جست‌وجوی استاد و پژوهشگر

• Internet Law
• Data Protection Law
• Information Technology Law
• +۳ مورد دیگر

Sebastian Brüggemann is a German legal scholar specialising in Internet, data-protection and IT law. Since 2013 he has been a part-time lecturer (Lehrbeauftragter) at the Faculty of Law of Eberhard Karls University of Tübingen, and he holds parallel teaching appointments in data-protection and IT law at the Universities of Applied Sciences in Kehl and Ludwigsburg as well as at ZHAW School of Management and Law in Winterthur, Switzerland. In private practice he works as in-house counsel (Syndikusrechtsanwalt) for a large international IT company, focusing on data-protection and technology law. Education: 2003-2011: Studies of Law and General Rhetoric, Eberhard Karls University of Tübingen 2009: First State Law Examination, Tübingen 2011: Magister Artium in General Rhetoric, Tübingen 2010-2012: Legal clerkship (Referendariat), including stages at the German University of Administrative Sciences Speyer and eco – Verband der Internetwirtschaft 2012: Doctorate in Law (Dr. iur.), Tübingen – dissertation on third-party disclosure claims against Internet providers in copyright enforcement 2013: Admission as attorney (Rechtsanwalt) 2013-2015: Part-time LL.M. in Information Technology Law, Carl von Ossietzky University of Oldenburg Research interests span the intersection of law and digital technology: data-protection compliance under the GDPR, cybersecurity regulation, copyright in digital media, network neutrality, M2M/IoT legal issues, and the legal framework of behavioural advertising. His work frequently analyses German, European and comparative US developments. He has authored a monograph, numerous commentaries to GDPR/BDSG provisions, model IT contracts, and more than two dozen peer-reviewed articles and case notes since 2013, identifying recurring themes such as data portability, ISP liability, streaming and copyright, and the challenges of Industrie 4.0. Professional memberships & science communication: editorial board of Privacy in Germany , core team member of the Telemedicus IT-law portal, member of IAPP, DGRI and GRUR, and co-author of sector guidelines issued by Bitkom and eco association. There is no indication of supervised doctoral or master’s students in the supplied material; his teaching activities concentrate on specialised continuing-education courses and part-time lectures.

Scotty Craigمشاهده پروفایل

دانشیار

• Cognitive Science
• Learning Engineering
• Educational Technology
• +۱۱ مورد دیگر

Scotty D. Craig is an Associate Professor in Human Systems Engineering at The Polytechnic School, Arizona State University. He serves as Director of Strategic Initiatives at ASU's Learning Engineering Institute and co-directs the ASU Advanced Distributed Learning Lab in collaboration with the U.S. Department of Defense. His research spans cognitive science, educational technology, and immersive learning environments with applications in virtual humans, mixed reality training systems, and intelligent tutoring technologies. Ph.D. Experimental Psychology (Cognitive Learning), University of Memphis (2005) M.S. Psychology, University of Memphis (2001) B.A. Psychology with minors in Anthropology and History, University of Memphis (1998) Dr. Craig's research focuses on the intersection of human cognition, technology, and learning sciences. His work includes virtual humans for training, cognitive load optimization in medical websites, and mixed reality systems for medical education. He leads multiple DOD-funded projects totaling $8.5M, including the $5M Virtual Insomnia Patients system and $2M WaterSim America sustainability game. Recent publications emphasize immersive learning technologies, with 2025 work on collaborative AR learning companions and 2024 studies on voice quality impacts in pedagogical agents. His research has produced over 150 publications, including three edited books on educational technology. Scientific Honors: Pacific Southwest Best Paper Award (ASEE 2016) Best Poster Award (AIED 2017) Innovation in Scholarship Award (ASU 2017) Faculty Teaching Excellence Award (ASU 2018) Top 5% Teaching Recognition (Fulton Engineering 2024) Dr. Craig serves on editorial boards for International Journal of STEM Education and Computers & Education . He has organized five journal special issues and conducted extensive research evaluations for the U.S. DoD.

