جست‌وجوی استاد و پژوهشگر

• 3D Object Retrieval
• Biometrics
• Shape Analysis
• +۵ مورد دیگر

Theoharis Theoharis is a Professor at the Department of Computer Science (IDI), Norwegian University of Science and Technology (NTNU Trondheim), where he leads research in shape analysis and visual computing. He is a core member of the Visual Computing Lab , focusing on 3D object retrieval, biometrics, and cultural heritage applications. Research Interests : 3D Object Retrieval and Registration Biometric Identification (facial data, somatotype analysis) Shape Segmentation and Cultural Heritage Preservation Medical Imaging and Robotics Notable Projects : PRESIOUS : EU-funded initiative for cultural heritage using visual computing D4FLY : On-the-move biometric verification CHANGE ITN : Monitoring cultural heritage change with 15 PhD theses Publications highlight trends in: 3D shape descriptors (QUICCI, radial intersection count) Deep learning for 3D reconstruction and registration Applications in cultural heritage, medical imaging, and geophysics Education : BSc in Computer Science MSc in Computation DPhil in Computer Graphics and Parallel Processing Advising includes doctoral students like Evdokia Saiti (2023) and Peder Bergebakken Sundt (2024), with contributions to SHREC'16 and 3DOR2022 symposiums. Labs & Collaborations : Visual Computing Lab (NTNU) NTNU's Computing unit European Union FP7-ICT (D3.1 Deliverable)

• Instructional Design
• Eye Tracking
• Educational Research
• +۵ مورد دیگر

Dr. Margot van Wermeskerken serves as an Assistant Professor in the Department of Education at Utrecht University's Faculty of Social and Behavioural Sciences. Her research focuses on multimedia learning, particularly learning from video examples, instructional design, and educational technology. She employs eye-tracking methodology to investigate attentional processes during learning and explores cognitive load and self-regulated learning. Her research interests span several interconnected domains of educational psychology. She investigates how visual information processing affects learning, with particular focus on instructional design principles that optimize educational outcomes. Her work on eye-tracking methodology has revealed important insights about attention allocation during learning processes. She also researches how visualizations of learners' attention can be used to enable adaptive instruction and feedback, bridging the gap between cognitive theory and practical educational applications. The analysis of Margot van Wermeskerken's recent publications shows a consistent focus on cognitive aspects of learning with multimedia. Her research trajectory demonstrates progression from foundational work on visual perception in infants to applied educational research on instructional design. A notable pattern in her work is the integration of eye-tracking technology with educational interventions, creating a strong connection between cognitive theory and practical applications in educational settings. Her research spans from basic cognitive processes to applied educational interventions, demonstrating both theoretical depth and practical relevance. Fellowship from the Community for Learning and Innovation of Erasmus University Rotterdam (2019) Coordinator of the special interest group Technology-Enhanced Learning and Instruction of the European Association for Learning and Instruction (EARLI SIG 7) (2017-2021) Dr. van Wermeskerken has been actively involved in educational research and practice throughout her career. From 2019-2022, she worked as an educational researcher and consultant at Erasmus Medical Center within the Digital Learning and Innovation team, focusing on educational renewal and innovation of courses and programs. She has secured research funding including a fellowship from the Community for Learning and Innovation. Her teaching responsibilities include courses such as Instructional Design & Evaluation, Research Plan & Master Thesis, and Introduction to Educational Neurosciences within the Master's programs in Educational Sciences and Educational Sciences: Learning in Interaction. Her current research project 'Oooo(g) ja: De rol van gedeelde aandacht bij het afstemmen van leren en lesgeven in docent-leerling interactie' investigates whether establishing joint attention between student and teacher during real-time dyadic interaction enhances instructional alignment and student learning.

