جست‌وجوی استاد و پژوهشگر

• Human-Computer Interaction (HCI)
• Tangible User Interfaces (TUIs)
• Smart Home Systems
• +۳ مورد دیگر

Michael B. Chamunorwa is a Research and Design Engineer and PhD candidate at the University of Oldenburg's Department of Computing Science (School II), specializing in Media Informatics and Multimedia Systems. His research focuses on designing user interfaces embedded in everyday objects for smart home control, exploring embodied interaction and repurposing household items as smart home interfaces. He holds a Bachelor of Technology in Software Engineering and a Master's in Computer Science from the Namibia University of Science and Technology. Michael has taught as a tutor and project supervisor in courses such as 'Experiments and Studies' and 'Makers’ Lab - Things that Think', supervising projects like 'Rich Interactive Materials for Everyday Objects in the Home'. His work bridges theoretical research with practical applications, including developing tools for cultural preservation with marginalized communities in Namibia. Key research areas include tangible user interfaces, embodied interaction, and smart home systems. His projects often involve collaborations with industry-standard frameworks and have been published in venues like ACM International Conference on Mobile and Ubiquitous Multimedia (MUM) and Interactive Surfaces and Spaces. Michael's current PhD project investigates secondary affordances of everyday objects to enhance smart home user experiences. He has contributed to open-source tools like the 'Popup Observation Kit' for remote usability testing and the 'Sweet Spots' AR platform for interaction area visualization. He has been actively involved in the Virtual and Augmented Reality Lab (inf174) and the Makers’ Lab, emphasizing hands-on innovation in technology design. His work reflects a commitment to both academic rigor and real-world societal impact through technology.

Pierre Jourlinمشاهده پروفایل

استاد

• Computer Science
• Artificial Intelligence
• Programming Languages
• +۳ مورد دیگر

Pierre Jourlin is a Professor at Avignon University, specializing in Computer Science and Artificial Intelligence. He actively contributes to academic events such as workshops on programming education and AI ethics. His research focuses on areas like natural language processing, machine learning, and the societal impact of AI. Jourlin has organized events like a programming workshop for high school students (2022) and authored numerous articles on topics ranging from rule-based event extraction to generative AI in creative writing. His academic contributions include work on semantic disambiguation, medical literature tools (SIMI), and foundational studies in speech recognition and multimedia retrieval. He critiques AI limitations, emphasizing the importance of human oversight in code generation and advocating for accessible education to counteract underfunding in public schools. Jourlin's recent publications (2024–2025) address AI's role in creative fields and the evolution of programming languages. His work often bridges technical innovation with ethical considerations, as seen in his analysis of code-producing AI tools like Copilot. He remains an active member of the academic community, blending research with pedagogical outreach.

• Complex Event Processing
• Healthcare Informatics
• Semantic Computing
• +۵ مورد دیگر

Fabio Persia is a Professor at the University of Naples Federico II with an extensive publication record spanning 15 years (2009-2025), demonstrating continuous academic engagement. His research portfolio spans multiple institutions through collaborations with over 70 co-authors, most notably Daniela D'Auria (43 publications), Mouzhi Ge (17), and Giovanni Pilato (14). Dr. Persia's research interests focus on the intersection of semantic computing, event processing, and practical applications. His work evolved from foundational contributions to multimedia recommender systems (2013) to developing the ISEQL interval-based surveillance event query language (2016), and most recently to healthcare AI applications. He has pioneered complex event processing frameworks for video surveillance, created multi-agent systems for epilepsy detection (PredictMed-epilepsy), and explored social sensing for personalized routing during the pandemic. His recent work increasingly integrates large language models with healthcare monitoring systems, reflecting current AI trends. Analysis of his publication trends since 2020 reveals a strong healthcare focus (65% of recent work), particularly in patient monitoring architectures, clinical decision support, and medical AI integration. His publications demonstrate consistent methodological rigor across domains, often combining semantic computing with real-time event processing to address practical challenges in healthcare and social computing contexts. Dr. Persia has served as guest editor for six special issues in the International Journal of Semantic Computing (2023-2025) covering Robotic Computing, Transdisciplinary AI, and Multimedia Computing, confirming his leadership in these research communities. His editorial roles complement his extensive publication record, which includes 25 journal articles and 76 conference papers. His collaborative research includes significant projects with Stefania Costantini on patient monitoring systems, with Mouzhi Ge on multimedia recommenders, and with Sven Helmer on interval joins and event detection. While specific grant information isn't detailed in publications, his sustained output suggests successful funding from multiple sources. His current research trajectory indicates growing emphasis on LLM integration in medical contexts and context-aware systems for public health applications.

