جست‌وجوی استاد و پژوهشگر

• Blockchain Technology
• Distributed Systems
• Cybersecurity
• +۳ مورد دیگر

Aad P. A. van Moorsel is a faculty member at the School of Computing Science, University of Newcastle , with a focus on blockchain technology, cybersecurity, and privacy-preserving machine learning systems. His work bridges theoretical analysis with practical implementations in decentralized systems and financial technologies. Research Interests : Blockchain systems, smart contract security, federated learning, verifiable fairness in AI, and privacy-preserving technologies. Key Contributions : Development of the BlockSim simulation framework for blockchain, quantitative analysis of Ethereum's verifier dilemma, and frameworks for fairness-as-a-service in machine learning. Collaborations : Regularly works with researchers in cybersecurity (e.g., Mhairi Aitken, Ehsan Toreini), financial technology (e.g., Karen Elliott, Kovila Coopamootoo), and distributed systems (e.g., Han Wu, Lydia Chen). Publications : Over 170 works since 1992, with recent emphasis on blockchain scalability, AI ethics, and secure financial services. Tools : Co-designed OpBench for Ethereum opcode benchmarking and ADaCS for analyzing data collection strategies in security contexts.

Philipp Cimianoمشاهده پروفایل

استاد

• Knowledge Representation
• Ontologies
• Knowledge-Based Natural Language Processing
• +۶ مورد دیگر

Philipp Cimiano is a Professor at the Faculty of Engineering, Bielefeld University, and leads the Semantic Databases Group. He holds additional roles as Coordinator of the Cognitive Interaction Technology Center (CITEC) and Director of the Joint Artificial Intelligence Institute (JAII). His research focuses on the intersection of language, semantics, and knowledge representation, with applications in Explainable AI , Knowledge Graphs , and AI in Medicine . Education: University of Stuttgart, University of South Australia, Karlsruhe Institute of Technology (KIT) Key Research Areas: Knowledge Representation, Ontologies, Explainable AI, Clinical Decision Support His recent work emphasizes dialogue-based XAI , federated learning , and semantic data integration . He has secured funding from the German Research Foundation (DFG) and the European Union for projects like TRR 318 "Constructing Explainability" and Pret-a-LLOD. Scientific Awards Carl Adam Petrie Prize, KIT Faculty of Business and Economics Editorial Roles Co-editor, Journal of Applied Ontology Area Editor, Semantic Web Journal Editorial Board, Journal of Web Semantics Notable Projects TRR 318 (Subprojects B01, C05, INF) 3B: Bots Building Bridges for online deliberation LLM4KMU: Open Source LLMs for SMEs

Simon Kranzerمشاهده پروفایل

مدرس ارشد

• Knowledge Transfer
• Cognitive Manufacturing
• Digital Twins
• +۷ مورد دیگر

Simon Kranzer is a Senior Lecturer and Head of Research Group at the Department of Information Technologies and Digitalisation, FH Salzburg. His work bridges academic research and practical application in digital transformation. Location: Campus Urstein, Room 425 Contact: simon.kranzer@fh-salzburg.ac.at | +43-50-2211-1316 Research Focus: Digital Twins for industrial systems Collaborative Robotics (Co-Bots) in retail Knowledge Transfer between academia and industry Operational Technology (OT) Security Data Acquisition and Visualization Programming Language Applications in industrial contexts Research Trends: Recent publications show expertise in retail automation (service robots, customer behavior analysis), industrial digital twins, and OT security. Earlier work spans GIS-SCADA integration, medical software implementation, and 3D microstructure analysis. Collaborative Projects: Active in interdisciplinary living labs, smart factory bootcamps, and 5G-based robotics exploration.

Luca Maria Aielloمشاهده پروفایل

استاد

• Data Science
• Computational Social Science
• Social Media
• +۷ مورد دیگر

Luca Maria Aiello is a Professor and Data Science Research Group Leader at the IT University of Copenhagen 's Department of Digital Design. He heads the education program for the Master of Data Science degree while co-leading the Networks, Data, and Society research group. His research spans computational social science , social media analysis , and network science , with recent focus on: Urban social connectivity patterns Sleep quality and social dimensions Financial collective action on Reddit COVID-19 pandemic's impact on dreaming Climate change discourse on TikTok Current research projects include COCOONS (Collective Coordination through Online Social Media) funded by the Carlsberg Foundation (2023-2025), and multiple grants for the International Conference on Computational Social Science (IC2S2) from Danish Data Science Academy and Otto Mønsteds Fond. Dr. Aiello has received significant recognition including the 2022 Research Environment of the Year award, with his work being covered by 16 news outlets , 47 X (Twitter) users , and 3 Facebook pages .