Tomek Strzalkowskiمشاهده پروفایل

استاد

• Computational Linguistics
• Socio-behavioral Computing
• Artificial Intelligence
• +۷ مورد دیگر

Professor Tomek Strzalkowski, currently at Rensselaer Polytechnic Institute's Tetherless World Constellation, is a leading researcher in human language technology. He holds a joint appointment in Cognitive and Computer Science and has previously served as Professor at SUNY Albany, Director of its Institute for Informatics, Logics and Security Studies, and as a Principal Scientist at GE Research and NYU Courant Institute. Current research focuses on socio-behavioral computing, social media analytics, and AI defenses against disinformation through projects like GATOR (dialogue systems), PANACEA (anti-social-engineering agents), and COMETH (computational ethnography). His 150+ publications span computational linguistics, interactive information retrieval, and formal semantics, with recent works addressing multimodal AI, agenda detection, and pandemic behavioral modeling. He has secured funding from DARPA, IARPA, NSF, European Commission, and industry partners, and serves on the editorial board of Natural Language Engineering .

Alexander Hauptmannمشاهده پروفایل

استاد پژوهشی

• Multimedia Analysis
• Machine Learning
• Natural Language Processing
• +۳ مورد دیگر

Alexander Hauptmann is a Research Professor at Carnegie Mellon University's Language Technologies Institute (LTI) within the School of Computer Science. His work focuses on integrating multimedia analysis, machine learning, and natural language processing to develop systems for large-scale video and multimedia content analysis. Known for pioneering technologies in video search, automatic annotation, and multimedia event detection Collaborates with students and researchers globally, including as a Visiting Professor at Japan's National Institute of Informatics Research emphasizes utilizing large corpora of found data to enhance speech recognition, image understanding, and information retrieval His multidisciplinary background combines computer science (Ph.D. from CMU, M.S. from Technische Universität Berlin) with psychology, enabling innovative approaches to AI challenges at the intersection of language, vision, and human interaction. Dr. Hauptmann's lab has contributed to significant analyses, including the Astroworld Festival tragedy investigation, and develops tools like the Event Reconstruction System and Cognitive Assistance for Medical Device Use. He maintains a strong focus on creating intelligent systems that bridge human understanding and computational processing in multimedia contexts.

Tomasz Maruszewskiمشاهده پروفایل

استاد

• Cognitive Psychology
• Emotion Regulation
• Autobiographical Memory
• +۵ مورد دیگر

Prof. Dr. Hab. Tomasz Maruszewski is a faculty member at the Faculty of Psychology in Sopot , affiliated with SWPS University . His primary role is in the Department of Basic Psychology , where he teaches courses in cognitive processes and social communication. His research focuses on: Cognitive Psychology (working memory, autobiographical memory) Emotion Regulation (expressive suppression, interoception) Gerontology (reminiscence materials for elderly) Personality Dynamics (biological, cognitive, and social perspectives) Key article trends include autobiographical memory mechanisms (2005-2015), emotion regulation costs (2015), and gerontological applications (2017). He has contributed to understanding how emotional suppression affects cognitive performance through tense arousal mediation. He previously served as deputy director of the Institute of Psychology of the Polish Academy of Sciences and leads the MEMO Project developing multimedia tools to support memory in older adults.

• Machine Learning
• Recommender Systems
• Natural Language Processing
• +۱۰ مورد دیگر

Julian McAuley is a Professor in the Department of Computer Science at the University of California, San Diego (UCSD). His research bridges machine learning, natural language processing, and computer music, with a focus on generative models, recommender systems, and multimodal learning. He leads a lab that has produced influential datasets and frameworks for recommendation tasks. Primary Affiliation: UCSD, Department of Computer Science Research Themes: Generative AI, Recommender Systems, Music-Cognition Interfaces, Multimodal Learning McAuley's work explores the intersection of large language models (LLMs) with sequential recommendation, causal inference, and creative applications in music generation. His lab develops novel architectures like CoMMIT (multimodal instruction tuning) and SAND (LLM agent deliberation), while also advancing ethical AI through normative alignment techniques. Recent publications highlight trends in code-augmented reasoning , symbolic music processing , and contextual preference optimization . Notable applications include video-guided music synthesis, Explainable Chain-of-Thought systems, and tools for scalable self-updating models. He advises PhD students in areas spanning large language models , vision-language systems , and healthcare-driven AI . Collaborations span institutions like MIT-IBM Watson AI Lab, CMU, and companies including Google Deepmind, Meta, and Nvidia.

