جست‌وجوی استاد و پژوهشگر

Theresa Zügerمشاهده پروفایل

پژوهشگر

• Artificial Intelligence
• Public Interest AI
• Sustainability
• +۵ مورد دیگر

Dr. Theresa Züger is an interdisciplinary researcher leading the AI & Society Lab at the Alexander von Humboldt Institute for Internet and Society (HIIG). She investigates how AI systems can be designed to serve the common good, focusing on initiatives that promote sustainability, strengthen social inclusion, and enable technology reuse through open systems. Her work addresses societal challenges associated with artificial intelligence at political, social, and cultural levels, contributing to accurate assessment of AI's societal implications. Züger received her Ph.D. in Media Studies from Humboldt University in Berlin in 2017 with her dissertation 'Reload Disobedience,' focusing on digital forms of civil disobedience. Previously, she earned an M.A. in Theatre, Film and Television Studies as well as German and Philosophy from the University of Cologne. She also headed the office responsible for the German government's Third Engagement Report on behalf of the Federal Ministry for Family Affairs, Senior Citizens, Women and Youth (BMFSFJ). Her research centers on Public Interest AI, examining how AI development and deployment can benefit society rather than primarily maximizing profit. Current projects include 'Impact AI' (funded by Volkswagen Foundation), which develops auditing methods to assess AI projects' impact on public interest and sustainability, and 'Human in the Loop,' investigating how automated decision-making processes should be designed for successful human-machine interaction. She previously led the 'Public Interest AI' project, developing a theoretically grounded understanding of public interest AI and creating prototypes like a web accessibility tool and fact-checking application. Analysis of her recent publications reveals a consistent focus on bridging AI technology with societal values. Her work spans technical aspects of AI implementation, ethical considerations, and practical applications that serve public interests. Key trends include human-AI collaboration frameworks, accessibility enhancements, critical examination of AI hype, and theoretical foundations for public interest-oriented AI development. Züger serves as Vice-Chair of the UNESCO Commission on Communication and Information and participates in several juries including the Deep Tech Award, Digital Places – Land of Ideas, and the Civic Innovation Fund. She is also a regular event moderator for organizations like the Berlin-Brandenburg Media Authority, re:publica, and transmediale. As project leader of Impact AI and head of the AI & Society Lab, Züger directs significant research initiatives with funding from organizations like the Volkswagen Foundation. Her work involves extensive collaboration with academic and practical partners across Europe and globally, particularly through projects addressing women in tech and international AI governance. The AI & Society Lab functions as an interdisciplinary interface for new research approaches and knowledge transfer in AI, promoting inclusive, human rights-friendly, and sustainable AI strategies in Europe.

• Natural Language Processing
• Text Normalization
• Named Entity Recognition
• +۵ مورد دیگر

Dilara Torunoğlu Selamet serves as a Lecturer in the Department of Computer Engineering within the Faculty of Computer and Informatics at Istanbul Technical University. Holding a PhD, she specializes in Natural Language Processing for Turkish, with research emphases on social media text normalization, named entity recognition, and sentiment analysis. Her academic credentials feature: PhD in Computer Engineering, Istanbul Technical University (awarded circa 2013) Master of Science in Computer and Information Sciences (Non-thesis), Doğuş University (2009-2013) Bachelor of Science in Computer Engineering, Doğuş University (2004-2009) Dilara's scholarship tackles the complexities of Turkish NLP, a language with rich morphology. She has made notable contributions to text normalization for social media platforms, named entity recognition in authentic datasets, and semantic smoothing techniques for sentiment classification. Her work often bridges theoretical NLP with practical applications, as seen in resource-building projects like the ITU Web Treebank and Turkish sign language corpora. Her publication record (2011-2021) demonstrates methodical growth: initial work on text classification (2011) evolved into named entity recognition (2013) and social media normalization (2014, 2017), then expanded to data augmentation (2020-2021) and sign language processing (2020). This trajectory reflects her commitment to advancing Turkish NLP through both foundational research and innovative resource development. While no specific awards are documented, her research impact is evidenced by an h-index of 4 and over 127 citations in Scopus. Available information does not indicate any students supervised or research grants obtained. She is affiliated with Istanbul Technical University's Department of Computer Engineering, but no laboratory or research team memberships are specified in public profiles.

