze topics like acoustic indicators in game commentary, moral decision-making mechanics in games, and democratisation of indie game development. She also contributes to editorial roles in HCI and game research venues. Scientific Awards: Fellow of the Higher Education Academy Grants/Advising: No specific grants listed, but active in educational outreach Denisova collaborates on projects involving procedural narrative generation and generative AI in arts, reflecting her interdisciplinary approach to interactive media research.

Zining Zhuمشاهده پروفایل

استادیار

• Natural Language Processing
• Explainable AI
• Model Interpretability
• +۳ مورد دیگر

Zining Zhu is an Assistant Professor at the Department of Computer Science at Stevens Institute of Technology, affiliated with the Stevens Institute for Artificial Intelligence (SIAI) and the Center for Research Toward Advancing Financial Technologies (CRAFT). He leads the Explainable and Controllable AI Lab, focusing on foundational and applied research in model interpretability, natural language explanations, and safe AI deployment. His work bridges theoretical advancements and practical applications in NLP and AI systems. Education: PhD in Computer Science (2024, University of Toronto), advised by Frank Rudzicz; BS in Engineering Science (2019, University of Toronto). Prior to Stevens, he was a research intern at Amazon, Tencent, and Winterlight Labs. Research Interests : Explainable AI and Model Interpretability Natural Language Processing and Large Language Models Societal Implications and Safe AI Deployments Knowledge Editing and Model Intervention Publications : Recent work emphasizes explainability in LLMs, dataset effects, and financial AI applications. Key papers include NAACL’s Outstanding Paper Award-winning ACCORD and tutorials on LLM explanations. Awards : Top Reviewer at NeurIPS (2023), Ontario Graduate Scholarship (2022-2023), and Vector Institute grants (2020-2023). Teaching : Instructors CS 584 (Natural Language Processing) and CS 810 (Explainable NLP). Extensive TA experience at University of Toronto. Labs : Leads the Explainable and Controllable AI Lab, fostering research into trustworthy AI systems.

Andrew Gilbertمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Generative Modelling
• +۶ مورد دیگر

Dr. Andrew Gilbert is an Associate Professor in Machine Learning at the University of Surrey, co-leading the Centre for Creative Arts and Technologies (C-CATS). His work bridges computer vision, generative AI, and creative industries, focusing on interpretable and human-centered systems. He leads a multidisciplinary team of 17 PhD students and has published over 100 papers in top venues like CVPR, ECCV, and BMVC. Education & Research: Gilbert earned his PhD in Computer Vision from the University of Surrey (2008) and has pioneered advancements in video understanding, style modeling, and AI-driven media production. His research integrates technical innovation with creative applications, such as AI-generated narratives and blockchain-based content rights. Research Trends: Recent work emphasizes long-term video analysis (DANTE-AD), motion-focused self-supervision (MOFO), and human-AI benchmarking (Human vs. Machine Minds). His projects often involve industry partnerships to address real-world challenges in media production and digital arts. Achievements: Best Paper at CVMP 2023, active BMVA committee member, and contributor to standards in explainable AI. His lab’s annual Gilbertine Weekend Away fosters collaborative research culture. Advising: Supervised 14 PhD completions, with ongoing projects in video diffusion models, decentralized content rights, and multimodal scene understanding. Seeks exceptional candidates for funded UK-based PhD opportunities. Key Labs: C-CATS lab explores AI’s creative applications, while his group develops tools for style transfer (NeAT), action recognition, and 3D performance capture.

