جست‌وجوی استاد و پژوهشگر

Doris Burgerمشاهده پروفایل

مدرس ارشد

• Knowledge Management
• Innovation Management
• Knowledge Transfer
• +۳ مورد دیگر

Mag. Dr. Doris Burger is a Senior Lecturer and Program Director at the Center for Business Specializations within the University for Continuing Education Krems. She leads the "International Business, Operations & Aviation" expertise area and oversees executive education programs such as the Executive MBA, MBA Aviation Management, and MBA International Business. Education: Master's (Mag.) in Business Administration from WU Wien Doctorate (Dr.) in Social and Economic Sciences from WU Wien's Institute for Business Administration and Information Management Research Focus: Her work centers on knowledge transfer mechanisms , innovation management , and environmental management in aviation contexts . She explores how computer-based systems enhance organizational learning and knowledge generation through expert-driven methodologies. Teaching: She teaches "Knowledge Management and Innovation" in both online and campus formats. Professional Contributions: Develops corporate programs for international clients in her areas of expertise Authored a monograph on computer-based knowledge transfer (2011) Supervised master's research on environmental management in Austrian air transport Labs/Teams: Operates within the Center for Business Specializations , collaborating on executive education and industry partnerships.

Manxi Wuمشاهده پروفایل

استادیار

• Societal Networks
• Game Theory
• Network Optimization
• +۴ مورد دیگر

Manxi Wu is an Assistant Professor in Cornell University's School of Operations Research and Information Engineering, specializing in societal networks and game-theoretic approaches to system design. Her research develops computational models for strategic learning and incentive mechanisms in socio-technical systems, with applications to transportation networks and digital platforms. Education: B.S. Applied Mathematics, Peking University (2015) M.S. Transportation, Massachusetts Institute of Technology (2017) Ph.D. Social and Engineering Systems, Massachusetts Institute of Technology (2021) Her research integrates game theory, optimization, and machine learning to address challenges in autonomous services, traffic management, and decentralized decision-making. Current investigations focus on adaptive incentive structures, spatial resource allocation, and equilibrium analysis in complex networked environments. Publication analysis reveals consistent emphasis on game-theoretic frameworks applied to urban mobility systems, with recent work exploring multi-agent reinforcement learning, congestion pricing equity, and electric fleet management. Methodological innovations include novel convergence proofs for decentralized algorithms and computational approaches to fairness constraints. Awards and Honors: Hammer Fellowship UTC Milton Pikarsky Memorial Award Siebel Scholarship EECS Rising Star recognition No information is currently available regarding student advising, research grants, or laboratory affiliations.

Trevor W. Haytonمشاهده پروفایل

استاد

• Actinide Chemistry
• Inorganic Chemistry
• Organometallic Chemistry
• +۶ مورد دیگر

Professor Trevor W. Hayton is a faculty member in the Department of Chemistry and Biochemistry at the University of California, Santa Barbara. He leads the Hayton Research Group, which focuses on solving problems in energy science, nanochemistry, and nuclear fuel clean-up through the synthesis and characterization of transition metal, lanthanide, and actinide complexes, as well as metal nanoclusters. Dr. Hayton's research spans several key areas in inorganic and organometallic chemistry: Actinide chemistry, particularly uranium and thorium complexes Synthesis of transition metal nanoclusters Molecular activation of small molecules Investigation of metal-ligand bonding and covalency Energy-related materials and processes Analysis of Professor Hayton's recent publications (2023-2025) reveals a strong focus on actinide chemistry, particularly uranium and thorium complexes with various ligands. His group has made significant contributions to understanding actinide-ligand bonding, especially through NMR spectroscopy. They also continue to advance the field of transition metal nanoclusters, with recent work on nickel, copper, and iron systems. A notable trend is the increasing use of advanced spectroscopic and computational methods to probe electronic structure. Professor Hayton mentors numerous graduate students and postdoctoral researchers, as evidenced by successful PhD defenses and award-winning research presentations. His group members learn advanced synthetic techniques including air-free procedures, and various spectroscopic and analytical methods. The Hayton Research Group operates state-of-the-art laboratories at UCSB, with dedicated spaces for air-sensitive synthesis and characterization. Group meetings are held weekly to discuss ongoing research and foster collaboration among members.