Mustafa Sertمشاهده پروفایل

دانشیار

• Audio Signal Processing
• Machine Learning
• Semantic Multimedia
• +۵ مورد دیگر

Mustafa Sert , currently serving as Associate Professor at Başkent University's Department of Computer Engineering and as Vice Dean of the Faculty of Engineering, has made significant contributions to audio signal processing, machine learning, and semantic multimedia. He earned his PhD (2006), MSc (2001), and BSc (1997) in Computer Engineering from Gazi University, supervised by prominent academics. PhD: Gazi University (2006) MSc: Gazi University (2001) BSc: Gazi University (1997) His research focuses on audio-visual content analysis , multimodal information fusion , and machine learning applications in semantic multimedia systems. He leads projects at the intersection of deep learning , speech processing , and acoustic pattern recognition , with work appearing in venues like IEEE Access, ACM Multimedia conferences, and Signal Processing and Communications Applications Conference (SIU). Recent publications demonstrate trends in automated audio captioning , medical speech analysis , and educational data mining , with applications spanning mental health detection, chatbot development, and reviewer selection systems. His work integrates transformer architectures , convolutional networks , and fuzzy decision-making models . Scientific Recognitions: Best Paper Award (7th Eurasian Congress on Emergency Medicine 2021) Outstanding Reviewer Awards (IEEE ICME 2020, 2021) Outstanding Area Chair Award (ACM Multimedia 2024) Academic Leadership includes roles as Senior IEEE Member, technical committee board positions in IEEE CTSoc divisions, and ACM membership. He supervises over 20 graduate students in topics ranging from depression detection through speech to geothermal permeability estimation , while maintaining active involvement in conference organization and journal reviewing for top-tier publications.

Imran Ahmedمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Deep Learning
• +۹ مورد دیگر

Dr. Imran Ahmed serves as a Senior Lecturer in Artificial Intelligence at Anglia Ruskin University's Faculty of Science and Engineering, School of Computing and Information Science. With over 100 research publications exceeding 250 JCR impact factor and an h-index greater than 30, he represents a distinguished academic in computer science and engineering fields. Dr. Ahmed's research spans multiple domains of artificial intelligence, with particular expertise in machine learning, deep learning, computer vision, and data science. His work focuses on medical imaging applications including brain tumor detection, Covid-19 detection, pulmonary nodule classification, and liver lesion detection. He also pioneers research in surveillance systems, IoT-enabled environments, anomaly detection, and AI applications for sustainability in environmental monitoring and precision farming. His recent publications demonstrate a strong trend toward practical AI applications in healthcare, environmental sustainability, and intelligent transportation systems. The research shows increasing emphasis on explainable AI, edge computing implementations, and interdisciplinary approaches that bridge computer science with medical, environmental, and industrial applications. His work consistently addresses real-world challenges with innovative technical solutions. World's top 2% scientists by Stanford University (2021, 2022) Double Gold Medallist Certificate of merit for brain MRI analysis for tumor detection Numerous awards for teaching, research, and administrative excellence Dr. Ahmed supervises research across multiple domains including medical imaging, healthcare informatics, surveillance systems, environmental monitoring, agricultural technology, recommender systems, anomaly detection, cyber security, public health, urban planning, smart cities, augmented reality, and human-computer interaction. His research projects include Human Surveillance and Activity Recognition, Data Analytics during Covid-19, Sustainable Healthcare applications, Deep Learning in Medical Imaging, and Sustainable Environmental Control frameworks. As Principal Investigator, he has led multiple funded projects integrating IoT and AI technologies for practical applications. He is actively involved in organizing technical sessions and workshops for IEEE conferences, particularly focusing on cybersecurity issues of IoT in Ambient Intelligence environments, connected intelligence for IoT applications, and real-time data processing in industrial contexts. His professional memberships include Fellow of the Higher Education Academy, Senior Member of IEEE, Member of ACM Computer Society, and Senior Member of the Institute of Research Engineers and Doctors.