Ravi Kiran Sarvadevabhatlaمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Human-Computer Interaction
• +۹ مورد دیگر

Ravi Kiran Sarvadevabhatla is an Associate Professor at the International Institute of Information Technology Hyderabad (IIIT-H), with additional roles as Lead (Applied Projects and Academic Programs) at iHub-Data Mobility. His research spans Computer Vision , Machine Learning , and Human-Robot Interaction , focusing on interdisciplinary challenges involving multimodal data (images, sketches, eye-tracking, audio). Research Themes : Computer vision projects in Document Image Understanding , Sketch Recognition , and Depiction-Invariant Object Recognition Cognitive modeling through Eye Tracking Analysis and Pictionary-inspired Models Human-robot interaction studies on Proxemics , Panoramic Attention , and Extended Interaction Analysis Technical Contributions : Pioneered Category-Epitome representations for sparse sketch recognition Developed SketchParse - a deep network for automated sketch parsing Created PPSS-12 benchmark for evaluating object recognition robustness

Moumoutzis Nektariosمشاهده پروفایل

مدرس

• Digital Storytelling
• E-Learning
• Technology-Enhanced Learning
• +۵ مورد دیگر

Moumoutzis Nektarios is a Lecturer at the School of Electronic & Computer Engineering at the Technical University of Crete , affiliated with the Distributed Information Systems and Applications Laboratory (TUC/MUSIC) . His work bridges the gap between technology, education, and the arts. Email: nmoumoutzis@tuc.gr Office: 141B-65, Science Building/IMMY (L), 1st Floor Phone: 282103 7395 His research focuses on technology-enhanced learning , digital storytelling , and serious games , with a strong emphasis on interdisciplinary approaches that combine design thinking , digital technologies , and arts to create innovative educational experiences. His projects often target diverse audiences, including K-12 students , young children , and children with ADHD . In recent years, his work has explored block-based programming tools , gamification of learning , and collaborative learning environments . Notable contributions include the development of eShadow+ for mixed-reality storytelling, Block-C for teaching C programming, and ViSTPro for spatiotemporal process visualization in education. He has also contributed to frameworks for digital competency , interoperability of e-learning systems , and personalized learning experiences . His work aligns with the European and National Curricula and emphasizes project-based learning and community-driven education .

• Multimedia Information Retrieval
• Recommender Systems
• Information Retrieval
• +۷ مورد دیگر

Professor Martha Larson is a faculty member at Radboud University, holding positions in the Department of Language and Communication and the Centre for Language Studies. She chairs the Multimedia Information Technology research group and collaborates with the Mohrmann Fonds. Her work focuses on intelligent access to multimedia content through search engines, recommendation systems, and speech recognition technologies. Research Interests: Recommender systems, information retrieval, multimedia analysis, language and speech technology, social network multimedia anonymization, and human computation. Teaching: Supervises courses including Text and Multimedia Mining, Bachelor Thesis, and Master Thesis programs across Computing Science, Information Sciences, and Communication disciplines. Contact: Email m.larson@cs.ru.nl or call +31 24-3652033.

Nuria Oliverمشاهده پروفایل

پژوهشگر

• Computational Models of Human Behavior
• Human-Computer Interaction
• Intelligent User Interfaces
• +۱۲ مورد دیگر

Nuria Oliver, PhD is a pioneering computer scientist and ACM Fellow , recognized as the first female Spanish computer scientist to achieve both ACM Distinguished Scientist and IEEE Fellow status. Current affiliations include Microsoft Research and former roles at MIT Media Lab. First female Spanish ACM Fellow IEEE Fellow Academia Europaea member Her research spans human behavior modeling , intelligent user interfaces , and mobile computing , with notable work in: Wearable context-aware systems (DyPERS, HealthGear) Music-adaptive exercise platforms (MPTrain, TripleBeat) Social network analysis (information propagation, community link modeling) Computer vision interfaces (LAFTER facial expression recognition) Scientific achievements include: 41 patents 15+ years of continuous multimodal systems research Recognized for LAFTER system (2000 paper) She actively promotes technology accessibility through: Media collaborations Technical/non-technical keynotes STEM outreach for girls

