جست‌وجوی استاد و پژوهشگر

Xavier Ochoaمشاهده پروفایل

استادیار

• Learning Analytics
• Multimodal Learning Analytics
• Artificial Intelligence in Education
• +۳ مورد دیگر

Xavier Ochoa is an Assistant Professor of Learning Analytics and Doctoral Program Coordinator at the Steinhardt School of Culture, Education, and Human Development, New York University. He holds a Ph.D. in Engineering (Computer Sciences) from the University of Leuven, Belgium (2008), an M.Sc. in Applied Computer Sciences from Vrije Universiteit Brussels (2002), and a B.S. in Computer Science from ESPOL, Ecuador (2000). His research focuses on Multimodal Learning Analytics, blending AI, sensors, and educational practices to enhance learning environments. He leads the Augment-Ed research group and has held roles such as Vice-President of SoLAR and Editor-in-Chief of the Journal of Learning Analytics. His academic career includes over a decade at ESPOL, where he directed the Information Technology Center and TEA research group. Awards include Best Researcher (2012, 2018), Best Professor (2013), and IEEE’s Best Researcher in Computer Science (2014). His work emphasizes tools for self-reflection, decision-making, and 21st-century skill development in education. Education: Ph.D. (2008, KU Leuven), M.Sc. (2002, VUB), B.S. (2000, ESPOL) Labs/Teams: Augment-Ed Research Group, Former Lead of TEA Group Key Contributions: RAP system for oral presentation feedback, OpenOPAF open-source tool, CrossMMLA initiatives Xavier’s research bridges education and technology, with publications in journals like the Journal of Learning Analytics and conferences such as LAK. His work addresses challenges in collaborative learning, feedback systems, and scalability of learning analytics tools.

• Human-Computer Interaction
• Extended Reality
• Virtual Reality
• +۹ مورد دیگر

Dr. Stephen Uzor is a Senior Lecturer in the School of Computing and Engineering at the University of West London. His academic work bridges computer science, engineering, and environmental applications, with a strong focus on interactive technologies and remote sensing. His research interests include: Human-Computer Interaction (HCI) Extended Reality (Virtual and Augmented Reality) Game Design Artificial Intelligence Digital Health Robotics Remote Sensing and Environmental Monitoring Dr. Uzor's recent publications demonstrate a consistent trend in applying emerging technologies such as smartphone LiDAR, Ground-Penetrating Radar, and augmented/virtual reality for environmental and civil infrastructure monitoring. His work often involves low-cost, accessible solutions for visualizing and analyzing tree health, urban green infrastructure, and historical or transportation structures, frequently in collaboration with researchers in geoscience and civil engineering. He teaches on the BSc (Hons) Computer Games Technology program, aligning with his expertise in multimedia and interactive systems. Contact: Email: stephen.uzor@uwl.ac.uk

Markus H. Flierlمشاهده پروفایل

دانشیار

• Visual Computing and Communication
• Machine Learning
• Information Theory
• +۳ مورد دیگر

Markus H. Flierl is an Associate Professor at the School of Electrical Engineering and Computer Science, KTH Royal Institute of Technology in Stockholm. He holds a PhD in Engineering from Friedrich Alexander University (2003). His career includes senior research roles at École Polytechnique Fédérale de Lausanne (2003-2005), leadership of the Max Planck Center for Visual Computing and Communication (2005-2008), and a Visiting Assistant Professorship at Stanford University (2000-2002). He has served as Program Director of the EIT Digital Master School’s 'Visual Computing and Communication' program and as Associate Editor for the IEEE Transactions on Circuits and Systems for Video Technology. Education: PhD in Engineering, Friedrich Alexander University, 2003 Studies at Friedrich Alexander University (1999-2002), EPF Lausanne (2003-2005), and Stanford University (2005-2008) Research Interests: Focused on visual computing, machine learning, and information theory. Key areas include distributed coding of dynamic scenes, multiview video coding, motion-compensated transforms, and applications in video compression and multimedia systems. His work explores efficient signal processing techniques for video and 3D visual search, with recent contributions in drone-based environmental monitoring and adversarial training methods. Awards: SPIE VCIP Young Investigator Award (2007) Teaching & Grants: Teaches courses on image/video processing, information theory, and multimedia systems. His research is supported by Ericsson, the Swedish Research Council, the European Commission, and KTH’s Digitalization Platform. He advises PhD and master’s students in visual computing and communication. Labs & Teams: Leads the Visual Computing and Communication research group at KTH, collaborating with industry partners like Ericsson and Qamcom. Former members include researchers now at Tobii AB and the University of Iceland.

