جست‌وجوی استاد و پژوهشگر

Jason Eisnerمشاهده پروفایل

استاد

• Natural Language Processing
• Speech Processing
• Machine Learning
• +۷ مورد دیگر

Jason Eisner is a Professor in the Department of Computer Science at Johns Hopkins University's Whiting School of Engineering, with a secondary joint appointment in Cognitive Science. He is affiliated with the Center for Language and Speech Processing (CLSP), the Human Language Technology Center of Excellence, and leads JHU's cross-departmental machine learning group. His research focuses on developing probabilistic modeling, inference, and learning techniques for linguistic structure. Eisner has authored over 100 papers in computational linguistics, particularly in parsing, grammar induction, machine translation, computational phonology, computational morphology, and weighted finite-state methods. He is the lead designer of Dyna, a declarative programming language for AI research that allows concise programs backed by efficiency tricks. Eisner's work centers on novel methods in NLP and machine learning, with emphasis on probabilistic modeling and inference in complex, structured settings. His research program combines computer science with statistics and linguistics to create statistical models that capture linguistic structure and develop efficient algorithms for applying these models to data with minimal supervision or through large pre-trained models. As an ACL Fellow, Eisner has made significant contributions to the field. His recent work (2023-2025) shows a strong focus on large language models, semantic parsing, controlled text generation, model interpretability, and privacy-preserving techniques, continuing his long-standing interest in the intersection of probabilistic modeling and linguistic structure. ACL Fellow He teaches courses including Natural Language Processing (601.465/665), Machine Learning: Linguistic and Sequence Modeling (601.765), Declarative Methods (601.325/425/625), and Selected Topics in Natural Language Processing (601.865). His advising focuses on research students through the Argo research group, with emphasis on fundamental research questions in NLP rather than immediate applied engineering.

Gerhard Schwabeمشاهده پروفایل

استاد

• Collaborative Technologies
• Information Management
• E-Government
• +۵ مورد دیگر

Gerhard Schwabe is a Professor in the Department of Informatics at the University of Zurich, Faculty of Business, Economics and Informatics. His research spans collaborative technologies, information management, E-government, blockchain applications, and digital health. He leads the Information Management Research Group and contributes to the university's Digital Society Initiative (DSI). Research Focus: Human-AI collaboration, blockchain systems, crisis informatics, persuasive technologies Key Projects: RefuGPT (refugee support chatbots), Scripted Medicine (health worker assistance), PROMISE (AI prompt orchestration) Technical Expertise: Design Science Research, conversational agents, data-driven governance His recent publications emphasize AI integration in collaborative workflows, blockchain applications for data markets, and digital solutions for crisis management. He explores how generative AI impacts freelance development practices and transforms advisory services through automated systems. Contact: schwabe@ifi.uzh.ch

Alexandre de Spindlerمشاهده پروفایل

استاد

• Conversational Agents
• Generative AI
• Information Systems
• +۸ مورد دیگر

Prof. Dr. Alexandre de Spindler is a Professor of Information Systems at the Zurich University of Applied Sciences (ZHAW) within the School of Management and Law . He co-leads the Center for Information Systems and Technologies and focuses on application development frameworks for conversational interactions with information systems, leveraging multimodal foundation models while enhancing their controllability and reliability. His work extends to improving social skills in digital interactions and teaching agile requirements engineering. University: Zurich University of Applied Sciences School: School of Management and Law Department: Institute of Business Information Technology Academic Rank: Professor His research explores conversational systems , generative AI , and stateful prompt orchestration for complex interactions, particularly in healthcare and financial sectors. Recent work includes frameworks like PROMISE for model-driven prompt management and Science Fiction Prototyping for responsible AI innovation. Teaching contributions span data science programs (BSc, MSc, CAS) covering machine learning, generative AI, and full-stack application validation. He collaborates across disciplines including gerontology and forensic phonetics, with a focus on applying AI to societal challenges.