• Signal Processing
• Video Coding
• Multimedia Transmission
• +۲ مورد دیگر

Dr. Pradeepa Yahampath is a Professor in Electrical and Computer Engineering at the University of Manitoba's Price Faculty of Engineering, specializing in signal processing and multimedia communications. Research interests include: Next-generation video coding techniques Reliable multimedia transmission in wireless systems Joint source-channel coding methods Adaptive transform coding Recent publications develop novel coding schemes for correlated sources, fading channels, and OFDM systems. Theoretical frameworks address bandwidth constraints and channel uncertainty challenges. Research contributes to efficient data representation and robust transmission for multimedia applications in bandwidth-limited environments.

• Instructional Technologies
• Artificial Intelligence in Education
• STEM Education
• +۳ مورد دیگر

Dr. Serkan Düzgün is an Associate Professor at Gazi University's Faculty of Education, Department of Basic Education, specializing in Classroom Education. He has previously worked as a part-time lecturer at Ankara Hacı Bayram Veli University and Ankara Yıldırım Beyazıt University. PhD, Master's, and Bachelor's degrees from Gazi University Active in instructional technologies, AI in education, STEM, and neuroscience applications Key contributor to Turkey's national education projects and civil society initiatives His research focuses on the integration of artificial intelligence in pedagogical practices, robotic coding platforms for K-12 education, and the cognitive impacts of neuroscience-based teaching methods . Recent work examines distance education challenges during the pandemic, learning style adaptations, and self-regulated learning in virtual environments. Current publications emphasize AI-driven educational tools , technology-enhanced literacy instruction , and virtual classroom dynamics . His 15 most recent articles (2021-2024) span topics like robotic coding in STEM education, emotional intelligence in remote teaching, and AI applications in qualitative research. Dr. Düzgün has conducted 108 projects, advised 3 theses, and actively participates in open-access initiatives and UN Sustainable Development Goals implementation through educational technology. He also played a pivotal role in establishing the "Voice of Turkish" Radio at Yunus Emre Institute.

Shiwen Maoمشاهده پروفایل

استاد

• Wireless Networks
• Multimedia Communications
• RF Sensing
• +۴ مورد دیگر

Shiwen Mao is a Professor and Earle C. Williams Eminent Scholar Chair at Auburn University's Department of Electrical and Computer Engineering. He serves as Director of the Wireless Engineering Research and Education Center. His education includes a Ph.D. in Electrical Engineering from Polytechnic University, M.S. in Systems Engineering, and dual B.E. degrees in Electronic Engineering and Enterprise Management from Tsinghua University. Research interests span wireless networks, multimedia communications, RF sensing for healthcare IoT, smart grid systems, and machine learning applications. Mao's work focuses on transforming edge intelligence, 6G systems, drone localization, and AI integration for next-generation networks. Recent publications demonstrate strong trends in AI-driven wireless communications, satellite-terrestrial networks, cybersecurity applications of large language models, and generative AI for wireless sensing. Awards and Honors: IEEE Communications Society's Best Paper Award (2021) IEEE Jack Neubauer Memorial Award (2020) Multiple National Science Foundation grants including a $300K award for 6G systems research Best Paper and Best Demo awards from IEEE conferences As Director of the Wireless Engineering Research and Education Center, Mao leads collaborative research involving over 20 faculty members addressing real-world communication challenges. The center develops solutions integrating drone technology, millimeter wave communications, and AI for future wireless systems.

Isabel Valera Martinezمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Data Science
• +۴ مورد دیگر

Isabel Valera Martínez is a full Professor of Machine Learning at the Department of Computer Science, Saarland University, and an Adjunct Faculty at the Max Planck Institute for Software Systems (MPI-SWS). She holds a PhD in Machine Learning from the University Carlos III of Madrid and has held prestigious fellowships including the Humboldt Postdoctoral Fellowship and the Minerva Fast Track Fellowship from the Max Planck Society. Her research focuses on developing interpretable, robust, and fair machine learning methods, with applications in healthcare, social systems, and consequential decision-making like hiring and loan approvals. Education: PhD in Machine Learning (2014) and MSc in Multimedia and Communications (2012) from University Carlos III of Madrid; Master’s work at Leibniz University Hannover (2009); Telecommunications Engineering from the Technical University of Cartagena (2009). Research Interests: Fairness in AI, Bayesian nonparametric models, robust machine learning, and applications in healthcare and social systems. She co-leads the ELLIS Robust Machine Learning program and the Saarbrücken AI & Machine Learning (SAM) Unit. Key Publications: Contributions to fair classification frameworks, automatic discovery of data types, and modeling psychiatric comorbidity. Notable venues include AAAI, NIPS/NeurIPS, JMLR, and ICML. Awards: Humboldt Fellowship, Minerva Fellowship, Best Paper Honorable Mention at WWW 2017. Labs & Collaborations: Active in the ELLIS Society and MPI-SWS, focusing on interdisciplinary AI applications.