• Graph Neural Networks
• Machine Learning
• Artificial Intelligence
• +۳ مورد دیگر

Fabian Jogl is a PreDoc Researcher at the Vienna University of Technology (TU Wien) within the Faculty of Informatics, holding dual affiliations in the Department of Databases and Artificial Intelligence (Institute E192) and the Department of Machine Learning (Institute E194). His work centers on theoretical and applied aspects of graph neural networks under the StruDL (2023–2027) and VHH (2019–2023) research projects. His research focuses on the expressivity limits of graph neural networks, particularly investigating whether enhanced expressivity translates to better predictive performance. Key areas include outerplanar graph analysis, path-based GNN architectures, global feature integration, and connections to the Weisfeiler-Lehman hierarchy. He examines structural properties of GNNs through homomorphisms and graph transformations to advance graph representation learning. Recent publications reveal trends toward unifying theoretical expressivity frameworks with empirical validation across diverse graph datasets. His work bridges geometric deep learning for cell complexes and practical applications like historical film analysis via the Historian dataset. Jogl actively contributes to major conferences including NeurIPS, ICML, and LoG while co-supervising student projects in machine learning algorithms. As a core member of the StruDL project, he investigates deep learning model structures for graph data, extending prior work on historical film annotation under the VHH project. His technical contributions include novel GNN simulation techniques and methods for enhancing message-passing architectures through graph transformations.

Jeffrey Martiniمشاهده پروفایل

استاد

• Middle East Security
• Military Affairs
• Threat Assessment
• +۳ مورد دیگر

Jeffrey Martini is an Associate Director at the RAND Arroyo Center's Strategy, Doctrine, and Resources Program, a Senior International Defense Researcher at RAND, and a Professor of Policy Analysis at the RAND School of Public Policy. His work focuses on Middle East security, U.S. military strategy, and conflict analysis. He holds an M.A. in Arabic Studies from Georgetown University and a B.A. in Political Science and Economics from Middlebury College, with four years of lived experience in the Arab world, including Peace Corps service in Morocco. His research spans climate change's impact on regional security, proxy warfare dynamics, and U.S. defense strategies in volatile regions. Notable contributions include analyses of Iran-backed militant groups, climate-related conflict projections for U.S. Central Command (CENTCOM), and studies on deterrence effectiveness in Europe and the Middle East. Martini has also authored works on Arab Gulf security, Syria stabilization, and civil-military relations in Egypt. Martini's articles reflect a blend of strategic foresight and empirical analysis, addressing topics like climate-induced instability, adversary exploitation of conflicts, and optimizing defense investments. His expertise is further highlighted in multimedia engagements, including panel discussions on CENTCOM challenges and podcasts dissecting regional geopolitical shifts.

• Natural Language Processing
• Large Language Models
• Digital Libraries
• +۶ مورد دیگر

Min-Yen Kan is an Associate Professor and Vice Dean of Undergraduate Studies at the National University of Singapore (NUS), with a focus on the Department of Computer Science. He earned his Ph.D., M.Sc., and B.S. in Computer Science from Columbia University. Associate Professor, NUS Department of Computer Science Vice Dean of Undergraduate Studies, NUS School of Computing His research spans Natural Language Processing , Large Language Models , Digital Libraries , and Information Retrieval , with applications in Human-Computer Interaction , Web Systems , and Recommendation Technologies . He leads the Web, Information Retrieval, and NLP Group (WING.NUS), driving projects in scholarly document analysis, dialogue systems, and AI ethics. Recent publications highlight his work on LLM alignment , multimodal deception detection , and evaluation frameworks . Key trends include ethical NLP, knowledge aggregation in vision-language models, and combating misinformation through AI. Scientific Awards: Best Paper Award, CIKM 2019 Distinguished Service Awards, ACL Vannevar Bush Best Paper Award, JCDL 2012 As a PhD advisor , his students have secured roles at institutions like Google and USTC. He also serves on the ACL Ethics Committee and as associate editor for Information Retrieval and JAIR .