Veijo Vaakanainenمشاهده پروفایل

مدرس

• Second language acquisition
• Third language acquisition
• Swedish as a Second Language
• +۶ مورد دیگر

Veijo Vaakanainen is a University Lecturer of Swedish at the Centre for Language and Communication Studies, University of Turku (since 2023). His roles include teaching Swedish for medical and economics students, designing language courses, and integrating AI into pedagogy. He previously held part-time teaching positions at the University of Turku’s Department of Scandinavian Languages and German, as well as Åbo Akademi University’s Swedish Department (2016–2023). His expertise spans second/third language acquisition, cross-linguistic influence, and digital tools in education. Education: PhD in Scandinavian Languages from the University of Turku (2016–2025), funded by Svenska kulturfonden and Svenska litteratursällskapet i Finland. Earlier roles include secondary school teaching (2018–2019) and research on formulaic sequences in learner languages (2017). Research focuses on connectors in L2 Swedish writing, leveraging Systemic Functional Linguistics and keystroke logging. He explores multilingualism, AI applications in language learning, and effective digital pedagogy. Recent work includes analyzing connector usage dynamics in Swedish and German learner texts, and developing interactive learning materials using QR codes and gamification. Teaching innovations include AI-integrated language courses and collaborative digital projects. He emphasizes student-centered approaches, evidence-based methods, and ethical sustainability in education. No scientific awards are explicitly listed, but his work has been supported by prestigious Finnish cultural and literary foundations.

Djamal Zeghlacheمشاهده پروفایل

استاد

• Network Virtualization
• Cloud Computing
• Software-Defined Networking
• +۵ مورد دیگر

Djamal Zeghlache is a Professor at Telecom SudParis (now part of Institut Polytechnique de Paris), where he leads research in network virtualization, cloud computing, and software-defined networking. His work spans multiple domains including wireless communications, network security, and AI applications in networking systems. Affiliated with the SAMOVAR laboratory (Services and Architectures for Multimedia and Ubiquitous Access to Resources), he has established himself as a prominent researcher in network and service management. Professor Zeghlache's research interests focus on the intersection of networking and artificial intelligence, with particular emphasis on network virtualization, cloud computing, and software-defined networking. His work addresses critical challenges in network function virtualization, resource allocation, and optimization in distributed systems. In recent years, he has expanded his research to include AI-driven approaches for network management, healthcare monitoring using wireless technologies, and optical network control. His publications demonstrate a consistent trajectory from traditional networking challenges to more complex, AI-integrated solutions for modern network infrastructures. Analysis of his recent publications (2023-2025) reveals a strong trend toward integrating machine learning, particularly deep reinforcement learning and graph neural networks, into network management systems. His work spans multiple application areas including healthcare monitoring (using RF-based techniques for vital sign detection), transportation systems (bike-sharing optimization), and optical networking (disaggregated control frameworks). The interdisciplinary nature of his research connects computer networking with biomedical engineering, urban mobility, and formal methods for system verification. Professor Zeghlache has supervised numerous PhD students and collaborated extensively with researchers across Europe and internationally. His work has resulted in significant contributions to network virtualization, cloud resource management, and network security. He has been involved in multiple research projects focusing on next-generation networking technologies, including 5G, network slicing, and cloud-native network functions.