Ed Hopkinsمشاهده پروفایل

استاد

• Game Theory
• Microeconomic Theory
• Behavioral Economics
• +۶ مورد دیگر

Ed Hopkins is a Professor of Economics at King's College London and the Interim Head of the Economics Department within the King’s Business School. He holds a PhD from the European University Institute in Florence, Italy, and has held positions at the University of Edinburgh and as a visiting scholar at institutions including the California Institute of Technology and the University of British Columbia. His research focuses on game theory, behavioral economics, and social economics, with particular emphasis on topics such as tournament models, inequality, learning dynamics, and experimental economics. Key areas of interest include status concerns, marriage matching, and the implications of non-standard preferences in strategic interactions. Ed has contributed extensively to experimental economics, testing theoretical predictions in laboratory settings. He is actively involved in PhD supervision, accepting students for doctoral research. His work spans theoretical and empirical analyses, with notable contributions to understanding cyclical behavior in strategic situations, the role of information in decision-making, and the interplay between economic inequality and risk-taking.

• Medical Education
• Pediatrics
• Curriculum Development
• +۵ مورد دیگر

Donna D. Elliott, MD, EdD, is a Professor of Clinical Pediatrics and Medical Education at the Keck School of Medicine of the University of Southern California (USC). She holds dual leadership roles as Vice Dean for Medical Education and Chair of the Department of Medical Education. Dr. Elliott oversees all aspects of medical student education, including pathway programs and graduate-level academic medicine and narrative medicine programs. She has been recognized with prestigious awards such as the Mellon Award for Excellence in Mentoring and the USC Master Teacher designation. Her research focuses on medical education innovation, curriculum design, and professionalism in training. Key areas include social media ethics, diversity in healthcare education, and quality improvement strategies in medical programs. Dr. Elliott has contributed to national organizations like the National Board of Medical Examiners and the AAMC Group on Student Affairs, currently serving as Chair of the National Resident Matching Program Board of Directors. Her publication record emphasizes curricular renewal, student learning environments, and the transition to clinical training. Over 20 years of work has advanced educational policies at both institutional and national levels, with a focus on fostering inclusive and effective medical training environments.

• AI
• Digitalisation
• Higher education
• +۹ مورد دیگر

Jimmy Jaldemark is a Professor at the Department of Education, Mid Sweden University, Sundsvall, Sweden. He serves as Research Leader of HEEL (Higher Education and E-Learning) and Head of Subject for the Discipline of Education. His roles include membership in the Faculty Board of Humanities and representation in the university-wide Education Council. He co-founded GRADE, a national graduate school in digital education, and leads the EARLI Centre for Excellence in AI in Learning and Instruction (AILI). His research focuses on AI, digitalization, lifelong learning, and networked learning. He co-edited *Networked Professional Learning* (2019) and guest-edited special issues in the *British Journal of Educational Technology*. He is an editor for that journal and serves on editorial boards for *Educational Research Review*, *Postdigital Science and Education*, and others. He supervises doctoral students and teaches in Behavioral Science and Education programs. Current projects include HEaD (Higher Education and Digitization) and BLAD (Need-based Learning through Adapted Participation). He collaborates internationally, notably in the AILI network exploring AI's educational impacts. His work spans educational development, organizational learning, and policy frameworks for lifelong learning in the digital era.

• Medical Imaging
• Biomedical Engineering
• Magnetic Resonance Imaging (MRI)
• +۳ مورد دیگر

Yonghyun Ha is an Associate Research Scientist in the Department of Radiology & Biomedical Imaging at Yale School of Medicine. His research focuses on advancing magnetic resonance imaging (MRI) technologies, particularly in low-field MRI systems, RF pulse design, and imaging hardware innovation. He collaborates with experts like Duy Phan, Haifan Lin, and Nikhil Malvankar, contributing to projects such as RF pulse distortion compensation and novel RF coil development. Research Interests: His work spans low-field MRI systems , RF engineering , imaging algorithm optimization , and hardware design . He explores applications like point-of-care imaging and cost-effective MRI solutions. Articles Trends: Recent publications address gradient-free imaging, field-cycling magnets, and deep learning for data compression. His work bridges engineering and clinical needs, emphasizing practical MRI advancements. Advising & Grants: No formal advisees are listed, but his collaborations suggest involvement in interdisciplinary research teams. No specific grants are mentioned, but his projects imply funding through institutional or NIH channels. Labs/Teams: Active in Yale’s Radiology & Biomedical Imaging department, contributing to MRI technology development and translational research initiatives.