Maria Sitteمشاهده پروفایل

پژوهشگر

• Art History
• Visual Culture
• Contemporary Art
• +۷ مورد دیگر

Maria Sitte is an art historian and curator currently working as a research assistant at the Offenbach University of Art and Design (HfG Offenbach), where she is pursuing her doctorate on investigative and forensic strategies in contemporary art, with a focus on Forensic Architecture. She is affiliated with the School of Art and Department of Art, contributing to academic and curatorial discourses at the intersection of art, politics, and visual epistemology. Education: Master's degree (Magister) in Art History, Psychology, and History from the University of Trier Maria Sitte's research centers on the visual and rhetorical strategies employed in contemporary artworks that investigate political murders, human rights violations, and socio-political injustices. Drawing from image studies, reception aesthetics, and forensic visualization techniques, her work critically examines how clarity, persuasion, and counter-narratives are constructed through aesthetic means. She explores the ethical and epistemological tensions in the 'forensic turn' in art, especially regarding the risks of manipulation and simplification in visual evidence. Her curatorial practice complements her academic research, with exhibitions such as 'From Today's Perspective. Discourses on the Future' (2021), 'The and' (2020), and 'Talk to Me' (2018/19) reflecting thematic concerns with media, technology, and future imaginaries. Previously, she served as a curatorial assistant at Schirn Kunsthalle Frankfurt, co-curating major exhibitions on socio-political themes. There are no scientific awards mentioned in the provided texts. Advising and Grants: Maria Sitte is supervised by Prof. Dr. Christian Janecke (HfG Offenbach) and Prof. Dr. Ulrike Gehring (University of Trier) for her doctoral research. While no formal advisees or grant funding are listed, her position as a research assistant since 2018 suggests institutional academic support and engagement in research activities. Labs and Research Teams: Though no formal lab or research team is explicitly named, her doctoral project is situated within the academic environment of HfG Offenbach’s Art Department, engaging with interdisciplinary methodologies that include forensic analysis, media studies, and artistic research.

Romain Raveauxمشاهده پروفایل

دانشیار

• Image Analysis
• Machine Learning
• Structural Pattern Recognition
• +۵ مورد دیگر

Romain Raveaux is an Associate Professor at the LIFAT Computer Science Laboratory, University of Tours, affiliated with Polytech Tours. His research focuses on Image Analysis, Machine Learning, Structural Pattern Recognition, Graph Matching, Graph Neural Networks, Discrete Optimization, Reinforcement Learning, and Transfer Learning . Email: romain.raveaux@gmail.com , romain.raveaux@laposte.net Address: 64 av. Jean Portalis, Tours, France, 37200 Phone: +33 (0)2 47 36 14 27 Research Interests Graph Matching and Neural Networks Discrete Optimization for Pattern Recognition Transfer Learning in Graph-Based Models Historical Document Analysis Scientific Trends His recent work bridges Graph Neural Networks with Mixed-Integer Programming , focusing on Image Semantic Segmentation and Graph Cycle Detection . Earlier studies emphasize Genetic Algorithms for graph classification and Graph Edit Distance optimization in pattern recognition.

• Cryptography
• Secure Multiparty Computation (MPC)
• Zero-Knowledge Proofs
• +۳ مورد دیگر