Pedro M. Cruzمشاهده پروفایل

دانشیار

• Data Visualization
• Information Design
• Bio-inspired Approaches
• +۴ مورد دیگر

Pedro M. Cruz is an Associate Professor in the Art + Design Department at Northeastern University, where he co-directs the Co-Lab for Data Impact and serves as a core faculty member of the Center for Design. His work bridges information design, data visualization, and computational art, featuring nature-inspired metaphors to convey complex data through visual narratives. Education includes a PhD in Information Science and Technology from the University of Coimbra (Portugal), with visiting research at MIT’s Senseable City Lab and the Singapore-MIT Alliance for Research and Technology. His research focuses on bio-inspired visualization, generative design, and the intersection of art and science. Awards include the 2018 Gold Award at the Information is Beautiful Awards, the 2017 CAMD Excellence in Teaching Award, and recognition as one of the top 10 global information designers (2013). His work has been showcased at MoMA, the London Design Biennale, and featured in WIRED, National Geographic, and Fast Company. Key projects include 'Visualizing Empires Decline' (2009), an animated visualization of maritime empire dissolution, and collaborations on exhibits at the Museum of Science and the Museum of Fine Arts in Boston. His teaching spans courses like Information Design Studio and Visualization Technologies.

• Resilience in 5G
• Distributed Artificial Intelligence (Edge AI)
• Information assessment
• +۳ مورد دیگر

Tobias Meuser is a Researcher at the Multimedia Communications Lab of Technische Universität Darmstadt, leading the "Adaptive Communication Systems" group since 2020. He holds a PhD (2019) focused on vehicular network data management and has been a central figure in the third phase of the Collaborative Research Center (CRC) MAKI as a principal investigator in subproject B1. His work emphasizes resilient 5G networks, edge AI, and distributed systems. Education: B.Sc. Business Informatics (Fernuniversität Hagen) M.Sc. Informatics (TU Darmstadt) Research Interests: Resilience in 5G and beyond Edge AI and distributed machine learning Information assessment in vehicular networks Collaborative perception systems Hardware acceleration for network functions Key Projects: Principal Investigator in CRC MAKI's B1 (Monitoring and Analysis) Collaborations with Opel (cooperative maneuvering) and Deutsche Bahn (5G resilience) Labs/Teams: Head of Adaptive Communication Systems group at Multimedia Communications Lab Member of Distributed Sensing Systems group (2016–2020)

Pasquale Lisenaمشاهده پروفایل

پژوهشگر ارشد

• Knowledge Graphs
• Knowledge Engineering
• Recommender Systems
• +۳ مورد دیگر

Pasquale Lisena is a Research Fellow in the Data Science department at EURECOM, where he contributes to the Data2Knowledge research group. His work bridges academic research with practical applications in knowledge-intensive domains. Education: PhD in Computer Science from EURECOM / Sorbonne University (2019), thesis: "Knowledge-based music recommendation: Models, algorithms and exploratory search" supervised by Raphaël Troncy His research centers on Knowledge Graphs, Knowledge Engineering, and Recommender Systems with strong applications in cultural heritage and music. Key specializations include: Semantic Web technologies for domain-specific knowledge representation Information extraction from multimedia and text sources Development of ontologies for complex cultural domains Music metadata modeling and recommendation systems Recent publications reveal a trajectory from foundational music metadata work (2018-2019) toward cutting-edge applications in olfactory heritage (Odeuropa) and language model-driven recommendation (2025). His research consistently integrates knowledge graphs with machine learning, demonstrating expertise in both classical music informatics and emerging sensory heritage domains. Awards: Best Resource Paper Award (2022) for Odeuropa Data Model publication Funding and Collaboration: ANR JCJC project coordinator for kFLOW (2022-2024) Key contributor to EU H2020 projects including Odeuropa, SILKNOW, and MeMAD Extensive cross-institutional collaboration across European cultural heritage initiatives He operates within EURECOM's Data2Knowledge group, participating in international research consortia focused on knowledge-intensive applications in cultural heritage preservation and digital humanities.

