جست‌وجوی استاد و پژوهشگر

Tobias Hodelمشاهده پروفایل

استادیار

• Digital Humanities
• Machine Learning in the Humanities
• Critical Algorithm Studies
• +۳ مورد دیگر

Prof. Dr. Tobias Hodel is an Assistant Professor of Digital Humanities at the University of Bern, affiliated with the Walter Benjamin College. His work focuses on applying machine learning and critical algorithm studies to historical and textual analysis. He holds a Ph.D. from the University of Zurich and has held roles such as Project Manager for the Königsfelden Edition Project and coordinator of the 'Ad fontes' e-learning program. Hodel’s research explores intersections between digital methods and traditional humanities, emphasizing ethical AI use in archives and historical workflows. He supervises numerous doctoral students and chairs the Swiss Academy of Humanities and Social Sciences (SAGW). His contributions span publications in journals like Historische Zeitschrift and conferences such as DHd and Digital Humanities. Education: Studied History and German Literature at the University of Zurich (2002–2010), with advanced roles in SNF-funded projects and book publications. His research interests include digital edition theory, text processing, and the epistemology of digital methods. Key research trends in his articles address historical document analysis, OCR advancements, and the ethical implications of AI in archives. He co-leads the ‘Basic Research and Digitization’ department at the Swiss Society for History and oversees programs like the MAS/CAS in Archives, Library, and Information Science. Hodel’s work bridges technical innovation with critical humanities scholarship.

• Human-Computer Interaction
• Technology and Gender Equality
• AI Ethics
• +۴ مورد دیگر

Elaine Huang is an Associate Professor of Human-Computer Interaction (HCI) and Head of the People and Computing Lab at the University of Zurich's Department of Informatics. She holds a PhD in Computer Science from Georgia Institute of Technology (2006). Her career includes prior roles as Assistant Professor at the University of Calgary and Senior Staff Researcher at Motorola Labs. Her research focuses on the interplay between technology and human behavior, particularly in areas of gender equality in tech, AI ethics, sustainable HCI design, and accessible technologies. She critiques systemic biases in AI training data and advocates for inclusive design processes integrating Hofstede's cultural dimensions. Her work also explores trust dynamics in sharing economies and predictive health technologies. Huang emphasizes empirical studies over intuition, stressing the need for data-driven insights into disruptive technologies like ChatGPT. She leads initiatives to improve STEM PDF accessibility and designs tools for chronic condition management through incident cards. Her lab develops frameworks addressing obsolescence in smart homes and sustainability in digital interfaces. Awards and recognitions focus on her contributions to HCI ethics and gender studies. She advises students to proactively shape their academic trajectories and leverage institutional resources strategically.

Tillman Weydeمشاهده پروفایل

عضو هیئت علمی

• Machine Learning
• Signal Processing
• Data Analysis
• +۵ مورد دیگر

Dr. Tillman Weyde is a Reader in the Department of Computer Science at City, University of London , where he has been employed since 2021. He leads the Machine Intelligence and Media Informatics Research Group and is a member of the Machine Learning Group . Prior to this, he served as Senior Lecturer (2009–2021) and Lecturer (2005–2009) at City, and worked as a researcher at the University of Osnabrück (2001–2005), coordinating the MUSITECH project. His academic background includes PhD in Music Technology (2002), MSc in Computer Science (1999), and MSc in Mathematics, Music, Philosophy & Pedagogy (1994), all from the University of Osnabrück. Research Focus: Machine learning and signal processing methods for data analysis with applications in finance, audio, NLP, music, health, security, and education. His recent work emphasizes inductive biases in neural networks for rule-learning, extrapolation, generalization, and interpretability. Grants & Projects: Principal Investigator for the AHRC-funded Digital Music Lab (2012–2017) and Integrated Audio-Symbolic Model of Music Similarity (2017–present). Co-investigator in Innovate UK and EPSRC projects on safer gambling ( Advancing Consumer Protection , 2015–2018) and Raven (2012–2021). Collaborations: Affiliated with the Institute of Cognitive Science (Osnabrück), Intelligent Systems Research Laboratory (Reading), and the MPEG Ad-Hoc Group on Symbolic Music Representation. Awards: Co-author of the 2000 Comenius Medal-winning educational software Computer Courses in Music Ear Training and co-editor of the Osnabrück Series on Music and Computation . Publications: Over 150 peer-reviewed works including conference papers, journal articles, and book chapters, focusing on interdisciplinary applications of machine learning in music, health, and finance. Students: Supervised 13 PhD students across topics like grammar bias in neural networks, emotion recognition from audio, extrapolation behavior in neural networks, relation-based patterns, legal text parsing, and more.