Aarushi Goel is an Assistant Professor of Computer Science at Purdue University's Department of Computer Science, part of the College of Science. She joined the department in Fall 2024 and is affiliated with Purdue's main campus in West Lafayette, Indiana. Her research focuses on cryptographic protocols, with a strong emphasis on secure multiparty computation (MPC), zero-knowledge proofs, and distributed systems security. Her work addresses challenges in privacy-preserving computation, Byzantine fault tolerance, and efficient cryptographic systems. Notable research directions include optimizing MPC protocols for dynamic environments, minimizing communication overhead in distributed systems, and developing practical zero-knowledge proof frameworks. Recent publications explore topics like homomorphic secret sharing, sublinear prover protocols, and Byzantine agreement with polylogarithmic communication complexity. Dr. Goel's contributions often bridge theoretical cryptography with real-world applications, such as secure machine learning training and verifiable computation. Her work has implications for decentralized systems, blockchain technology, and privacy-enhancing technologies. No awards or grants are explicitly listed in the provided materials, but her prolific publication record indicates active engagement in cutting-edge research. She holds no listed advisees or students in the current data. Lab and team affiliations are not specified in the provided text, though her research likely involves collaborations within Purdue's computer science department and external institutions. Her office is located in LWSN 2142D on the Purdue campus.

Chenjuan Guoمشاهده پروفایل

دانشیار

• Machine Learning
• Data Engineering
• Spatio-temporal Data Analysis
• +۴ مورد دیگر

Chenjuan Guo is an Associate Professor at the Department of Computer Science, Aalborg University, within The Technical Faculty of IT and Design. She is affiliated with the Data Engineering, Science and Systems group and the AI for the People initiative, and is part of the Daisy - Center for Data-intensive Systems. Her research focuses on machine learning, data engineering, spatio-temporal data analysis, and time series forecasting. Key projects include the Villum Foundation-funded 'Explainable AI for Complex Microbial Community Interactions and Predictions' (2021-2024) and the Astra project on time series analytics in spatial networks (2018-2021). Her research interests span representation learning, autoencoders, path representation, outlier detection, trajectory data analysis, and time series modeling. She has supervised 3 PhD students and contributed to over 60 publications, with a recent emphasis on transformer-based forecasting, neural architecture search, and continuous learning frameworks for spatio-temporal data. Her work bridges theoretical advancements with practical applications in environmental science, cloud computing, and urban mobility systems. Key achievements include developing frameworks like AutoCTS++ for automated time series forecasting and LightGTS for lightweight models. She actively collaborates internationally, contributing to conferences like ECML PKDD and CVPR. Her research is supported by grants from the Villum Foundation and other institutions.

• Natural Language Processing
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Ahmed AbuRa'ed is a Researcher at the Department of Information and Communication Technologies (DTIC) at Universitat Pompeu Fabra (UPF), Barcelona. He is affiliated with the TALN research group and the Large-Scale Text Understanding Systems Lab. His work focuses on advancing knowledge in scientific text summarization, information extraction, and machine learning. Education: PhD in Computer Science (2020), UPF, Barcelona, Spain M.Sc. in Computer Science (2015), University of Trento, Italy B.Sc. in Computer Information Systems (2007), An-Najah University, Nablus, Palestine Research Interests: Natural Language Processing (NLP), Machine Learning/Deep Learning, Semantic Web, Information Extraction, Data Mining, and Scientific Document Summarization. His projects include developing systems for automatic generation of state-of-the-art reports, scientific text summarization, and cross-document relation discovery. Publications Focus: His 15 most recent articles (2016–2021) emphasize advancements in scientific literature analysis, including citation detection, text simplification, and cross-document summarization. Notable works involve systems like LaSTUS/TALN for scientific text processing and OlloBot for Arabic health dialogue agents. Labs & Teams: Active member of the TALN research group and the Large-Scale Text Understanding Systems Lab at UPF's DTIC department. Open to collaborations in NLP, Machine Learning, and related fields via email or Skype.

Yasir Zakiمشاهده پروفایل

استادیار

• Communication Networks
• Wireless Networks
• Cellular Communication
• +۹ مورد دیگر