• Artificial Intelligence
• Curriculum and Pedagogy
• Control Engineering
• +۶ مورد دیگر

Dr. Anthony Bartel is an Adjunct Industry Fellow at the School of Social Sciences, Media, Film and Education, Swinburne University of Technology. He teaches Physics, Electronic Instrumentation, and Multimedia Technology to undergraduate and postgraduate students across science, engineering, games, and multimedia disciplines. He has coordinated multiple subjects and courses in these areas. His educational background includes an undergraduate major in Physics, a Master's involving instrumentation for balloon-borne x-ray astronomy, and a PhD in neutron physics instrumentation development. Undergraduate: Physics Master's: Instrumentation for Balloon-Borne Astronomical X-Ray Observatory PhD: Instrument Development for Neutron Physics Experiments Dr. Bartel's research spans Artificial Intelligence, Curriculum and Pedagogy, Control Engineering, Mechatronics, Robotics, and Music Education Technology. His work emphasizes the use of AI and serious games to enhance deliberate music practice and self-regulated learning. He explores feedback models, incentive systems, and progression design in mobile music games to improve educational outcomes. His recent publications (2010–2021) demonstrate a strong trend toward integrating AI with music education, particularly in generating adaptive sight-reading exercises and analyzing percussive sounds. The research bridges computer science, education, and acoustics, focusing on intelligent tools for music practice and systematic sound description. He is available to supervise PhD students and has previously supervised doctoral research in intelligent music tools and percussive audio lexicons. Intelligent Tools for Deliberate Music Practice: Evolving Targeted Sight Reading Exercises (2015–2019) The Percussive Audio Lexicon (2014–2015) Dr. Bartel has not received any publicly listed scientific awards. His teaching and research are supported through institutional roles and collaborative projects in educational technology and instrumentation. He is involved in interdisciplinary teams working on serious games for music education and AI-driven learning systems, contributing expertise in instrumentation, signal processing, and pedagogical design.

Paul Richardsonمشاهده پروفایل

استاد

• Automotive Engineering
• Computing and Networks
• Robotics

Paul Richardson is a Professor in the Department of Electrical and Computer Engineering at the University of Michigan-Dearborn’s College of Engineering and Computer Science. His research spans automotive systems, real-time networks, and robotics. PhD in Systems Engineering, Oakland University His work focuses on Automotive Engineering , Computing and Networks , and Robotics . Key contributions include innovations in intra-vehicle networks, UWB channel modeling, and real-time control systems. Recent publications highlight advancements in OFDM signal processing, PAPR reduction techniques, and adaptive scheduling for QoS in vehicular and mobile networks. Collaborations include researchers like W. Xiang and A. Elkateeb. He is affiliated with the Institute for Advanced Vehicle Systems at UM-Dearborn. Contact: richarpc@umich.edu .

• Instructional Design
• Educational Technology
• Multimedia Learning
• +۳ مورد دیگر

Mário Melo is a Visiting Assistant Professor at ISCTE - Instituto Universitário de Lisboa, affiliated with the Department of Social and Business Sciences. He is also an Associate Researcher at ISTAR-Iscte (Research Center in Information Sciences, Technologies and Architecture). His research focuses on instructional design models for digital education, particularly the 4C/ID model and its application to teaching physics. He investigates how multimedia learning theories and cognitive load theory influence the effectiveness of digital educational resources, emphasizing knowledge transferability and acquisition in physics education. Mário's recent publications analyze the 4C/ID model's impact on learning outcomes, with studies on electrical circuits, secondary education, and meta-analytic reviews. His work spans journals like Learning Environments Research and International Journal of Instruction . Scientific Awards Education Institute/Caixa Geral de Depósitos Award (2019) He teaches courses such as Multimedia Communication and Learning and Curriculum Development across Bachelor's and Postgraduate programs in Digital Educational Technologies. His work bridges educational sciences with information systems, focusing on technology-driven pedagogy.