Brian Ó Raghallaighمشاهده پروفایل

استادیار

• Digital Terminology
• Onomastics
• Folkloristics
• +۶ مورد دیگر

Dr. Brian Ó Raghallaigh is an Assistant Professor in Fiontar & Scoil na Gaeilge at Dublin City University (DCU). He holds a BA (Mod.) in computational linguistics and a PhD in speech technology from Trinity College Dublin. His research focuses on digital terminology, onomastics, folkloristics, phonetics, and language technology. He is Co-Principal Investigator of the AHRC-IRC 'Decoding Hidden Heritages' project (2021–2024) and Principal Investigator of the Department of the Gaeltacht-funded 'Logainm Placenames Database of Ireland' project. Education: BA (Mod.) in Computational Linguistics (Trinity College Dublin), PhD in Speech Technology (Trinity College Dublin) Roles: Technology Manager of the Gaois research group, Module Coordinator for Irish Linguistics (LIG1004), Co-coordinator for Corpus Research (LIG1010) Publications: Authored Fuaimeanna na Gaeilge , creator of fuaimeanna.ie , and co-editor of Decoding the Oral Traditions of Scotland and Ireland . His research interests span terminology, placename studies, digital humanities, and language preservation. He leads projects like Terminologue (a cloud-based terminology platform) and collaborates on initiatives such as the EU-GA terminology project. He is active in professional organizations like SNSBI, SIEF, and CIGILT. Grants & Projects: Funded by AHRC/IRC, Department of the Gaeltacht, RIA. Key projects include Logainm.ie , Gaois surname database , and Historical Dictionary of Modern Irish . Labs/Teams: Gaois research group (focused on language technology), Terminologue (terminology management), and collaborations with the Digital Repository of Ireland (DRI).

Thomas Littleمشاهده پروفایل

استاد

• Smart and Connected Systems
• Visible Light Positioning
• Mobile and Vehicular Ad Hoc Networks (MANETs)
• +۲ مورد دیگر

Thomas Little is a Professor in the Department of Electrical & Computer Engineering and Systems Engineering at Boston University, serving as the Associate Dean of Educational Initiatives. He holds a PhD from Syracuse University (1991) and leads the Multimedia Communications Laboratory. His research focuses on smart systems, visible light positioning, MANETs, pervasive computing, and optical wireless communications. Key honors include the Kern Faculty Fellow, NSF CAREER Award, and Senior Member of IEEE. His teaching spans courses like EC444 (Smart Systems) and EC744 (Mobile Ad Hoc Networking). He is affiliated with the Center for Information and Systems Engineering and Clean Energy Sustainability Initiative. Recent publications emphasize optical wireless networks, interference mitigation, and 3D localization. Over 150 articles showcase advancements in VLC systems, hybrid RF/VLC networks, and smart lighting integration with 5G frameworks. His work bridges communication technologies and environmental sustainability.

• Applied Linguistics
• Foreign Language Education
• Sociolinguistics
• +۳ مورد دیگر

Merje Miliste is a Lecturer in German Language and Linguistics at the University of Tartu's Faculty of Arts and Humanities, Institute of Foreign Languages and Cultures (1.00 FTE since 2019). Previously, she held roles including Programme Director for German Studies (2014), Academic Developer (2016–2019), and various lecturer positions since 2003. She earned a Doctor's Degree in 2011, focusing on interactions between Estonian learners' mother tongue and other languages when acquiring German as an additional foreign language. Education : PhD (2011, University of Tartu) with a thesis on mother tongue interactions in multilingual learners; MA (2000, German Philology); BA (1996, German Language and Literature). Pedagogy training (1995–1996) and intercultural mentorship certification (2008–2009). Research Interests : Applied linguistics, multilingualism, language acquisition processes, technology in language learning, foreign language pedagogy, and sociolinguistics. Her work emphasizes intersections between mother tongue influence, digital tools, and educational methodologies. Publications Overview : Over 20 peer-reviewed articles and book chapters since 2001, focusing on topics like AI's role in language media, YouTube-driven language learning, MOOC engagement patterns, and multilingual curriculum design. Recent work explores digital dictionary usage and collaborative teaching strategies. Awards : 2015 Tartu University Scholarship for Teaching and Learning Innovation. Recognized for administrative leadership in educational initiatives. Grants & Roles : Managed German MA programs (2013–2015), chaired national German Olympiad committees (2001–2002), and contributed to language policy discussions in post-Soviet educational contexts. Active in teacher training and intercultural mentorship programs. Labs/Teams : Collaborates with the Institute of Foreign Languages and Cultures on multilingual education projects and digital pedagogy initiatives.