Yasir Zaki is an Assistant Professor of Computer Science at New York University Abu Dhabi and a Global Network Assistant Professor at the Courant Institute of Mathematical Sciences, NYU. He leads the Communication Networks Lab, focusing on next-generation communication systems, performance optimization, and digital equity. University: New York University Abu Dhabi School: Courant Institute of Mathematical Sciences Department: Department of Computer Science Academic Rank: Assistant Professor Email: yz48@nyu.edu Dr. Zaki holds an MSc and PhD in Communication and Information Technology from the University of Bremen, graduating with honors. His research centers on communication and wireless networks, cellular systems, congestion control, and enhancing internet access in developing regions. His work bridges theory and real-world impact, especially in digital inclusion and AI's role in education. His recent publications span top venues like PNAS, IEEE TCSS, and ACM IMC, covering topics such as satellite network performance, digital inequality (Lite-Web), AI in education, and Big Tech's global influence. These works reveal a strong trend toward socially impactful computing, network measurement at scale, and algorithmic transparency. Big Tech Dominance Despite Global Mistrust Perception of AI in Education YouTube's Political Bias Lite-Web for Digital Equity Satellite Network Analysis His research has been recognized through high-profile media coverage in Nature and The National , and his PhD student Hazem Ibrahim received the MIT Technology Review Arabia’s Innovators Under 35 MENA 2023 award. This reflects the lab's excellence in computational social science and AI policy. Dr. Zaki mentors students in the Capstone and Research Seminar courses and actively advises PhD and research assistants. He has secured research funding through NYUAD and collaborative projects, enabling field deployments in 56 countries. His lab, the Communication Networks Lab, fosters interdisciplinary work, involving researchers from computer science, social sciences, and policy.

Sandaru Seneviratneمشاهده پروفایل

پژوهشگر ارشد

• Natural Language Processing
• Machine Learning
• Text Simplification and Generation
• +۱ مورد دیگر

Sandaru Seneviratne is a Research Fellow at the School of Computing , The Australian National University , focusing on Natural Language Processing (NLP), Machine Learning, Text Simplification, and Health Informatics. His work bridges advanced language technologies with healthcare applications. PhD in Computer Science, The Australian National University Bachelor of Computer Science and Engineering, University of Moratuwa Research Interests His NLP research emphasizes text simplification frameworks like TextSimplifier and Prompt-based methods for multilingual contexts (e.g., English-Sinhala translation). He investigates factuality error detection in simplified text and lexical substitution techniques for accessibility. In Health Informatics, he contributes to medical term identification using neural networks (CNNs/Transformers), CLEF eHealth evaluations, and diabetes management technologies for teens. Earlier work includes clustering word embeddings for knowledge graphs and restaurant domain information extraction. Publication Trends His publications span 2018–2024, with recent focus on multilingual text simplification, factuality in AI-generated text, and healthcare information retrieval. Technical methods include transformers, triplet networks, and hierarchical clustering, often applied to medical/health domains.

• Self-regulated Learning
• Learning Analytics
• Online Education
• +۴ مورد دیگر

Dr. Jacqueline Wong is an Assistant Professor in the Department of Education and Pedagogy at the Faculty of Social and Behavioural Sciences, Utrecht University. Her academic work focuses on enhancing educational practices through evidence-based research in self-regulated learning and learning analytics, with particular applications in higher education contexts. Dr. Wong earned her Ph.D. (cum laude) from Erasmus University Rotterdam with a thesis entitled "Enhancing Self-Regulated Learning Through Instructional Supports and Learning Analytics in Online Higher Education," which received the Best Thesis Award 2021 from the Erasmus Graduate School of Social Sciences and the Humanities. She completed her Master's degree (cum laude) in Educational Psychology, where she examined the use of movements to support text comprehension. Prior to joining Utrecht University, she was a postdoctoral researcher at Delft University of Technology (2020-2022) working with the Program of Innovation in Mathematics Education (PRIME). Dr. Wong's research program spans several interconnected areas: the application of learning analytics to support self-regulated learning, the design of instructional interventions that promote metacognitive awareness, and the investigation of how emerging technologies like generative AI can enhance educational experiences. Her work frequently examines how technology can be leveraged to support students' metacognitive processes and goal-setting behaviors in both traditional and online educational settings. She has made significant contributions to understanding how conversational agents and learning analytics can provide personalized support for students' self-regulated learning processes. Analysis of her recent publications reveals a clear trajectory toward integrating emerging technologies with established educational theories. Her 2024-2025 work increasingly focuses on the intersection of artificial intelligence and educational psychology, particularly examining how generative AI tools can enhance academic text accessibility and provide adaptive support for learning. She also continues to investigate cognitive aspects of learning in educational games and augmented reality environments, with implications for both educational practice and learning theory development. Among her notable achievements, Dr. Wong received the Best Thesis Award 2021 from the Erasmus Graduate School of Social Sciences and the Humanities. This recognition highlights the significant contribution her doctoral work has made to the field of educational psychology and learning sciences. Her systematic reviews, including examinations of student engagement in mathematics education and gamification in MOOCs, have provided valuable syntheses of research in growing areas of educational technology. Dr. Wong has been an active research member of the Leiden-Delft-Erasmus Centre for Learning and Education (LDE-CEL) and the network for Self-Regulated Learning in Digitalised Schools (SeReLeDiS). Her collaborative approach to research is evident in her extensive co-authorship network across multiple institutions. Before joining Utrecht University, she worked with lecturers to promote student motivation and self-regulated learning in blended service mathematics courses and examined the effectiveness of technology tools for learning mathematics. Dr. Wong's work bridges theoretical frameworks with practical implementations, often involving close partnerships with educators to ensure research relevance to real-world classroom challenges. Her current research appears to be moving toward deeper integration of AI technologies with educational theory, particularly examining how generative AI can support metacognitive processes and self-regulated learning across diverse educational contexts.