Gang Qianمشاهده پروفایل

استاد

• Multi-dimensional indexing techniques and access methods
• Database techniques for Bioinformatics
• Multimedia databases
• +۴ مورد دیگر

Gang Qian is a Professor in the Department of Computer Science at the University of Central Oklahoma. He obtained his Ph.D. in Computer Science from Michigan State University in 2004. Education Ph.D. in Computer Science from Michigan State University (2004) Research Interests Multi-dimensional indexing techniques and access methods Database techniques for Bioinformatics Multimedia databases Information retrieval for text and document databases Organizing and querying information on the Web Machine learning and data mining Computer science education Teaching Current courses include Application of Database Management Systems, Programming Languages, and Theory of Computing. Previous courses taught: Computer Technologies for Communication in a Global Society, Introduction to Computing Systems, Beginning Programming, Programming I, Object Oriented Programming, and Data Structure. Office hours: TR 3:00-4:15 p.m. Contact Information Email: gqian@uco.edu Additional Resources Links to Curriculum Vitae, Research Statement, and Teaching Statement are available on his personal website.

Vladimir Mladenovićمشاهده پروفایل

استاد

• Symbolic computation and processing
• Artificial intelligence and machine learning
• Deep learning and neural networks
• +۷ مورد دیگر

Prof. Dr. Vladimir Mladenović is a Full Professor at the Department of Information Technologies , Faculty of Technical Sciences in Čačak , University of Kragujevac , Serbia. A 1975 native of Paraćin, he earned his Dipl. Ing. from the Faculty of Electronic Engineering, University of Niš (2000), followed by an M.Sc. (2005) and Ph.D. in Technical Sciences (2009) from the University of Kragujevac. His career spans industry (IT Manager, Serbian Glass Factory, 2001–2004), secondary education (teacher, 2004–2009), and academia (Professor of Vocational Studies, 2009–2013) before joining the University of Kragujevac. Research Focus: Symbolic software & tools, higher integration in IT systems Signal & multimedia processing, computer vision & AI/ML 5G/IoT architectures, edge computing, data protection Modern communication systems, web & network technologies He directs the Digital Innovation Lab at his faculty and has authored over 100 peer-reviewed publications in leading journals and conferences, with a strong emphasis on cross-layer modeling, deep learning, and IoT applications. He also co-holds 18 Serbian utility patents covering smart IoT systems ranging from greenhouse monitoring to smartwatch data collection, fire detection, and pedestrian safety. Honors & Professional Standing: Licensed Technology-Transfer Engineer – WIPO & Intellectual Property Office of Serbia (2012) Member, Union of Engineers and Technicians of Serbia Teaching Portfolio: Undergraduate: Modern Software Architectures, Multimedia Systems, Data Protection Master: Modern Communication Systems, Web Programming Doctoral: Modern Network Technologies, Applied Computer Vision

• Physics Education
• Quantum Physics
• Nuclear Physics
• +۳ مورد دیگر

Zdeňka Koupilová is a Lecturer at the Department of Physics Didactics , Faculty of Mathematics and Physics , Charles University in Prague. She teaches courses in Quantum Mechanics, Thermodynamics, Theoretical Mechanics, and Physics Education. Nuclear and Subnuclear Physics Quantum Physics Education Science Communication Experiential Learning Educational Technology Her research focuses on innovative physics teaching methods, particularly quantum and nuclear physics education. She has developed interactive tools like the Orbitals project for atomic visualization and electronic problem collections . Her work includes collaborations with ČEZ, a.s. on educational brochures like Jaderné hrátky and Učíme jadernou fyziku . Publications highlight her contributions to physics education and detector simulations for the ATLAS experiment at CERN. Though no scientific awards are listed, her efforts in educational outreach and conference participation (e.g., GIREP 2006, Veletrh nápadů) underscore her impact.