Xiaojun Caoمشاهده پروفایل

استاد

• Optical Networks
• Wireless Networks
• Network Security
• +۳ مورد دیگر

Dr. Xiaojun Cao is a faculty member at the Andrew Young School of Policy Studies, Georgia State University, specializing in optical and wireless network architectures, protocols, and security. His research addresses challenges in bandwidth scalability, network survivability, and future Internet design through innovations in multi-granular switching, traffic grooming, and cross-layer interactions. B.S., Engineering Physics, Tsinghua University, 1996 M.S., Electrical Engineering, Chinese Academy of Sciences, 1999 Ph.D., Computer Science and Engineering, State University of New York at Buffalo, 2004 His work spans three core areas: Optical Network Optimization : Developing waveband switching frameworks for backbone networks, focusing on multi-layer architectures and performance evaluation. Network Survivability : Designing proactive and reactive strategies for protection and restoration in optical and wireless systems. Edge Network Security : Advancing secure service function chain deployment in multi-vendor and zero-trust environments. Recent research trends highlight his leadership in Network Functions Virtualization (NFV) , Edge Computing , and AI-Driven Networking , with publications on blockchain-based federated learning, prompt chain deployment, and asymmetric protection mechanisms. His work bridges theoretical rigor with practical applications in 5G/6G, UAV networks, and smart infrastructure. Dr. Cao leads a research group exploring optical-wireless convergence and has contributed to foundational studies in network virtualization and traffic management.

• Natural Language Processing
• Artificial Intelligence
• Information Retrieval
• +۷ مورد دیگر

Dr. Rohini K. Srihari is a full Professor and Associate Chair in the Department of Computer Science and Engineering at the University at Buffalo, The State University of New York , and also serves as an Adjunct Professor in the Department of Linguistics within the School of Engineering and Applied Sciences . Her expertise lies at the intersection of natural language processing , artificial intelligence , information retrieval , and AI for social good . Education: PhD in Computer Science, University at Buffalo, 1992 B.Math, University of Waterloo, Canada Research Interests: Dr. Srihari’s research spans a wide range of topics including conversational AI systems (especially empathetic and socially-aware chatbots), disinformation detection and attribution , multilingual text mining for low-resource languages, and predictive analytics for social unrest using heterogeneous data sources. She also explores multimedia information retrieval and AI-driven early warning systems for social and economic disruption. Recent Research Trends: Her recent publications reflect a strong focus on conversational AI and AI for social good , with applications in mental health support, misinformation mitigation, and empathetic dialogue systems. She has led interdisciplinary teams in competitions like the Alexa Prize Socialbot Grand Challenge , where her team won the bronze medal in 2021. Scientific Awards & Recognition: Bronze Prize, Alexa Prize Socialbot Grand Challenge 4 (2021) NSF Grant: Purposeful Conversational Agents based on Hierarchical Knowledge Graphs Holds two US patents in multilingual text mining and face recognition Advising & Funding: Dr. Srihari has supervised numerous PhD and Master's students across departments and has led research funded by NSF , DARPA , IARPA , and the US Government . She has also served as Chief Data Scientist at PeaceTech Lab, leading AI initiatives for conflict prevention. Research Labs & Teams: She directs the Conversational AI for Social Good research group, which focuses on building trustworthy, empathetic, and socially responsible AI systems. The group integrates deep learning, knowledge graphs, and symbolic AI to address real-world societal challenges.

Mateusz Dolataمشاهده پروفایل

استاد

• Human-AI Collaboration
• Digital Transformation of Advisory Services
• AI Ethics and Policy
• +۴ مورد دیگر

PD Dr. Mateusz Dolata is Professor (since 2025) at Zeppelin University, Germany, holding the ZF Endowed Chair of Artificial Intelligence. Concurrently, he continues as a senior researcher in the Department of Informatics at the University of Zurich, Switzerland. His expertise lies at the intersection of human-AI collaboration, sociotechnical systems, and digital transformation of advisory services, with a particular focus on healthcare and finance. Education 2025 – Professor (ZF Endowed Chair of AI), Zeppelin University, Germany 2024 – Venia Legendi (Habilitation) in Informatics, University of Zurich, Switzerland 2018 – Doctor of Science in Informatics, University of Zurich, Switzerland 2012 – Master of Science in Media Informatics, RWTH Aachen University, Germany 2010 – Bachelor of Arts in Computational Linguistics and Philosophy, University of Heidelberg, Germany Research Interests Dolata’s research agenda centers on human-AI collaboration in organizational contexts , spanning ethical AI design, multimodal conversational agents, and service innovation. Recent emphases include: AI-mediated customer feedback management (ReAdvisor project) Human-drone collaboration for emergency response Sociotechnical and algorithmic justice in ride-hailing and finance Digital agents supporting chronic-care patients and community health workers Conversational AI in financial advisory encounters Publication Trends Between 2024 and 2025, Dolata has published prolifically in premier venues such as CHI, ECIS, HICSS, JMIR, and IEEE TSE. Themes converge on designing AI artifacts that mediate human collaboration —whether in large-scale brainstorming, community health, persuasive mobile apps, or crisis informatics. Empirical methods blend design-science research with qualitative field studies, underscoring an integrative sociotechnical lens. Scientific Awards & Service General Conference Co-Chair, ECSCW 2021 Steering Committee & Publicity Co-Chair, EUSSET (since 2019) Associate Editor/Editorial Board Member for MISQ, ISJ, JIT, EJIS, BISE, CSCW journal Reviewing roles for ICIS, ECIS, HICSS, WI, ACM CSCW, CHI, INTERACT, DESRIST Advising & Funding Landscape Dolata has supervised more than 60 bachelor’s and master’s theses on topics ranging from conversational agents in banking to drone-supported emergency response. His projects are supported by Swiss and EU funding streams, including the ReAdvisor, Human-Drone Collaboration, and ComBaCaL initiatives. Active collaborations involve interdisciplinary teams across computer science, medicine, public administration, and finance. Labs & Teams He leads the Human-AI Collaboration research cluster at the University of Zurich’s Department of Informatics, while also directing the AI & Work research group at Zeppelin University. The teams comprise doctoral researchers, post-docs, and industry partners exploring next-generation AI services.