Alan J. Smithمشاهده پروفایل

استاد

• Computer Architecture
• Computer Engineering
• Operating Systems
• +۴ مورد دیگر

Alan J. Smith is a Professor in the Electrical Engineering and Computer Sciences department at the University of California, Berkeley, within the College of Engineering. With a distinguished career spanning several decades, he has made significant contributions to computer architecture, system performance analysis, and memory systems. Dr. Smith received his S. B. from MIT and a Ph.D. from Stanford University. His educational background provided the foundation for his extensive research in computer systems. Professor Smith's research focuses on computer architecture and engineering, particularly in system performance analysis, I/O systems, cache memories, and memory systems. His work has profoundly influenced how computer systems are designed and evaluated, with particular emphasis on optimizing storage systems, cache performance, and energy efficiency in computing platforms. His research has bridged theoretical analysis with practical implementation, resulting in numerous influential publications and real-world applications. His publication record shows a consistent focus on computer system performance, evolving from early work on cache memory and paging algorithms to more recent research on multimedia workloads, energy management, and storage systems. The breadth of his work spans fundamental computer architecture principles to applied system design, with particular emphasis on measurement-based analysis and optimization techniques. Harry Goode Award of the IEEE Computer Society (2006) IEEE Reynold B. Johnson Information Storage Systems Award (2008) A. A. Michelson Award of the Computer Measurement Group (2003) Fellow of the American Association for the Advancement of Science (2001) Fellow of the ACM (2000) Fellow of the IEEE (1988) Throughout his career, Professor Smith has actively contributed to the academic community through editorial roles, conference organization, and professional society leadership. He has served as Subject Area Editor for the Journal of Parallel and Distributed Computing since 1989, chaired ACM SIGARCH and SIGOPS, and participated in numerous technical committees. His research has been supported by various grants that enabled extensive experimental work and system development. Professor Smith has been instrumental in developing benchmarking methodologies and performance analysis techniques that have become standard practices in computer system evaluation. His work on cache memory systems, in particular his influential 1982 Computing Surveys paper "Cache Memories," has shaped the field for decades.

• Multilingualism and the Arts
• Sámi Literature
• Comparative Literary Studies
• +۱۱ مورد دیگر

Dr. Johanna Domokos is an Associate Professor at the Department of Theatre Studies, Faculty of Humanities and Social Sciences, Károli Gáspár University of the Reformed Church in Hungary. With a distinguished academic career spanning several institutions including University of Bielefeld and UCLA, she has established herself as a leading scholar in multilingualism, Sámi literature, and Finno-Ugric studies. Her educational background includes a PhD in Comparative Literary Studies (1999) from József Attila University with a dissertation on Translation-semiotic analysis of Lapp poetry , multiple MA degrees in Finno-Ugric Studies, Hungarian Language and Literature, and English Language and Literature (1994, 2000), and the prestigious Dr. Habil degree from Eötvös Loránd University (2011). Domokos's research focuses on multilingualism in the arts , particularly examining literature, theatre, and visual arts in Northern and Central Europe, with special emphasis on Finland, Estonia, Sámi/Lapland, and the Carpathian Basin. Her work explores artistic rituality, mystical poetry, and interlingual and intersemiotic translation. She has led numerous research projects including the 'International Mediation of Sámi Literature' (2016-2019) and 'Rituality, Theater, Literature' (2018-2020). Her recent scholarly output reveals a strong trend toward Anthropocene studies and code-switching research , with publications examining multilingual creativity, Sámi literature, and the intersection of theatre with ecological concerns. Her work demonstrates growing interdisciplinary connections between literary studies, environmental humanities, and performance theory. Scientific Awards: Faludy-Díj (1992) Karriert Támogató Díj and Kutatói Díj from UCLA (2005, 2007) Kulturális Szervezői Kitüntetés from Los Angeles Hungarian Embassy (2008) Inger Sjöberg Prize from Scandinavian Society, USA (2022) Dr. Habil degree from Eötvös Loránd University (2011) Domokos has supervised doctoral students including Molnár Attila (on multimedia in contemporary art), Miklós Krisztina (on multilingualism and corporeality in Tompa Andrea and Sofi Oksanen's novels), and Bilibok Apollónia (on streamed theatre performances during the pandemic). She has served on numerous doctoral committees, most recently examining Balázs Renáta's work on contemporary Hungarian and Finnish national literary history constructions (2025). Her research has been supported by prestigious Humboldt Scholarships at Bielefeld University (2010-2011, 2018). She leads the Translation Workshop at Károli Gáspár University and has been instrumental in establishing the university's translation laboratory. Her international research group 'Kódváltás a kortárs művészetben' (Code-Switching in Contemporary Art) continues to produce significant scholarly work bridging linguistic and artistic disciplines.