Moi Hoon Yapمشاهده پروفایل

استاد

• Computer Vision
• Medical Image Analysis
• Facial and Gesture Analysis
• +۳ مورد دیگر

Professor Moi Hoon Yap is a Professor of Image and Vision Computing and Lead of Human-Centred Computing at The Manchester Metropolitan University. Her research focuses on computer vision, deep learning, and medical image analysis, particularly in early cancer detection and diabetic foot ulcer tools. She leads projects funded by The Royal Society, EU, EPSRC, Innovate UK, and industry partners. She is an Associate Editor of the Journal of Computers and Programs in Biomedicine and has developed datasets and grand challenges for reproducible research, such as the DFU-2021 challenge. Her work includes facial analysis, gesture interpretation, and human behavior quantification. Key Projects: FAST Healthcare NetworksPlus Award (2020-2021), Royal Society PhD Studentship (2018-2022), FootSnap Cloud Infrastructure (2019-2021). Awards: Royal Society Industry Fellowship, Marie Skłodowska-Curie Innovative Training Network Grant. Research Interests: Medical imaging, facial/gesture analysis, human behavior analysis, dataset creation, and sustainable software development. Professor Yap supervises PhD students and teaches Data Analytics, Deep Learning, and related courses. She is actively involved in international collaborations to advance biomedical data sharing and federated learning mechanisms.

• Applied Physics
• Artificial Intelligence
• Data Analytics
• +۴ مورد دیگر

Dr. Vincent Ginis is a prominent academic at Vrije Universiteit Brussel (VUB), associated with the Applied Physics Department and the Data Analytics Lab. His roles include doctoral scholarship supervision and research leadership in interdisciplinary projects. He holds a strong background in applied physics, metamaterials, and AI-driven solutions for societal challenges. Current affiliations include: Principal Investigator in 19 funded projects (2010–2029), focusing on AI ethics, sustainable transitions, and historical data analysis Supervisor of 60+ student theses across master's and doctoral levels Recipient of 15+ prestigious awards including the Agathon De Potter Award and FWO/Barco Prize Research interests span: Applied Physics: Metamaterials, optics, and photonics AI Applications: Ethics, bias mitigation, and historical data digitization Social Sciences: Wealth inequality, intergenerational mobility, and policy impact analysis Recent work highlights include groundbreaking studies on: Large Language Models' performance in OCR tasks Bias patterns in AI citation practices Ethical frameworks for human-centered AI systems Notable collaborations span institutions in Europe and beyond, with 1295 citations across 120+ publications. His work is amplified through platforms like Strava data for urban planning and historical datasets from 19th-century archives.

Abied Alsulaimanمشاهده پروفایل

دانشیار

• Translation Studies
• Translation Technology
• Legal Translation
• +۵ مورد دیگر

Abied Alsulaiman is an Associate Professor at KU Leuven 's Faculty of Arts , specializing in Arabic Studies . He co-founded the Arabic Translators International (ATI) and co-edits its publication series. His teaching focuses on history of Arabic culture, legal translation, business translation, and interpreting. Research Interests : Translation studies, legal terminology (Arab states, Belgium, Netherlands), Arabic linguistics, Islamic studies, Judeo-Arabic literature, and Semitic languages. Projects : Functional equivalence in legal terminology, translation's role in Saudi students' historical awareness, OCR solutions for Arabic/Persian scripts, and diplomatic terms in Saudi Arabia. Publications : Recent works include co-edited handbooks on terminology, legal translation analysis of the US Constitution, and studies on Qur'anic lexicography and Islamic traditions.