Georg Langsمشاهده پروفایل

استاد

• Machine Learning
• Medical Imaging
• Precision Medicine
• +۳ مورد دیگر

Georg Langs is a Full Professor of Machine Learning in Medical Imaging at the Medical University of Vienna and Founding Director of the Computational Imaging Research Lab (CIR). He leads a 25-member interdisciplinary team focusing on machine learning methodologies for medical image analysis. Key roles include Director of the Joint Initiative on AI in Medical Imaging (European Institute of Biomedical Imaging Research) and Scientific Lead of the Respiratory Disease Phenotype Observatory (ZODIAC, UNO/IAEA). He is affiliated with MIT’s CSAIL and serves on advisory boards for global AI initiatives. Education: PhD in Computer Science, Graz University of Technology (2007) M.Sc. in Mathematics, Vienna University of Technology (2003) Research Interests: Machine learning-driven precision imaging, neuroimaging, clinical data phenotyping, and cross-species brain connectivity analysis. His work bridges imaging biomarkers with biological mechanisms and large-scale clinical data integration. Grants & Funding: Over €6M in competitive grants as Principal Investigator in the last two years. Projects include ARTEMIS (fatty liver disease digital twins) and AI-POD (personalized risk scores via imaging). Awards: 2022 IS3R Emerging Leaders Club 2022 National Academy of Medicine Emerging Leader Programme 2018 Advisor, AI Mission Austria 2030 Lab & Teams: CIR Lab focuses on AI-driven medical imaging solutions. Co-founded contextflow GmbH , a MedUni spin-off developing AI software for imaging analysis.

Patrick T. Brandtمشاهده پروفایل

استاد

• Political Dynamics
• Time Series Analysis
• Machine Learning
• +۸ مورد دیگر

Patrick T. Brandt is a Professor of Political Science, Public Policy, and Political Economy at the University of Texas at Dallas , affiliated with the School of Economic, Political and Policy Sciences . His work integrates advanced statistical methods with political science, focusing on time series analysis, machine learning, and Bayesian modeling to study political dynamics. His research spans international relations , political economy , terrorist targeting , and conflict forecasting . He specializes in developing novel models for event count time series, including the Bayesian Poisson Vector Autoregression and MS-BVAR packages for R. His NSF-funded projects focus on event data generation and real-time conflict forecasting. Recent publications emphasize domain-specific language models (ConfliBERT variants), graph neural networks for conflict prediction, and machine translation challenges in political text analysis. He maintains the OpenEvent Data Repository and develops software like MSBVAR and PESTS for academic use. Scientific Awards : Robert H. Durr Award for Best Methodology Paper, Midwest Political Science Association (2006)

Raphaël Baroniمشاهده پروفایل

دانشیار

• Narratology
• French Linguistics
• Narrative Theory
• +۷ مورد دیگر

Raphaël Baroni is an Associate Professor of Teaching French as a Foreign Language at the School of French as a Foreign Language (EFLE), Faculty of Arts, University of Lausanne (UNIL). He has held this position since August 1, 2011, and has been actively involved in research and academic collaboration since 2005. He previously taught at the University of Michigan and conducted research at the Center for Research on Arts and Language (EHESS-CNRS) in Paris. His research centers on narratology, particularly narrative tension, plot dynamics, focalization, and transmedial storytelling, with a strong emphasis on the didactic applications of narrative theory in language learning. He aims to develop a general narrative theory while exploring its role as a reflective and pedagogical tool in French language acquisition. His work bridges literary theory, cognitive narratology, and language pedagogy. The recent scholarly output shows a consistent focus on narrative theory, especially in graphic narratives and transmedia contexts. His publications explore narrative pacing, segmentation, immersion, and the teaching of narrative concepts. There is a clear trend toward interdisciplinary research, connecting narratology with media studies, education, and cognitive science. Raphaël Baroni founded the French-speaking Narratology Network (RRN) and co-founded the Research Group on Language Biographies (GReBL) to strengthen interdisciplinary collaboration among Francophone scholars. These initiatives reflect his commitment to building academic communities around narrative studies. He has not received any scientific awards mentioned in the source material, and no information is available about advising students or securing research grants. His work is primarily theoretical and pedagogical, with a strong publication record in narratology and French language education.