Zheng Yuanمشاهده پروفایل

مدرس ارشد

• Educational Technology
• Language Acquisition
• Multilingual NLP
• +۳ مورد دیگر

Dr. Zheng Yuan is a Senior Lecturer (Associate Professor) in Natural Language Processing at the School of Computer Science, University of Sheffield. He holds affiliated positions at the University of Cambridge and King's College London, and is a Fellow of Trinity College, Cambridge. His research focuses on NLP applications in education, healthcare, and multilingual systems. Education: PhD in Natural Language Processing, University of Cambridge MPhil in Advanced Computer Science, University of Cambridge BSc(Eng) from Queen Mary University of London Research: Dr. Yuan's work spans educational NLP, multilingual systems under low-resource conditions, and explainable machine learning. His group develops technologies for grammatical error correction, automated assessment, and cross-lingual applications, with significant contributions to computer-assisted language learning and computational creativity. Publications: Recent works (2023-2025) demonstrate strong focus on educational NLP, multilingual systems, and LLM evaluation. Key themes include grammatical error correction for code-switched languages, creativity assessment frameworks, and robust evaluation methods for large language models across diverse linguistic contexts. Awards: Winning systems at SemEval-2021 and CoNLL-2014 Fellowship at Trinity College Cambridge Fellow of Higher Education Academy Grants & Advising: Principal Investigator for Royal Society grant 'Large Language Models as Agents for Intelligent Language Tutoring' (2025-2027). Actively supervises PhD students in NLP and machine learning, welcoming new research collaborations. Affiliations: Member of Alan Turing Institute (Data-Centric Engineering), King's Institute for AI, and ACL committees. Organizes major NLP workshops including ACL/NAACL BEA workshops and AIED tutorials.

Juan Jiménez-Salcedoمشاهده پروفایل

استاد

• Intercultural Education
• French Studies
• Gender Studies
• +۱۰ مورد دیگر

Dr. Juan Jiménez-Salcedo is a Professor at Universidad Pablo de Olavide in the Department of Philology and Translation , with a focus on French Philology . He is also affiliated with the Université de Mons (Faculté de traduction et d'interprétation). Research Pillars : Postmonolingualism and intercultural education Linguistic policy analysis in Colombia, the EU, and Catalonia Legal translation and judicial bilingualism Gender studies in historical and modern contexts Key Publications : 2021: Investigated Colombian bilingual education policies 2020: Analyzed EU multilingualism and Catalan-Spanish legal conflicts 2019: Explored Catalan language desterritorialization 2018-2017: Co-edited volumes on postmonolingual translation justice Methodological Contributions : Applied sociocritical paradigms to language policy analysis Developed mixed-methods approaches for courtroom interpreting quality His work bridges jurilinguistics , gender studies , and microterritory language dynamics , emphasizing ethical translation practices in multicultural legal systems.