Martin Krulišمشاهده پروفایل

دانشیار

• High-performance computing
• GPU programming and CUDA optimization
• Parallel algorithms and data structures
• +۴ مورد دیگر

Martin Kruliš is an associate professor in the Department of Distributed and Dependable Systems at the Faculty of Mathematics and Physics, Charles University , Prague, Czech Republic. His primary roles include research, teaching, advising, and leading projects that bridge high-performance computing, GPU programming, and self-adaptive systems. Education: While exact details of his own degrees are not provided, Dr. Kruliš’s extensive publication record and faculty position at Charles University indicate advanced training in computer science with specialization in parallel and distributed computing. Research Interests: High-Performance GPU Computing: Deep investigation into CUDA kernel optimization, memory bandwidth utilization, and workload dispatching for massively parallel accelerators. Self-Adaptive & Self-Optimizing Systems: Designing ensemble-based abstractions that integrate machine-learning estimators to enable runtime adaptation in component architectures. Parallel Algorithms & Data Structures: Development of cache-friendly, SIMD-aware, and GPU-accelerated algorithms for clustering, dimensionality reduction, and similarity search. Software Engineering for Parallelism: Creation of C++ libraries, DSLs (e.g., Bobolang), and educational tools (ReCodEx) that simplify parallel programming and automated evaluation. Publication Trends: Across 2011–2025, Kruliš’s articles reveal a clear trajectory from foundational GPU-accelerated indexing and multimedia retrieval toward sophisticated self-adaptive systems that leverage machine learning. Recent works (2023–2025) increasingly focus on integrating LLMs and neural networks into compiler and runtime optimization loops, reflecting a convergence of AI and systems research. Scientific Awards & Recognition: No specific awards or fellowships are mentioned in the provided text; however, sustained publication in top-tier venues (JPDC, IPDPS, Euro-Par, SEAMS) and active involvement in program committees and tool development indicate strong peer recognition. Teaching & Student Supervision: Teaches Programming in Parallel Environment (NPRG042) , Advanced Programming in Parallel Environment (NPRG058) , Computer Systems (NSWI170) , and Software Projects . Supervises numerous bachelor’s and master’s theses; exact student names are not listed in the text. Labs, Projects & Tools: ReCodEx: A widely used platform for semi-automated evaluation of programming assignments at Charles University. Simdex: A modular simulator of the ReCodEx backend that enables realistic experimentation with self-adaptive job dispatching and machine-learning controllers. Active contributor to open-source repositories on GitHub, focusing on GPU kernels, benchmarking frameworks, and educational tooling.

Arnaud Revelمشاهده پروفایل

استاد

• Machine Learning
• Human-Computer Interaction
• Robotics
• +۶ مورد دیگر

Arnaud Revel is a Professor at the University of La Rochelle, holding the position of Deputy Director of the Science and Technology Department since April 2015 and Deputy Director of the S2IM doctoral school (Sciences and Engineering for Information, Mathematics) since June 2012. His academic career spans multiple institutions including ENSEA, where he was initially recruited in 1998, and the University of La Rochelle where he was promoted to professor in 2009. He has served in various administrative roles including co-directing the IMAGIN team at L3I laboratory and as deputy director of the L3I laboratory for AERES evaluation. Revel's research interests focus on three interconnected themes: Learning (structuring complex information and data mining), Human/Machine Interaction (modeling interaction dynamics in robotics and multi-agent systems), and Art and Science (notably the LINK Human/Robot project collaborating with the Cambrai School of Art). His work bridges theoretical computer science with practical applications in robotics, digital art, and interactive systems. Recent publications demonstrate his continued focus on mobile agent security, human-robot interaction, and content-based image retrieval, with notable collaborations across disciplines and international borders. His work on the LINK Human/Robot project, despite not receiving ANR funding, has been presented at prestigious venues including Le Fresnoy (2012), Bains numériques (2012), Futur en Seine (2013), VIA (2014), University of La Rochelle (2014), and Le Cube (2015), culminating in a collaborative art and science book published by Van Dieren in 2015. Professor Revel has supervised multiple doctoral students including K.Prepin (co-supervision, 2008), M.Rojas-Castro (co-supervision since 2012), and H.Idrissi (co-supervision since 2013 in a cotutelle with Morocco). His teaching activities span various institutions including the University of La Rochelle where he teaches Logic Programming, Smartphone programming, and Video Game Programming at the undergraduate level, and Data Mining and Python Programming at the Master's level.