• Biometrics
• Behavioral Biometrics
• Mobile Authentication
• +۱۲ مورد دیگر

Ruben Tolosana is a researcher at the Biometrics and Data Pattern Analytics Lab (BiDA Lab) in the School of Engineering at Universidad Autónoma de Madrid. His work centers on biometrics, with emphasis on behavioral and mobile authentication, face recognition, privacy-enhancing technologies, and deep learning applications in human-computer interaction. He actively contributes to major research initiatives such as the FRCSyn-onGoing challenge and the ChildCI framework. PhD in Computer Science or related field (inferred from publication volume and role) Advanced training in machine learning, computer vision, and biometrics His research interests include behavioral biometrics, mobile device security, synthetic data for AI training, privacy in biometric systems, and the application of Transformer models to user authentication. Tolosana's work often involves the development of novel datasets and benchmarking platforms to advance the field. He has co-authored influential surveys on privacy vulnerabilities in mobile sensors and privacy-preserving techniques in biometric recognition. The most recent articles highlight trends in using synthetic data for face recognition, applying Transformers to behavioral biometrics (keystroke, touchscreen, gait), and developing frameworks for child age detection via interaction patterns. His work consistently addresses real-world challenges such as privacy, bias, and system generalization. Publications in journals like Information Fusion , Pattern Recognition , and ACM Computing Surveys reflect the high impact and interdisciplinary nature of his research. Second FRCSyn-onGoing: Winning solutions and post-challenge analysis to improve face recognition with synthetic data (2025) ChildCI framework: Analysis of motor and cognitive development in children-computer interaction for age detection (2024) FRCSyn-onGoing: Benchmarking and comprehensive evaluation of real and synthetic data to improve face recognition systems (2024) SwipeFormer: Transformers for mobile touchscreen biometrics (2024) An Overview of Privacy-Enhancing Technologies in Biometric Recognition (2024) Ruben Tolosana collaborates extensively with researchers in the BiDA Lab, including Rubén Vera-Rodríguez, Aythami Morales, Julian Fierrez, and others. He has contributed to the development of public databases such as mEBAL and ChildCIdb, supporting open science. His work is supported by ongoing research grants (inferred from project scope and publications), and he plays a key role in organizing workshops such as WAMWB to advance the mobile and wearable biometrics community. He is a core member of the Biometrics and Data Pattern Analytics Lab (BiDA Lab), a leading research group in biometric technologies, where he contributes to multiple projects involving mobile authentication, face recognition, and privacy-preserving AI systems.

Neitzke Adamo, Laurenمشاهده پروفایل

دانشیار

• Paleoceanography
• Stable Isotope Stratigraphy
• Geoscience Education
• +۴ مورد دیگر

Lauren Neitzke Adamo is an Associate Professor in the Department of Earth and Planetary Sciences at Rutgers University, where she directs the Undergraduate Program (2022–present) and co-leads the Rutgers University Geology Museum (2016–present). Her career includes roles as Assistant Teaching Professor (2016–present), Lecturer (2008–2016), and prior leadership at the museum. Education : Ph.D. (2016), M.S. (2006), and B.S. (2004) from Rutgers University. Her research spans paleoceanography , stable isotope stratigraphy , and innovative geoscience education , focusing on drone-based remote sensing, 3D visualization, and museum outreach. She integrates technology like UAVs and 3D printers to enhance educational experiences and coastal process analysis. Recent publications highlight her work in virtual field trips (Newark Basin), drone-assisted coastal geomorphology, and science communication through comics and interactive museum exhibits. Collaborative projects emphasize democratizing geospatial tools and engaging diverse audiences via digital platforms.