Christian Meskeمشاهده پروفایل

استاد

• Socio-technical Systems
• Artificial Intelligence
• Digital Transformation
• +۷ مورد دیگر

Prof. Dr. Christian Meske is a faculty member at Ruhr University Bochum , holding the Chair of Socio-technical System Design and Artificial Intelligence since September 2021. He previously served as an Assistant Professor at Freie Universität Berlin (2017–2021) and conducted postdoctoral research at the University of Duisburg-Essen (2015–2017) and University of Münster (2012–2015). Education: Diploma in Business Administration (Diplom-Kaufmann), University of Potsdam His research focuses on the intersection of Artificial Intelligence , socio-technical systems , and digital transformation . Key areas include Explainable AI , Digital Twins , AI Governance , and Human-AI Interaction . His recent publications analyze algorithmic transparency, digital nudging, and affordance theory in AI systems. Notable trends in his work include: Foundational AI models and their ethical implications Relational quality in social networks Feedback mechanisms in mobile health applications Philosophical perspectives on digital twin perception Design principles for AI-based decision support Scientific accolades include: Best Paper Award at ICAART (2022) ICIS Best Short Paper in Health IS (2020) AIS Best Information Systems Publication of the Year (2016) Elite Award for Excellence (European University Information Systems, 2015) He has contributed to projects like sciebo – the Campuscloud for NRW and supervised student initiatives such as 'Mobile Learning.' Meske is an active member of the Association for Information Systems , German Informatics Society , and other academic bodies, focusing on computer-supported cooperative work and digital ethics.

Rachael Graham Lussosمشاهده پروفایل

مدرس

• Medical Rhetoric
• Health Communication
• Proposal Writing
• +۴ مورد دیگر

Rachael Graham Lussos is a Lecturer in the Department of English at George Mason University, specializing in medical rhetoric, health communication, and multimodal composition. Her work bridges technical writing pedagogy with advocacy, focusing on quantification practices in chronic pain discourse, sexual assault reporting, and digital activism. PhD in Writing and Rhetoric, George Mason University MFA in Creative Writing, George Mason University Graduate Certificate in Professional Writing & Rhetoric, George Mason University Lussos’s research examines how data visualization and statistical narratives shape public understanding of complex issues. She explores the rhetorical agency of Twitter bots in social justice movements and analyzes institutional communication around campus sexual assault. Her scholarship spans interdisciplinary fields including medical humanities, digital rhetoric, and technical communication. Notable contributions include studies on opioid crisis discourse, kairotic timing in healthcare, and ethical implications of drug testing protocols. Doctoral Dissertation Research Improvement Grant, National Science Foundation (2019) Lussos has taught courses on proposal writing, digital writing assignments, and multilingual composition. Her work integrates computational methods with rhetorical theory, challenging traditional frameworks in both healthcare and pedagogical contexts.

Lisovenko Iryna Dmytrivnaمشاهده پروفایل

استادیار

• Parallel and Distributed Computing
• GPU Computing
• Automatic Program Parallelization
• +۳ مورد دیگر

Lisovenko Iryna Dmytrivna serves as Assistant Professor in the Department of Computer Systems and Networks at Yuriy Fedkovych Chernivtsi National University since 2002, following her 2000 diploma in Computer Systems and Networks from the same institution. Her professional trajectory includes software engineering at a municipal medical institution (2000–2002) and ongoing contractual collaboration with Elogic Commerce since 2018. Her academic credentials include: Yuriy Fedkovych Chernivtsi State University, Faculty of Physics, Department of Computer Science, specialty "Computer Systems and Networks" (2000) Dr. Lisovenko's research centers on parallel and distributed computing, emphasizing automatic parallelization techniques, GPU-accelerated non-graphical computing, and structural analysis of program intermediate representations. She concurrently investigates specialized computer systems for data stream processing and develops methodologies for enterprise accounting automation, bridging theoretical computer science with business process optimization. Her scholarly output demonstrates sustained innovation in high-performance computing architectures. Analysis of her 15 most recent publications (2012–2021) reveals three dominant research thrusts: GPU-based parallelization (40% of works, including Kalyna encryption and bitonic sorting implementations), algorithmic optimization for diverse hardware (33%, covering sorting networks and structural matrices), and applied systems for real-world problems (27%, spanning smart home control, social media analysis, and enterprise automation). This evolution reflects increasing focus on practical GPU applications while maintaining core expertise in parallel algorithm design. She actively contributes to academic development through teaching Parallel and Distributed Computing, Economic and Legal Aspects of Enterprise Automation, and DevOps/DevNet courses, while authoring 12+ methodological manuals including "Parallel and Distributed Computing: Laboratory Workshop" (2022) and "System Administration of Linux OS" (2021). Her professional development includes certifications in Constitutional Law, Finance and Investment, DevNet Associate, and All Digital Week initiatives (2020–2021).