Ashwin Ramمشاهده پروفایل

دانشیار مدعو

• Artificial Intelligence
• Cognitive Science
• Machine Learning
• +۳ مورد دیگر

Dr. Ashwin Ram serves as an Adjunct Associate Professor in Georgia Tech's School of Interactive Computing (College of Computing), an Associate Professor of Cognitive Science, and an Adjunct Professor in the School of Psychology. He directs the Cognitive Computing Lab and founded Enkia Corporation, a Georgia Tech AI spinoff specializing in commercial software. His educational background includes: B.Tech. in Electrical Engineering from Indian Institute of Technology, New Delhi (1982) M.S. in Computer Science from University of Illinois at Urbana-Champaign (1984) Ph.D. from Yale University (1989) for dissertation on "Question-Driven Understanding: An Integrated Theory of Story Understanding, Memory, and Learning" His research bridges artificial intelligence and cognitive science, emphasizing machine learning, natural language processing, case-based reasoning, and educational technology applications. With over 90 publications and two MIT Press co-edited books ("Goal-Driven Learning" and "Understanding Language Understanding"), his work focuses on practical AI implementation. Research funding has been secured from NSF, DARPA, ARDA, AFOSR, ARL, ONR, EduTech Institute, DEC, and Yamaha Motor Corporation. He actively participates in Georgia Tech's Intelligent Systems and AI groups, Graphics Visualization and Usability Center, Interactive AI Lab, and Mobile Robot Lab.

• Artificial Intelligence
• Computer Vision
• Human-Computer Interaction
• +۱۵ مورد دیگر

Dr. Stuart James is an Assistant Professor in Visual Computing at Durham University's Department of Computer Science, with a research focus on Visual Reasoning and Spatial Reasoning. His work bridges 2D/3D scene understanding with applications in Cultural Heritage, Digital Humanities, and Assistive Technologies. Key projects include EU-funded initiatives RePAIR (FET), DCitizens (Twinning), and BoSS (Lighthouse). Previous roles include Researcher/PostDoc positions at Istituto Italiano di Tecnologia (IIT) and University College London (UCL), where he earned his PhD in visual information retrieval for sketches from the University of Surrey. PhD in Visual Information Retrieval (University of Surrey, 2015) hBSc in Computer Science with Games Development (University of Hull, 2009) Research interests span Artificial Intelligence, Computer Vision, Human-Computer Interaction, and Robotics, with emphasis on Sketch-based Retrieval , Scene Graphs , Visual Question Answering , and Knowledge Retrieval & Reasoning . The VIViD research group at Durham drives innovations in neuro-symbolic reasoning for cultural analytics. Publications highlight trends in 3D scene understanding, cultural heritage digitization, and AI-driven storytelling frameworks. Scientific accolades include: CVPR 2025 Outstanding Reviewer ICIAP 2019 Best Student Paper IPAS 2018 Best Paper Current projects involve EU grants totaling €10.6 million across RePAIR, DCitizens, and BoSS. Collaborations include IIT (External Scientist), UCL (Honorary Associate), and ITI/LARSyS (International Collaborator). The lab recruits PhD students and organizes VISART workshops, while also advertising KTP Associate positions in Machine Learning for railway monitoring.

Andrew Burnstineمشاهده پروفایل

دانشیار

• Retail strategies
• Textiles
• Dress and culture
• +۷ مورد دیگر

Andrew Burnstine, Ph.D., serves as an Associate Professor of Marketing in the College of Business and Management at Lynn University. With nearly 30 years of experience teaching and chairing fashion marketing and design programs, he brings extensive industry knowledge to academia. Previously, he held leadership positions at Martha Inc. as Executive Vice President and taught at prestigious institutions including New York University, Kent State University, Berkeley College, and SUNY Purchase College. Burnstine's research interests span retail strategies, textiles, dress and culture, history of fashion, fashion marketing, and arts management. His work increasingly focuses on the intersection of artificial intelligence and retail, examining how emerging technologies are transforming the fashion industry. His educational background includes a Ph.D. from New York University, where his dissertation explored the 'History of Costume Design for the Big Apple Circus from 1985 to 1998,' reflecting his unique blend of academic rigor and practical industry experience. Burnstine has produced over 70 research outputs, including numerous academic articles and his popular 'Retail Matters' podcast series that examines compelling retail and fashion stories. His recent publications focus on AI applications in fashion, sustainable textile development, and the evolving luxury resale market. His work demonstrates a clear trajectory toward understanding how technology, sustainability, and changing consumer behaviors are reshaping the retail landscape. Awards and Professional Recognition Faculty Writing Fellow, Lynn University (2025-2026) Service and Dedication to Lynn University Award (2022-2023) President's Volunteer Service Award (2023) New York University Alumni Board of Directors (2007-present) Fashion Group International South Florida Chapter Board Member (2006-present) Berkeley College Teacher of the Year Award (1999) Burnstine actively engages with the community through initiatives like conducting mock interview workshops for high school students at Olympic Heights High School Academy of Finance. His distinctive background as a former professional circus clown with Ringling Bros. and Barnum & Bailey Circus, where he designed his own costumes, provides him with a unique perspective on fashion, performance, and consumer behavior that informs his academic work and teaching philosophy.