Norah Lorwayمشاهده پروفایل

استادیار

• Artificial Intelligence
• Music
• Live Coding
• +۳ مورد دیگر

Dr. Norah Lorway is an Assistant Professor at the RTA School of Media, Toronto Metropolitan University. She specializes in artificial intelligence and music research, film composition, and live coding performance. With a PhD in Computer Music & Human-Computer Interaction from the University of Birmingham, her work bridges technology, health care, and creative expression. Her research spans artificial intelligence applications in music and healthcare, digital sound design, and human-computer interaction. Key projects include developing AI assistants for dementia care with the NHS and co-creating the Scorch music programming language. Education: BMus, Piano Performance, Mount Allison University Masters, Music Computing, University of Calgary PhD, Computer Music & Human-Computer Interaction, University of Birmingham Postdoc, University of British Columbia Awards: 18 Women Composers You Should Know (Sundance Institute, 2019) Cinema Eye Honors Nominee (2020) Immersion Fellowship, South West Creative Technology Network (2018) She co-founded the Studio for Creative Artificial Intelligence and has two software companies. Her artistic works have been featured globally, including TIFF and Sundance festivals.

Regina Kaplan-Rakowskiمشاهده پروفایل

استادیار

• Immersive Learning Environments
• Artificial Intelligence in Education
• Computer-Assisted Language Learning
• +۵ مورد دیگر

Regina Kaplan-Rakowski is an Assistant Professor in the Department of Learning Technologies at the University of North Texas. Her research focuses on immersive technologies like virtual reality (VR), artificial intelligence (AI), and computer-assisted language learning. She holds a PhD in Curriculum and Instruction from Southern Illinois University (2016), an MA in Foreign Languages (2006), and an MEd in European Studies (2001) from Pedagogical University, Cracow. Her research interests include VR applications in education, emotional responses to technology, and second language acquisition. Notable projects explore VR for social isolation mitigation, AI-mediated language learning, and accessibility for visually impaired learners. She has co-edited multiple books on educational technology, including pandemic-era teaching strategies and AI-driven innovations. Recent publications highlight VR’s impact on language anxiety reduction, AI integration in teacher training, and the effectiveness of immersive technologies in vocabulary and listening comprehension. Her work bridges theoretical insights with practical applications, influencing both classroom practices and technology design.

Mohsen Aminiمشاهده پروفایل

دانشیار

• Cloud Computing
• Artificial Intelligence (AI)
• Domain-Specific Cloud Computing
• +۷ مورد دیگر

Mohsen Amini is an Associate Professor in the Department of Computer Science and Engineering at the University of North Texas (UNT). He previously held tenured positions at the University of Louisiana Lafayette (UL Lafayette) and completed postdoctoral research at the University of Miami and Colorado State University. His research focuses on Cloud 2.0 systems, AI-friendly serverless architectures, and domain-specific computing for Industry 4.0, multimedia, and edge-to-cloud integration. He leads the High Performance Cloud Computing (HPCC) Lab and has attracted over $2.7 million in research funding, including an NSF CAREER Award (2021). His work emphasizes democratizing cloud-native development and enhancing system resilience through heterogeneous computing frameworks. Education: Ph.D. in Computing and Software Engineering, University of Melbourne (2012) M.Sc. in Software Engineering, Ferdowsi University (2006) B.Sc. in Software Engineering, Azad University (2003) Research Interests: Cloud+AI Integration Fluid Computing across Edge-to-Cloud Continuum Domain-Specific Cloud Platforms (e.g., Industry 4.0, Multimedia) Confidential Computing Security Awards: NSF CAREER Award (2021) Best Service Award at IEEE/ACM CCGrid 2023 Francis Patrick Clark/BORSF Endowed Professorship (2021–2024) Grants & Projects: NSF IRES Track 1: Wireless Federated Fog Computing for Remote Industry 4.0 ($400k grant) NSF CAREER: Special-Purpose Cloud for Serverless Multimedia Streaming ($513k grant) SmartSight: AI-Based Platform for Visually Impaired Assistance ($499k grant) Teaching & Advising: Current advising 5 PhD students and leading a team of 25+ researchers Teaches courses on Cloud Computing, Distributed Systems, and Software Engineering Lab & Collaborations: HPCC Lab develops open-source tools like the E2C simulator and OaaS framework. Active collaborations with institutions like IMDEA Networks and industry partners like Hub Enterprise Inc.

• Digital Forensics
• Network Security
• Artificial Intelligence
• +۳ مورد دیگر

John Sheppard is a Lecturer in the Department of Computing and Mathematics at South East Technological University. His research focuses on digital forensics , AI applications in cybersecurity , and network intrusion detection . His expertise spans forensic methodologies and the ethical implications of generative AI in investigations. Research interests include: AI-driven forensic analysis techniques Resource-constrained security systems Multimedia evidence processing Recent publications (2023-2024) demonstrate a strong emphasis on AI-enhanced cybersecurity solutions and innovative forensic geolocation methods . Work explores limitations and opportunities in applying large language models to digital investigations.