Gregor Wiedemannمشاهده پروفایل

پژوهشگر

• Natural Language Processing
• Text Mining
• Computational Social Science
• +۵ مورد دیگر

Dr. Gregor Wiedemann serves as a Senior Researcher in Computational Social Science at the Leibniz Institute for Media Research (Hans Bredow Institute) since September 2020, co-heading the Media Research Methods Lab (MRML) with Sascha Hölig. His work bridges computer science and social sciences through methodological innovation in empirical media research. Wiedemann holds a doctorate in computer science from Leipzig University (2016), where his dissertation focused on automating discourse analysis using text mining and machine learning. His educational background combines political science and computer science studies at Leipzig University and the University of Miami, followed by postdoctoral work in Language Technology at the University of Hamburg under Prof. Chris Biemann. His research centers on natural language processing and text mining applications for social and media analysis, with significant contributions in hate speech detection, argument mining, and cross-platform misinformation tracking. Recent work demonstrates a strategic shift toward building research infrastructures for sensitive data handling, including the Community Data Trust model for extremism research and the Social Media Observatory open-science platform. His methodology development specifically targets unsupervised information extraction from large document corpora to support investigative journalism and social science inquiry. Wiedemann's publication trends reveal deepening specialization in computational infrastructure development, with 7 of his 11 most recent works (2024-2025) focusing on data trust frameworks, cross-platform methodologies, and AI-driven analysis systems. His projects consistently intersect computational linguistics with pressing social issues including election integrity, climate discourse, and child safety in digital spaces. He has secured major funding through the German Research Foundation (DFG) for the FAME project on argument mining and evaluation, and leads collaborative initiatives including NOTORIOUS (mis- and disinformation tracking) and ComAI (communicative AI impact studies). His work with state media authorities on family influencing content demonstrates applied policy relevance. As co-director of the Media Research Methods Lab, Wiedemann oversees a dynamic team developing cutting-edge computational approaches for media analysis. The lab functions as an interdisciplinary hub connecting computer scientists with social researchers, with current projects spanning TikTok political campaigning analysis, right-wing extremism data infrastructure, and ethical AI applications in public discourse monitoring.

H. Andrew Schwartzمشاهده پروفایل

استادیار

• Large and scalable language analyses
• Psychological and health discovery
• Computational social science
• +۶ مورد دیگر

H. Andrew Schwartz is an Assistant Professor at Stony Brook University's Department of Computer Science. His research bridges computational social science, natural language processing, and psychological discovery, focusing on social media language analysis for health and demographic insights. Education : PhD in Computer Science (2011) from the University of Central Florida Past Affiliations : Postdoctoral Research Fellow and Visiting Assistant Professor at University of Pennsylvania's Computer & Information Science department Current Role : Lead Research Scientist for the World Well-Being Project, a multidisciplinary collaboration between computer scientists and psychologists Dr. Schwartz's research utilizes machine learning to analyze large-scale social media data for mental and physical health prediction, automatic lexicon refinement, and measuring human temporal orientation. His work has been recognized by Almetric's top 25 most discussed research papers in 2013. Recent publications examine psychological state detection through NLP, including PTSD analysis, mental health screening algorithms, and LLM adaptation for personality modeling. He develops methodologies like adaptive question-asking systems and self-supervised learning frameworks for behavioral analysis. Key scientific contributions include: Developing the WWBP-SQT-lite system for identifying mental health change moments Creating AlBA (Adaptive Language-Based Assessments) for mental health evaluation Advancing temporal analysis of social media language for health informatics

Bastien Perroyمشاهده پروفایل

پژوهشگر

• Cognitive Science
• Natural Language Processing (NLP)
• Social Media Analysis
• +۶ مورد دیگر