Atanas Gotchevمشاهده پروفایل

استاد

• Immersive Imaging
• 3D and Light Field Imaging
• Image Quality Assessment
• +۲ مورد دیگر

Atanas Gotchev is a Professor of Signal Processing at Tampere University, Finland, where he leads the 3D Media Group and directs the Centre for Immersive Visual Technologies (CIVIT). He also serves as Chair of the Erasmus Mundus Joint Master Programme in Imaging and Deputy Director of the TAU Imaging Research Platform. Gotchev holds degrees from Technical University Sofia (M.Sc. in Electronics and Automation Engineering and M.Sc. in Applied Mathematics), the Bulgarian Academy of Sciences (PhD in Information Technologies), and Tampere University of Technology (D. Tech.). His research focuses on immersive imaging, 3D/light field imaging, computational optics, and image quality assessment. He has coordinated three Marie Sklodowska-Curie networks in light field imaging and serves as Senior Editor for IEEE Transactions on Image Processing and the Journal of Electronic Imaging. Gotchev has organized major conferences like the IEEE International Conference on Image Processing (2026) and chaired workshops on multimedia signal processing. Recent research emphasizes computational cameras, diffractive optics, and end-to-end design for metaoptics. He has a visiting professorship at the University of Utah (2023-2024) supported by Fulbright and Nokia Foundation grants. His work spans datasets like CIVIT and contributions to safety-critical applications in robotics and ITER projects.

Carol Roundsمشاهده پروفایل

مدرس ارشد

• Hungarian Pedagogy
• Uralic Linguistics
• Finno-Ugric Languages
• +۳ مورد دیگر

Carol Rounds is a Senior Lecturer in Hungarian at Columbia University's Department of Italian. She has been affiliated with Columbia since 1979 and specializes in Hungarian pedagogy and Uralic linguistics. Her research explores linguistic relationships among Finnish, Komi, and Hungarian, particularly focusing on definiteness in syntax. She holds a BA in Linguistics (1984), MA (1986), and PhD in Uralic Studies (1992). Her publications include seminal works like Hungarian: An Essential Grammar and Colloquial Hungarian , both widely used in language education. In 2010, she received the Pro Cultura Hungarica Award for advancing Hungarian language and culture abroad. Teaching focuses on Hungarian language instruction, including elementary, intermediate, and advanced courses. Courses recently taught include UN1101 (Elementary Hungarian I), UN2101 (Intermediate Hungarian I), and UN3341 (Advanced Readings in Hungarian). Education: BA in Linguistics (1984) MA in Uralic Studies (1986) PhD in Uralic Studies (1992) Research Highlights: Authored/co-authored major Hungarian language textbooks Explored accusative marking systems in Finno-Ugric languages Her publications reflect a sustained engagement with language pedagogy and comparative Uralic linguistics, bridging theoretical research with practical language instruction materials.

• Digital Signal Processing
• Image Processing
• Multimedia Communications
• +۳ مورد دیگر

Marco Carli is a Full Professor at the Department of Industrial, Electronic, and Mechanical Engineering, Roma Tre University, Italy. He holds a Laurea in Telecommunication Engineering from Università degli Studi di Roma 'La Sapienza' and a Ph.D. from Tampere University of Technology. His research focuses on digital signal and image processing applied to multimedia communications, including digital watermarking, multimedia quality evaluation, and information security. He has led projects such as EHEM (medieval architecture modeling), ISEEYOO (AI-based anomaly detection), and INSECTT (secure IoT-AI systems). Carli serves as an Associate Editor for IEEE Transactions on Image Processing and Area Editor for Signal Processing: Image Communication. He is an IEEE Senior Member. His work spans over 55 journal publications and numerous conferences, addressing topics like immersive VR applications, cybersecurity, and perceptual quality metrics. Education: Laurea in Telecommunication Engineering, Università di Roma 'La Sapienza', 1990s Ph.D. in Telecommunication Engineering, Tampere University of Technology, Finland Projects: EHEM: Digital modeling of medieval architecture and art ISEEYOO: Anomaly detection in Cyber-Physical Systems INSECTT: Secure IoT systems with AI Research Interests: Signal/image processing for multimedia Quality evaluation and watermarking Cybersecurity and IoT applications Awards: None explicitly listed Grants/Advising: Multiple EU-funded projects (e.g., ImmerSAFE, RESISTO, ATENA) and collaborations with industry partners like Thales Alenia Space.