• Neuroscience
• Cognitive Science
• Neuroimaging
• +۷ مورد دیگر

Giacomo Handjaras is an Assistant Professor at the IMT School for Advanced Studies Lucca, affiliated with the MOMILAB research group. His work focuses on neuroimaging, sleep neurophysiology, affective neuroscience, and brain structure-function relationships. He explores topics such as neural correlates of emotions, sleep dynamics, and motor control mechanisms using advanced methodologies like EEG, fMRI, and computational linguistics. Research interests include: (1) Sleep architecture and slow-wave subtypes linked to thalamic activity, (2) Multisensory integration in perception and action, (3) Neuroplasticity in sensory restoration, (4) Computational analysis of dream semantics, and (5) Telemedicine applications in cardiac rehabilitation. His studies often integrate behavioral, neuroimaging, and computational approaches. Recent publications highlight trends in sleep-brain interactions, affective processing across modalities, and neural mechanisms underlying communication deficits. He has contributed to understanding the role of thalamic regulation in sleep stages and the impact of sensory deprivation on brain organization in congenitally blind individuals. His work bridges basic neuroscience with clinical applications in rehabilitation and cardiovascular health.

• Structural Steel Engineering
• Sustainability Impact of Tall Buildings
• Steel Construction Design
• +۳ مورد دیگر

Abbas Aminmansour is an Associate Professor at the School of Architecture, University of Illinois. His expertise spans structural steel engineering, tall building sustainability, and innovative educational technologies. He has contributed significantly to the design optimization of steel structures and the integration of multimedia tools in engineering education. His research emphasizes sustainable tall building practices, including environmental impact assessments and material efficiency. Key research areas include structural steel design, sustainability metrics for high-rise structures, and pedagogical innovations using IT. Notable works include studies on Integrated Design and Construction of Tall Buildings and Sustainability Impact of Tall Buildings . Recipient of the AISC Special Achievement Award (2015) for contributions to structural steel education. Active in media engagement, including a 2023 analysis on global tall building trends. Developed SteelDEM, an AI-driven multimedia tool for structural steel learning (1994). His work bridges technical innovation and real-world application, with a focus on advancing both construction practices and engineering education.

• Parallel and Distributed Systems
• Peer-to-peer Systems
• Large-scale Distributed Systems
• +۵ مورد دیگر

Charalambos Papadakis is an Assistant Professor at the Department of Electrical and Computer Engineering (E.M.E.) of the Hellenic Mediterranean University (EL.ME.PA). His research focuses on Distributed Services and Networks. He holds a PhD from the University of Crete's Department of Computer Science, with a thesis titled "Improving Routing in Unstructured Peer-to-Peer Systems". He earned his B.A. in Computer Science (University of Crete, 2000) and M.A. in Computer Engineering (University of Patras, 2004). Teaching responsibilities include undergraduate courses like "Computer Networks II", "Distributed Systems and Clouds", and "Big Data", as well as postgraduate courses such as "Distributed Systems and Applications". He collaborates with the MNCLab (Multimedia, Networks and Communications Laboratory) at the University of Athens, focusing on Network and Distributed Systems research. Papadakis has authored over 30 publications in international journals/conferences, achieving an h-index of 8 and i10-index of 7. His research spans blockchain systems, graph analysis, and peer-to-peer networks. He actively reviews for academic conferences and journals and has led numerous EU/National R&D projects.

Yu Liangمشاهده پروفایل

مدرس

• Computer Vision
• Machine Learning
• Image Processing
• +۴ مورد دیگر

Dr. Yu Liang is a Lecturer at the Department of Information Technology and Electrical Engineering at ETH Zürich. His research focuses on advancing computer vision and machine learning techniques, particularly in video generation, image restoration, and event-based systems. He specializes in developing innovative frameworks for tasks like motion-aware video synthesis, low-light image enhancement, and diffusion models applied to multimedia processing. Key research interests include hierarchical information flow architectures, transformer-based networks, and scalable solutions for real-world imaging challenges. His work emphasizes practical applications of generative models and cross-modal fusion techniques to achieve high-quality visual outputs. Dr. Liang has contributed extensively to the field through publications on topics such as Fractal-IR for image restoration, Uni3C for 3D-enhanced video generation, and event-based frame interpolation. His research often bridges theoretical advancements with practical implementations, addressing issues like temporal coherence, motion deblurring, and adaptive illumination estimation. Although no specific academic awards are listed, his prolific publication record (over 20+ papers since 2019) highlights his active role in the academic community. His work has led to impactful datasets like Lsdir and frameworks like SwinIR, demonstrating strong contributions to both methodology and infrastructure in computer vision.