Bastien Perroy is an Industrial Cognitive Science Researcher based in Paris, France, leading the Passenger Cognition Lab at the RATP Group – the operator of 10 million daily public transport trips in Paris. He holds a Ph.D. in cognitive science from École des Hautes Études en Sciences Sociales (EHESS), completed at ENS Ulm's Institut Jean-Nicod Department of Cognitive Studies, where he continues to collaborate. Education: Ph.D. in Cognitive Science from EHESS His research bridges cognitive science and urban mobility, focusing on passenger perception, temporal disorientation, and crisis-induced cognitive disruptions. Key projects include: Developing a zero-cost, real-time social media bot questionnaire system for passenger sentiment analysis Engineering a 30 million tweet dataset using Spacy, CamemBERT, and GPT-4 for NLP analysis Conducting distress analysis during the Line 4 incident (2023) to improve service recovery Creating a psychometric instrument mapping 63 key messages across 9 clarity dimensions Investigating non-spatial disorientation during the pandemic through multi-method research His work has resulted in publications across diverse journals including Nature Scientific Reports , PLOS One , and the British Journal of Psychology . He emphasizes actionable insights for customer service, operational audits, and policy development, particularly through: Statistical models doubling disruption recovery time estimation precision Real-time KPI dashboards for executive decision-making Policy recommendations focused on social disorientation mitigation Currently seeking collaborations, conferences, and new projects in cognitive science and transportation psychology.

Rebekah Overdorfمشاهده پروفایل

استاد پژوهشی

• Computer Security
• Privacy
• Information Integrity
• +۷ مورد دیگر

Rebekah Overdorf is a Research Professor and Chair for Security and Trustworthiness of Online Information at Ruhr University Bochum, where she leads research at the intersection of computer security, privacy, and information integrity. She is also affiliated with the Research Center for Trustworthy Data Science and Security. Her research focuses on identifying and mitigating threats to information integrity in online platforms, with particular expertise in detecting disinformation campaigns, analyzing propaganda distribution channels, and developing methods to protect user privacy. Overdorf's work combines data science and machine learning approaches with security expertise to address contemporary challenges in online information ecosystems. Analysis of her recent publications reveals a consistent focus on security and privacy challenges in social media environments, with particular attention to Telegram and Twitter platforms. Her research spans technical analysis of bot networks and propaganda distribution mechanisms, development of detection methodologies for disinformation campaigns, and creation of protective technologies that empower users against algorithmic manipulation. Over the past decade, her work has evolved from foundational research in stylometry and authorship attribution to more applied security challenges in contemporary social media ecosystems. Professor Overdorf has received recognition through publications in top security and social media conferences including USENIX Security, ICWSM, EuroS&P, and FAT*. Her collaborative research approach is evident in her extensive co-authorship network spanning multiple institutions across Europe and North America. Her advising and research activities focus on training the next generation of security researchers while developing practical solutions to pressing information integrity challenges. Through her leadership of the Chair for Security and Trustworthiness of Online Information, she oversees research projects that address real-world security threats while maintaining academic rigor. The Chair for Security and Trustworthiness of Online Information serves as a hub for interdisciplinary research, bringing together computer scientists, social scientists, and policy experts to develop comprehensive approaches to online security challenges. Current projects focus on detecting coordinated inauthentic behavior, analyzing state-sponsored disinformation campaigns, and developing privacy-aware technologies that maintain functionality while protecting user data.

Line Henriksenمشاهده پروفایل

مدرس

• Monster Theory
• Hauntology
• Creative Writing
• +۴ مورد دیگر

Line Henriksen is a Lecturer in Literature and Creative Writing at Malmö University's Faculty of Culture and Society, Department of Art, Culture and Communication. She holds a PhD in Gender Research from Linköping University and is affiliated with the MEDEA Lab and The Monster Lab research groups. Her research explores: Monster theory and cultural representations of horror Hauntology and temporal studies Creative writing as methodological practice Digital ethics and bot communication Feminist posthumanism and speculative fiction Through artistic research approaches, she examines intersections of gender, technology, and cultural narratives. Recent publications demonstrate interdisciplinary engagement across gender studies, digital humanities, and literary theory, with consistent focus on ethical dimensions of human/non-human relationships. Her 2024 co-authored book examines feminist reconceptualizations of alien encounters. At MEDEA Lab, she contributes to multidisciplinary projects addressing societal challenges through experimental media approaches. Her work with The Monster Lab investigates cultural manifestations of monstrosity in contemporary media landscapes.