Ryan Cordellمشاهده پروفایل

دانشیار

• Digital Humanities
• Textual Analysis
• 19th-Century American Literature
• +۳ مورد دیگر

Ryan Cordell is an Associate Professor in the School of Information Sciences at the University of Illinois at Urbana-Champaign and an affiliated faculty member in the Department of English. He is also a Core Founding Faculty Member of the NULab for Digital Humanities and a Senior Fellow at the Andrew W. Mellon Society of Critical Bibliography. His research focuses on how technologies shape textual circulation, with a specialization in 19th-century American newspapers and computational methods. Cordell co-leads the Viral Texts project, which uses data mining to trace text reuse in historical archives. He previously directed the Huskiana Experiential Letterpress Studio at Northeastern University. Education: PhD in English Language and Literature from the University of Virginia (2010). Research Interests: Digital humanities, textual analysis, history of print culture, computational social science, and cultural analytics. His work bridges literary studies, media history, and information science to explore how texts circulate and gain authority through networks. Awards & Honors: ACLS Digital Innovation Fellowship (2015-2016) NEH Digital Humanities Start-Up Grant (2013-2014) Outstanding Teaching Award, Northeastern University (2014-2015) Andrew W. Mellon Fellow in Critical Bibliography (2013-2016) Advising & Grants: Served as Project Director for multiple grants, including a Mellon Fellowship and NEH funding. Advises on interdisciplinary projects combining humanities and computational methods. Labs & Collaborations: Leads the Viral Texts initiative and collaborates with scholars in History, Computer Science, and Library Science. Affiliated with the NULab for Digital Humanities, focusing on computational social science and digital scholarship.

Zia Ush Shamszamanمشاهده پروفایل

مدرس ارشد

• Cybersecurity
• AI Governance
• Secure and Safe AI
• +۵ مورد دیگر

Dr. Zia Ush Shamszaman is a Senior Lecturer in Computer Science at Teesside University's School of Computing, Engineering & Digital Technologies (SCEDT). He holds a PhD in Computer Science from the University of Galway and a Master's from Hankuk University of Foreign Studies. His research focuses on Cybersecurity, AI Ethics, IoT Resilience, and Game Theory applications, with a strong emphasis on bridging academic research with industry applications. Teaching responsibilities include postgraduate modules on AI Ethics, Cyber Risk Management, and Ethical Hacking, alongside undergraduate courses in Secure Data Acquisition and Ethical Hacking. He actively supervises five PhD students in cybersecurity and AI, advocating for inclusive technology education and societal impact. Professional memberships include IEEE (Senior Member), Elsevier Advisory Panel, and W3C. He has organized conferences like the International Conference on Suitable Technologies 4.0 and served on program committees for major events. Recognized for exceptional peer reviewing, he has received awards from leading journals like the Journal of Network and Computer Applications and Future Generation Computer Systems. Current projects funded by Innovate UK include CyberPathway (diversity in cybersecurity education), SafeSCMS (AI-driven supply chain security), and Opera-CyberThemis (trustworthy AI frameworks). Past industry roles include technical leadership in Bangladesh's government projects like the Machine Readable Passport system and World Bank-funded Bangladesh Automated Clearing House initiative. Shamszaman's work spans industry collaborations, academic leadership, and community engagement, with recent media contributions on GenAI governance and cyber resilience strategies. His research integrates theoretical advancements with practical solutions for SMEs, healthcare systems, and underserved communities.

• Artificial Intelligence
• Computer Science
• Financial Modeling
• +۴ مورد دیگر

José Ignacio Olmeda Martos is a Professor at the Computer Science Department of the University of Alcalá, Spain. His research focuses on artificial intelligence, neural networks, financial modeling, and applications in tourism and e-learning. He leads the CSRG-UAH Cognitive Science Research Group and the AUDITAI Group for AI Software Development. He earned his Ph.D. in 1996 with a thesis on nonlinear financial models under Dr. Sergio Barba-Romero. His work bridges computational methods with real-world challenges in finance, tourism, and education. Research interests include predictive analytics, algorithmic optimization (genetic algorithms, SOMs), and accessibility in digital systems. His contributions span hybrid models in credit scoring, volatility forecasting using neural networks, and e-commerce adoption analysis. Over 25 years, he has published extensively on topics like tourism demand prediction (PLAZA project), web accessibility metrics, and financial market predictability. Key projects include developing internet-based tourism reservation systems for Castilla-La Mancha and applying wavelet filtering in financial time series. His research emphasizes interdisciplinary applications, integrating AI with tourism management and financial engineering. Education: Ph.D., Universidad de Alcalá, 1996 Publications reflect his expertise in computational finance, tourism technology, and machine learning. Despite no listed awards, his work demonstrates sustained impact in both academic and applied domains. Advising and grant activities are not detailed in the provided texts.