• Technology-Enhanced Learning
• Learning Analytics
• Artificial Intelligence in Education
• +۵ مورد دیگر

Olga Viberg is an Associate Professor at KTH Royal Institute of Technology, specializing in Technology-Enhanced Learning within the Division of Media Technology and Interaction Design at the School of Electrical Engineering and Computer Science. With a PhD in Informatics from Örebro University (2015), she brings extensive experience from Dalarna University (2008-2016) as a lecturer in Media Technology and Learning Sciences. Current roles: Associate Professor, Docent, Course Coordinator Key research areas: AI in Education, Learning Analytics, Privacy & Ethics Leadership roles: Editor-in-Chief of International Journal of Learning Analytics , Vice-President of SoLAR Research Focus : Viberg's work bridges AI, learning analytics, and educational design through value-sensitive approaches. Her studies address: Privacy concerns in learning analytics Cultural alignment of AI systems Self-regulated learning frameworks Trust dynamics in AI adoption Responsible data practices in education Generative AI applications in assessment Scientific Contributions : Recognized through: 2024 Google Academic Research Award Multiple conference recognitions (LAK'24, LAK'23) Leadership in international initiatives like UNESCO's online education policy Educational Impact : Directly shaping academic programs through: Coordination of Bachelor's course in Media Technology Teaching PhD courses in Learning Analytics Organizing Nordic Learning Analytics Summer Institute

Thomas Krebsمشاهده پروفایل

دانشیار

• Commercial Law
• Contract Law
• Agency Law
• +۴ مورد دیگر

Thomas Krebs is an Associate Professor of Commercial Law at the University of Oxford and a Tutorial Fellow in Law at Brasenose College. He holds roles as Mooting Co-ordinator and Associate Dean for External Relations. His research focuses on commercial law, contract law, agency law, and restitution, with particular attention to comparative legal systems and international harmonization efforts. Krebs has published extensively on topics including agency principles in international commercial contracts, restitution theories, and cross-jurisdictional legal comparisons. His work often bridges English and German legal frameworks, contributing to debates in European contract law. His academic output includes monographs like Restitution at the Crossroads: A Comparative Study (2001), numerous book chapters analyzing agency law, and articles in journals such as the Lloyds Maritime and Commercial Law Quarterly . Krebs is actively involved in the Commercial Law Centre and contributes to legal education through mooting programs. His research interests span contract formation, unjust enrichment, and the application of international commercial principles. Krebs’ publications demonstrate a focus on doctrinal clarity and practical implications of legal frameworks, particularly in agency law and restitution. He has reviewed major texts on agency law and contributed to edited volumes addressing European contract harmonization and comparative legal studies.

• Microchannel Engineering
• Proton Exchange Membrane Fuel Cell
• Two-phase Flow
• +۷ مورد دیگر

Eon Soo Lee is an Associate Professor in the Department of Mechanical and Industrial Engineering at the New Jersey Institute of Technology (NJIT). His primary research focuses on advanced materials engineering, biomedical microfluidics, and assistive technologies for individuals with disabilities. He has led federally funded projects including 'I-Corps: Multiplex Diagnostic Assay Using Interdigitated Nano-Sensing Technology' (NSF, 2023-2025) and 'Innovative Nano Catalysts for Automobile and Fuel Cell Applications' (NSF, 2018). Research Interests: Lee's work spans interdisciplinary areas including: Development of N-doped graphene/MOF composites for energy applications Microfluidic systems for blood plasma separation and antigen detection Design of accessible technologies for visually impaired users, including VR audio descriptions and remote sighted assistance systems Grants and Projects (select): National Science Foundation (2023): $500K for multiplex diagnostic assays National Science Foundation (2018): $300K for nano-catalysts in fuel cells Multiyear collaborations with industry partners on biosensor integration Innovation Highlights: Developed AIGuide: AR hand-guidance system for visual impairments Pioneered omnidirectional audio descriptions for VR music performances Published extensively in Carbon , Biomicrofluidics , and ACM/IEEE accessibility venues