Vijay Magoمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Machine Learning
• Natural Language Processing
• +۵ مورد دیگر

Vijay Mago is Chair and Associate Professor of Computer Science at Lakehead University, Canada, and Associate Professor at York University's School of Health Policy and Management since 2015. He holds a Ph.D. in Computer Science from Panjab University, India (2010). Education: Ph.D. in Computer Science, Panjab University, India (2010) His research integrates artificial intelligence, machine learning, and natural language processing to address complex societal challenges including homelessness, obesity, and crime through health informatics, medical decision support, and Bayesian intelligence. Current work emphasizes modeling complex health systems and social networks using big data analytics. Recent publications reveal strong interdisciplinary trends applying AI to public health crises (notably COVID-19 modeling) and political/social media analysis, with consistent focus on ethical considerations, system resilience, and narrative shaping in digital environments. Dr. Mago serves as Associate Editor for IEEE Access and BMC Medical Informatics and Decision Making, demonstrating significant editorial contributions to his fields. He previously contributed to the Modeling of Complex Social Systems Program at Simon Fraser University's IRMACS Centre starting in 2011, establishing foundational work for his current research trajectory.

• Lung pathology
• Pulmonary fibrosis
• Lung cancer
• +۷ مورد دیگر

Robert Homer, MD, PhD is Professor of Pathology and of Medicine (Pulmonary) at Yale School of Medicine, where he serves as Director of Medical Studies for Anatomic Pathology and Director of Medical Education for Pathology. He previously served as lead thoracic pathologist at Yale from 2004 to 2022 and Director of Anatomic Pathology at VA Connecticut HealthCare system from 1994 to 2022. His institutional affiliations include multiple Yale centers and programs such as the Cancer Signaling Networks, Center for Thoracic Cancers, Interstitial Lung Disease Program, and Pulmonary, Critical Care & Sleep Medicine. Dr. Homer's research focuses on the pathology of neoplastic and inflammatory lung diseases, with particular expertise in pulmonary fibrosis and lung cancer mechanisms. His work bridges basic science and clinical pathology, utilizing both human tissue analysis and murine models of lung disease. He has recently become interested in applying Large Language Models to medical education, reflecting his dual commitment to pathology research and pedagogy. Analysis of Dr. Homer's recent publications (2022-2025) reveals a strong focus on lung cancer genomics, tumor evolution mechanisms, and the molecular basis of pulmonary fibrosis. His work frequently appears in high-impact journals including Nature, Nature Communications, and Cancer Discovery, demonstrating significant contributions to understanding lung disease pathogenesis and developing improved diagnostic approaches. Keynote address for Pulmonary Pathology Society (2009) Dr. Homer maintains an active research program despite being in phased retirement, with numerous publications through 2025. He serves as an editorial board member for the American Journal of Pathology and has presented on innovative approaches to medical education, including 'From Bots to Docs, Harnessing AI in the medical education journey' (2023). His clinical expertise in thoracic pathology continues to inform both his research and teaching activities at Yale.

Salla-Maaria Laaksonenمشاهده پروفایل

استاد مدعو

• Communication
• Technology
• Social Media
• +۸ مورد دیگر

Salla-Maaria Laaksonen is an Adjunct Professor and Senior Researcher at the University of Helsinki's Faculty of Social Sciences, affiliated with the Department of Social Research and Centre for Consumer Society Research. She holds a Dr.Soc.Sc. (2017) and M.Soc.Sc (2008) from the same institution. Her current positions include Postdoctoral Researcher and Grant Researcher roles at University of Helsinki, along with an affiliation at Vrije Universiteit Amsterdam since 2021. Her research examines digital communication transformations in the platform society, focusing on: Platform-driven changes in public communication flows and business-society relationships Intersections of organizing, data practices, and machine learning methods Critical analysis of datafication's societal impacts Application of computational methods to hybrid media systems She leads projects exploring AI ethics, misinformation governance, organizational communication, and social media analytics. Recent publications (2021-2025) cluster around three themes: Platform governance : Studies on content moderation, corporate responsibility, and AI's societal impact Datafied communication : Research on social media discourse, organizational rhetoric, and computational methods Digital transformations : Analyses of media ecosystems, political communication, and technology adoption She directs research at the Centre for Consumer Society Research , focusing on digital society challenges. Her work has appeared in journals including New Media & Society , Journal of Computer-Mediated Communication , and Information, Communication & Society .