Ellen Garlandمشاهده پروفایل

پژوهشگر ارشد

• Animal Culture
• Social Learning
• Bioacoustics
• +۷ مورد دیگر

Dr Ellen Garland is a Principal Research Fellow in the School of Biology at the University of St Andrews , Scotland. She is affiliated with the Centre for Biological Diversity, the Scottish Oceans Institute, the Sea Mammal Research Unit (SMRU), and the Centre for Social Learning & Cognitive Evolution. She leads multiple research projects funded by The Royal Society and is an active Principal Investigator in marine bioacoustics and animal culture. Research Interests: Her primary research focuses on animal culture , social learning , bioacoustics , and behavioural ecology , particularly in cetaceans. She specializes in the cultural transmission, vocal learning, and function of humpback whale song, using vocal sequence analysis to define population structures for conservation. Her work contributes to UN Sustainable Development Goals related to life below water and biodiversity. Recent Research Trends: Her recent publications (2023–2025) explore humpback whale song complexity, cultural evolution, mating systems, and the parallels between whale song and human language. These studies combine bioacoustics, genetics, and network analysis to understand cultural transmission and population dynamics. Scientific Awards: National Academy of Sciences Postdoctoral Fellowship (2012) Academy of Medical Sciences SUSTAIN career programme (2023) ASA Acoustic Expert Multimedia: Honourable mention (2023) Co-lead, UNEP CMS Expert Working Group on Animal Culture (2023) Executive Officer, South Pacific Whale Research Consortium (2019) Advising and Grants: She supervises research and has led multiple funded projects with The Royal Society, including a University Research Fellowship extension (2022–2025) with over £360,000 in funding. She collaborates internationally and mentors early-career researchers. Her lab generates extensive datasets on cetacean vocalizations and genetics. Laboratories and Teams: She is embedded in the Sea Mammal Research Unit and the Centre for Social Learning & Cognitive Evolution, working with interdisciplinary teams on marine mammal cognition, communication, and conservation.

Soon Lay Kiمشاهده پروفایل

دانشیار

• Applied Natural Language Processing
• Data Management
• Aspect-Based Sentiment Analysis
• +۹ مورد دیگر

Soon Lay Ki is an Associate Professor at the School of Information Technology, Monash University Malaysia, where she also serves as Associate Head (Graduate Research) since November 2018. Her academic journey began with roles at Multimedia University (MMU), where she was a Senior Lecturer and Deputy Dean (Research and Innovation) from 2016 to 2018. PhD in Web Engineering, Soongsil University, Korea Master of Science in Database, Universiti Putra Malaysia Bachelor of Computer Science, Universiti Putra Malaysia Her research centers on applied natural language processing and data management , with a focus on analyzing domain-specific and social media content. Her work spans aspect-based sentiment analysis , cyberbullying detection , misinformation detection , and relation extraction from conversational texts. Recently, her research has expanded into digital health , particularly emotion-aware mental health chatbots and emotion detection via video data. The most recent articles highlight a strong trend in AI for social good , including legal reasoning, mental health, accessibility, and public health. Her publications appear in high-impact journals and conferences such as Artificial Intelligence and Law , IEEE Transactions on Dependable and Secure Computing , and ACL-affiliated workshops. She has received notable scientific awards, including: ITEX'24 Silver Award for 'MOBOT' mental health chatbot (2024) Silver Medal at Malaysia Technology Expo 2023 for the same innovation The Incubator Grant: Bolster Category (2023) Dr. Soon has graduated seven PhD and three Master’s students, one of whom received the MMU Best Master Thesis Award in 2015. She leads multiple research grants, including FRGS-funded projects and industry collaborations with Telekom Malaysia and Intel . She is currently a Chief Investigator or Primary Chief Investigator on six active projects, including WHinc, WAge, and Epsilon, often in collaboration with Monash Australia and SEACO. She is part of key research teams such as the Action Lab at Monash University Australia and the South East Asia Community Observatory (SEACO) , contributing to inclusive research infrastructure and public health data access initiatives.