Amir Sadovnikمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Deep Learning
• +۱۱ مورد دیگر

Amir Sadovnik is an Assistant Professor in the Min H. Kao Department of Electrical Engineering and Computer Science at the University of Tennessee, Knoxville. He holds a PhD in Electrical and Computer Engineering from Cornell University and a BEng from The Cooper Union. Previously, he served as an Assistant Professor at Lafayette College, where he focused on undergraduate education and curriculum innovation. His educational background includes: PhD in Electrical and Computer Engineering, Cornell University, 2014 BEng in Electrical and Computer Engineering, The Cooper Union, 2009 Amir Sadovnik's research lies at the intersection of computer vision, machine learning, and human-computer interaction, with a strong focus on human-centered problems. His work explores how humans perceive and interact with visual content, leading to research in emotion recognition, face similarity, fashion compatibility, blur detection, and reinforcement learning. He leverages deep neural networks to tackle subjective tasks that are challenging for machines but intuitive for humans. His research also extends into bioinformatics, where he applies machine learning to genome analysis and sequence similarity. The 15 most recent publications reflect a consistent trend in using deep learning for perception-driven tasks. These include emotion prediction, face and object similarity, adversarial robustness, and biomedical data analysis. His work often integrates attention mechanisms, U-Net architectures, and reinforcement learning frameworks, demonstrating a multidisciplinary approach across computer vision, signal processing, and computational biology. While no formal scientific awards are listed in the provided texts, his involvement in grant-funded projects, such as the NSF-funded 'CS for Appalachia' initiative, highlights recognition of his educational and research contributions. Amir Sadovnik is actively engaged in teaching and mentoring. He has taught graduate and undergraduate courses including ECE 517 (Reinforcement Learning), ECE 574 (Computer Vision), and COSC 525 (Deep Learning). He has also led curriculum redesign efforts to make computer science more inclusive, particularly through integrating digital humanities into introductory programming courses. His educational grants and projects emphasize interdisciplinary learning and real-world data applications. He is involved in a research-practice partnership (NSF Grant No. 1923509) aimed at bringing computer science education to K–12 schools in East Tennessee. He leads research projects such as Easy Visual Question Answering with Video and Counting, and developed the educational tool Code-A-Story to integrate computer science with literacy for elementary students. These projects reflect his commitment to both cutting-edge research and accessible, impactful education.

Jason Boweyمشاهده پروفایل

مدرس

• Game Design
• Player Experience
• Digital Game Psychology
• +۳ مورد دیگر

Dr. Jason Bowey is a Lecturer in the Department of Computer Science at the University of Saskatchewan. He holds a PhD (2021) and BSc (2014) in Computer Science from the same institution. His research focuses on game design, player experience, and the psychological dimensions of digital games, including narrative design, social dynamics, and gender-related issues in gaming environments. Education: PhD in Computer Science, University of Saskatchewan (2021) BSc in Computer Science, University of Saskatchewan (2014) Research interests include understanding player-character belief congruence, the impact of dialogue choices in RPGs, and the effects of social exclusion on gameplay. His work also explores narrative prototyping, trust-building through social games, and the role of leaderboards in player motivation. Recent studies address topics like sexist beliefs in games and the application of spaced practice intervals in skill development. No scientific awards or grants are listed. His office is located at Thorvaldson 377.3, and he can be reached at jason.bowey@usask.ca .