Mustafa Özuysalمشاهده پروفایل

استادیار

• Computer Vision
• Object Detection
• Object Tracking
• +۵ مورد دیگر

Mustafa Özuysal is an Assistant Professor in the Department of Computer Engineering at the College of Engineering, Izmir Institute of Technology (İYTE), where he leads the Visual Intelligence Research Group. His research focuses on computer vision, including object detection, tracking-by-detection, and real-time scene text recognition, with applications on mobile devices. Research Interests: Large-scale object detection Object detection and tracking on mobile platforms Real-time scene text recognition Feature learning from image and video sequences Augmented reality and camera egomotion estimation His scholarly work includes influential publications in IEEE TPAMI, IET Computer Vision, and top-tier conferences such as CVPR and ECCV, particularly in local feature descriptors like BRIEF and keypoint recognition using random ferns. His research emphasizes efficient, real-time algorithms suitable for embedded and mobile systems. Scientific Contributions: Co-developer of the BRIEF descriptor, widely used in computer vision for fast binary feature matching. Contributor to tracking-by-detection frameworks and homography estimation methods robust to occlusions and viewpoint changes. Dr. Özuysal has taught a range of undergraduate and graduate courses, including Introduction to Image Understanding, Vision-Based Tracking and Modeling, Data Structures, and Mobile Application Development. He advises the Visual Intelligence Research Group and continues to advance research in scalable and efficient vision systems.

• Digital Humanities
• Computational Humanities
• Text Mining
• +۱۰ مورد دیگر

Manuel Burghardt is a full-time Professor of Computational Humanities at the Institute of Computer Science , Leipzig University . He coordinates the Bachelor's and Master's programs in Digital Humanities and serves as a spokesperson for the GI's Computer Science and Digital Humanities Group and the Forum for Digital Humanities Leipzig . PhD in Information Science (summa cum laude) from University of Regensburg Magisterstudium in Information Science, English Linguistics, General Linguistics, and Corpus Linguistics at University of Regensburg Burghardt's research spans multiple Computational Humanities domains: Digital Environmental Humanities : Integrating Computational Literary Studies with Biodiversity Research via NLP and Information Retrieval Immersive Humanities : Applying AR/VR/XR, Eye Tracking, and Tangible Interfaces for Digital Humanities Text Mining & NLP : Focused on text reuse detection, similarity analysis, and sentiment modeling Video Analytics : Analyzing news videos and cinematic media through Distant Viewing techniques Theory of Digital Humanities : Investigating methodological foundations and scientometric trends Computational Game Studies : Multimodal empirical analysis of games Computational Spatial Humanities : Spatial data analysis in humanities contexts His recent publications demonstrate strong focus on: Improving OCR for historical documents (2015-2020) Computational drama analysis using sentiment and text mining techniques (2016-2019) Music information retrieval applications in folk song and manuscript analysis (2015-2019) Development of specialized tools for humanities data processing

• Computer Vision
• Machine Learning
• Document Analysis
• +۵ مورد دیگر

Ujjwal Bhattacharya is affiliated with the Indian Statistical Institute, India. His primary research focuses on computer vision, machine learning, and document analysis with a strong emphasis on multimodal perception systems and deep learning applications. He has published extensively in top-tier venues like ICPR, ICDAR, CVPR, and BMVC, contributing to advancements in autonomous driving, image processing, and privacy-aware machine learning. His work spans from developing robust pedestrian detection systems using multimodal sensors to enhancing degraded document image processing through domain adaptation and advanced neural architectures. Recent contributions include semi-supervised 3D object detection frameworks and privacy-preserving clustering techniques. Key research areas include: Multimodal sensor fusion for autonomous systems Deep learning for document analysis and OCR Privacy-aware metric learning Efficient neural network compression techniques Image enhancement and restoration His publication trends reflect a focus on solving real-world challenges in autonomous driving, degraded document processing, and privacy-sensitive machine learning applications.