• Machine Learning
• Predictive Analytics
• Computational Astrophysics
• +۳ مورد دیگر

Elena Gavagnin is a Senior Lecturer and Project Leader for Data Science at the ZHAW School of Management and Law's Institute of Business Information Technology. She holds a PhD in Computational Science from the University of Zurich, an MSc in Astrophysics from the University of Bologna, and a BSc in Physics from the same institution. Her work focuses on machine learning, predictive analytics, computational astrophysics, and AI applications in healthcare and technology. Research interests include data science foundations, multimodal AI systems, and radiation hydrodynamics. Notable projects include leading initiatives on AI-driven radiative transfer simulations for the Square Kilometre Array (SKAO), toxicity detection in video games, and webcam-based stroke rehabilitation assessment. Her work bridges astrophysics, healthcare, and information technology. Elena has authored/co-authored over 15 peer-reviewed articles, spanning topics from clinical movement analysis to NLP frameworks and computational astrophysics. Her collaborations include institutions like the University of Zurich and the University of Bologna. She has also contributed to educational initiatives, such as the CAS Higher and Professional Education at ZHAW. Her research emphasizes practical applications of data science, including clinical decision-making tools and ethical AI design. Projects like 'Tele-Assessment' and 'Digital Companion' highlight her focus on real-world healthcare solutions. Ongoing work includes generative deep learning for astrophysical simulations and stateful prompt orchestration in conversational systems.

• Rich Web-based Applications Engineering
• Software Design
• Software Architectures
• +۴ مورد دیگر

Nalaka R. Dissanayake serves as a Senior Lecturer in the School of Computer Science and Engineering at the University of Westminster, where he contributes to the Software Systems Engineering Research Group. With 17 years of academic experience since 2007, he progressed from student instructor to his current senior position while completing his doctoral studies. His foundational education includes a B.Sc. in Information Technology from the Sri Lanka Institute of Information Technology (2007), an M.Phil. from the University of Colombo School of Computing (2017), and a Ph.D. from the University of Westminster (2024). Dr. Dissanayake's research centers on rich web-based applications engineering, where he has established significant contributions through architectural style development and design methodology formalization. His work introduces specialized concepts including RiWAArch Style, BAW-MVC, and delta communication principles that address core challenges in web application state management and communication efficiency. Current research frontiers actively explore prompt engineering techniques for integrating AI/ML capabilities into rich web applications, demonstrating adaptation to emerging technological paradigms while maintaining focus on architectural fundamentals. His publication portfolio reveals a clear research trajectory evolving from AJAX application foundations (2013-2014) through architectural pattern specification (2017-2020) toward comprehensive design methodology development (2023-2024). This progression demonstrates increasing theoretical sophistication while maintaining practical implementation relevance, with consistent output across journals like the Journal of Web Engineering and major conferences including FTC and ICTer. As an active academic contributor, Dr. Dissanayake serves as a reviewer for the Journal of Web Engineering and various conferences. His research group membership provides access to collaborative opportunities within the university's software engineering ecosystem, while his extensive teaching experience across multiple institutions offers valuable mentorship perspective for graduate students.