Frank Guerinمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Robotics
• Computer Vision
• +۳ مورد دیگر

Frank Guerin is a Senior Lecturer at the University of Surrey, affiliated with the Computer Science Research Centre within the School of Computer Science and Electronic Engineering. His research focuses on Artificial Intelligence, integrating insights from cognitive psychology into robotics, computer vision, and natural language processing. He emphasizes the development of adaptable AI systems capable of handling everyday tasks akin to human cognitive flexibility. Education: BSc, MSc, PhD Research Interests: Robotics, AI ethics, metaphor interpretation in language models, and the societal impact of AI. Teaching: Courses include Computational Intelligence and Final Year Projects. His recent work addresses challenges in large language models, such as data contamination in evaluations and context compression for efficiency. He critiques grant-writing processes and advocates for more researcher-friendly funding mechanisms. Frank’s publications span AI applications, cognitive modeling, and ethical considerations. He actively blogs on topics like AI’s societal impact, grant-writing frustrations, and parallels between nuclear development and AI’s potential global influence.

Samuel Shenمشاهده پروفایل

عضو هیئت علمی

• Data Science
• Machine Learning
• Climate Science
• +۳ مورد دیگر

Dr. Samuel Shen is a Distinguished Professor at the Department of Mathematics and Statistics , San Diego State University (SDSU) and a Visiting Research Mathematician at Scripps Institution of Oceanography, UCSD. He co-founded the SDSU Big Data Analytics (BDA) MS Program and currently serves as Co-Director of the Center for Climate and Sustainability Studies . Previously, he was McCalla Professor at the University of Alberta and President of CAIMS . B.Sc. in Engineering Mechanics (1982) from East China Engineering Institute M.A. (1985) and Ph.D. (1987) in Applied Mathematics from University of Wisconsin-Madison His research spans three major areas: Climate Informatics : Developed Spectral Optimal Averaging (SOA) and Ensemble Canonical Correlation Analysis (ECCA) for climate uncertainty quantification Data Science : Created US Climate Prediction Center's operational prediction tools and filed a US patent on spectral optimal gridding Nonlinear Wave Dynamics : Advanced theoretical understanding of stochastic differential equations for climate modeling Recent publications focus on 4D climate visualization , heat stress mitigation , AI democratization in climate science , and cloud-aerosol interactions . His work has secured major grants including: $2.7M NSF AI Institute grant (2023) $1.9M California Climate Action grant (2023) $2.1M NSF EaSM-3 grant (2014) Scientific accolades include: Arthur Beaumont Distinguished Service Award (CAIMS) US National Research Council Senior Fellowship Chinese Academy of Sciences Well-known Overseas Scholar He leads the SDSU Climate Informatics Lab (founded 2006) and has been featured in New York Times , NASA Top Story , and Nature Geoscience press releases.

Tobias Höllererمشاهده پروفایل

استاد

• Visual Computing and Interaction
• Augmented Reality
• Virtual Reality
• +۵ مورد دیگر

Tobias Höllerer is a Professor of Computer Science at the University of California, Santa Barbara (UCSB). He leads the Imaging, Interaction, and Innovative Interfaces research group, focusing on novel user interfaces, augmented reality (AR), virtual reality (VR), and immersive visualization technologies. His work emphasizes 'Anywhere Augmentation' in AR and contributions to the Allosphere project, a three-story immersive visualization environment. Education: PhD in Computer Science, Columbia University MS in Computer Science, Columbia University Diplom (MSc equivalent), Technische Universität Berlin Research Interests: Höllerer explores AR/VR interfaces, spatial computing, human-computer interaction (HCI), and data visualization for analyzing large-scale information networks. His group develops solutions for 3D reconstruction, multimodal interaction, and applications in fields like digital fabrication, assistive technologies, and immersive storytelling. Publications Trends: Recent work spans AR navigation aids for visually impaired users, cognitive load analysis in VR, multimodal AI for spatial awareness, and creative applications like textile crafting and music instruments in AR. Scientific Awards: NSF Early Career Development Award Grants & Labs: Active in NSF-funded projects and directs the UCSB Allosphere Research Group. His lab collaborates on projects like Attention-Aware Mixed Reality Interfaces and Large-Scale Real-Time Information Visualization . Labs/Teams: Oversees the Allosphere, a unique immersive platform for data-driven exploration, and leads interdisciplinary teams advancing HCI and AR/VR technologies.