• Information Retrieval
• Medical Informatics
• Natural Language Processing
• +۱۷ مورد دیگر

Guido Zuccon is a Professor at Queensland University of Technology (QUT), specializing in Information Retrieval and Medical Informatics. He is affiliated with QUT's ielab, contributing to research in health information systems, semantic web technologies, and quantum models for IR. His work emphasizes evaluation methodologies in medical search, clinical decision support, and healthcare informatics. Education: PhD in Information Retrieval (University of Glasgow, 2012). Research focuses on medical information extraction, ontology mapping, and user-centered IR systems. He has co-authored over 130 publications, including landmark studies on consumer health search, clinical query framing, and de-identification of health records. Key contributions include advancements in task-oriented search, diversity in rankings, and evaluation frameworks for health IR. His work bridges theoretical models (e.g., quantum probability ranking) with practical applications in healthcare and biomedical systems.

• Urban Economics
• Regional Economics
• Health Economics
• +۵ مورد دیگر

Kalle Kappner is an Assistant Professor in the Department of Economics at Ludwig-Maximilians-Universität München (LMU Munich), specializing in urban, regional, health and historical economics. He previously held teaching positions at Humboldt-Universität zu Berlin (2016-2022) where he served as a teaching assistant for graduate-level courses on European Economic History and developed seminars in economic geography. Dr. Kappner earned his PhD in economics from the Berlin School of Economics and Humboldt-Universität zu Berlin in 2021. His doctoral work, titled Water and the Micro-Geography of the Urban Mortality Transition: Essays on 19th Century Berlin , focused on the relationship between sanitation infrastructure and urban health outcomes during the 19th century. His primary research interests lie at the intersection of urban, regional, health and historical economics, with a particular focus on the economic consequences of 19th-century epidemic diseases. He employs empirical methods and works extensively with historical spatial data to examine how epidemics like cholera affected urban development patterns, population dynamics, and infrastructure investments. His work often combines economic history with spatial analysis techniques, including GIS mapping and micro-geographic data extraction from historical sources. Dr. Kappner's publications reveal a consistent focus on how epidemics shape urban development and infrastructure decisions. His research spans multiple disciplines, connecting economic history with public health, urban planning, and spatial economics. A recurring theme across his work is the examination of how cities responded to health crises through infrastructure investments, particularly water and sanitation systems, and how these responses varied based on political, economic, and social factors. His scientific recognition includes: Department-wide teaching prize for best seminar at HU Berlin (2021) Short-listed for university-wide Humboldt teaching prize (2018) Listed first in economics department for teaching excellence (2018) At LMU Munich, Dr. Kappner teaches graduate-level courses in Urban Economics, Advanced Economic History (co-taught with Lukas Rosenberger), and Epidemics in Economic History. He has also been a co-organizer of the annual AGORA Summer School in Philosophy, Politics and Economics since 2016, and was a regular contributor to the Institute for Research in Economic and Fiscal Issues (IREF). His methodological expertise includes spatial data science and the development of algorithms for extracting and referencing historical geographic data, as demonstrated in his work on Berlin city directories.

• Geographic Information Systems (GIS)
• Remote Sensing
• Photogrammetry
• +۵ مورد دیگر

Dr. Gülsüm Çiğdem Çavdaroğlu Akkoç is a full-time Assistant Professor in the Information Technologies Department at Işık University's Faculty of Economics, Administrative and Social Sciences. She holds a multidisciplinary background with degrees in Mathematics Engineering, Geomatics Engineering, and Turkish Language & Literature. Education Ph.D. in Photogrammetry Engineering – Yıldız Technical University (2006–2013) M.S. in Photogrammetry Engineering – Yıldız Technical University (2003–2006) B.S. in Mathematics Engineering – Yıldız Technical University (1998–2003) B.A. in Turkish Language & Literature – Anadolu University (2016–2020) Research Interests Dr. Akkoç's research spans remote sensing , GIS , and machine learning , with applications in environmental monitoring, urban mobility, and health informatics. Her work leverages satellite imagery, mobile data, and AI to address challenges such as wildfire detection, air pollution tracking, and disease diagnosis. She actively integrates spatial data with AI to support smart city development and sustainable resource management. Scientific Awards First Prize – Mobilya Ar-Ge Proje Pazarı (2013), Entrepreneurship Category Supervision & Projects She has supervised four master's theses and led several EU and national projects including: BEE-OPTECH4Honey : Optimizing beekeeping routes using ICT TOP4HoneyChain : A sustainable smart honey value chain platform Open Data Platform for Precision Agriculture Labs & Teams Dr. Akkoç collaborates with interdisciplinary research teams in the fields of AI, geospatial technologies, and agricultural informatics. Her lab activities include developing machine learning models for real-world applications in health, environment, and urban systems.