• Sleep Disorders
• Obstructive Sleep Apnea
• Digital Health
• +۷ مورد دیگر

Dr Bastien Lechat is a Research Fellow at Flinders Health and Medical Research Institute (FHMRI): Sleep Health, within the College of Medicine and Public Health at Flinders University. He is also a Full Member of the College of Science and Engineering and the Medical Device Research Institute. As an NHMRC Emerging Leadership Fellow, he leads innovative research at the intersection of sleep medicine, artificial intelligence, and wearable technology. Education: PhD in Sleep Health, Adelaide Institute for Sleep Health, Flinders University (2018–2021) Bachelor of Engineering in Engineering Science/Acoustics, Université du Maine, France (2014–2017) Dr Lechat’s research focuses on understanding the physiological mechanisms and consequences of obstructive sleep apnea (OSA), particularly night-to-night variability and patient subtypes. He develops AI-driven tools for efficient and accurate diagnosis using wearables and signal processing. His work aims to create a scalable, low-cost model of care for sleep-disordered breathing, addressing global diagnostic gaps. His recent publications reveal a strong trend in digital health innovation, with a focus on machine learning for OSA detection, circadian rhythm modeling, cardiovascular risk prediction, and climate impacts on sleep. His research has been published in top journals including Nature Communications , Journal of Sleep Research , and Sleep Medicine , demonstrating interdisciplinary reach. Scientific Awards and Recognition: NHMRC Emerging Leadership Fellow (2023) Helen Bearpark Memorial Scholarship (2022) Emerging Research Leader Award, Flinders University (2021) Multiple early-career awards from Sleep Down Under, Australasian Sleep Association, and Adelaide Sleep Retreat Ranked in the top 5% of international authors in sleep apnea by Expertscape Dr Lechat has secured over $2.5 million in competitive research funding and actively supervises and mentors junior researchers. He serves on the program committee of the American Thoracic Society meetings and contributes to clinical guidelines. He collaborates globally with industry and academic partners to translate research into clinical practice. Laboratories and Research Teams: He co-leads the 'Novel use of digital innovations & technology development' theme at FHMRI: Sleep Health, working closely with Professor Danny Eckert. His team integrates expertise in biomedical engineering, data science, and clinical sleep physiology to advance digital sleep medicine.

• Computational Mechanics
• Dynamics of Learning
• Evolutionary Dynamics
• +۱۲ مورد دیگر

Jim Crutchfield is a Distinguished Professor of Physics at the University of California, Davis, where he also serves as Director of the Complexity Sciences Center. He holds additional affiliations as President and Scientific Director of the Art & Science Laboratory in Santa Fe, External Faculty at the Santa Fe Institute, General Member of the Telluride Science Research Center, and Visiting Scholar at the Redwood Center for Theoretical Neuroscience. His work bridges physics, computation, and complex systems. Education: B.A. summa cum laude in Physics and Mathematics, University of California, Santa Cruz (1979) Ph.D. in Physics, University of California, Santa Cruz (1983) Crutchfield's research centers on computational mechanics , a framework he pioneered to quantify how natural systems store, process, and transmit information. His interests span nonlinear dynamics, evolutionary dynamics, information engines, quantum computation, and pattern discovery. He explores how structure emerges in complex systems, from cellular automata to biological evolution and neural networks. His recent work focuses on thermodynamic computing, causal inference, and the physics of intelligence. His publications reveal a consistent focus on the interplay between information, energy, and computation in physical systems. Themes include the thermodynamics of information engines, causal architecture in time series, emergent organization, and intrinsic computation in quantum and classical domains. These works span disciplines such as physics, computer science, biology, and cognitive science. Scientific Recognition: Postdoctoral Fellow, Miller Institute for Basic Research in Science IBM Postdoctoral Fellow, Condensed Matter Physics Distinguished Visiting Research Professor, Beckman Institute Bernard Osher Fellow, San Francisco Exploratorium NSF Graduate Fellow UCB Chancellor’s Fellow Crutchfield has advised over two dozen PhD students in physics, computer science, and mathematics, contributing significantly to the next generation of complexity scientists. He has led major interdisciplinary initiatives, including NSF-funded museum exhibits and workshops on network dynamics, collective cognition, and evolutionary dynamics. He has also been active in public discourse through talks, films, and publications on the philosophy of complexity. He leads research groups exploring the dynamics of learning, pattern discovery, and distributed intelligence, often in collaboration with institutions like the Santa Fe Institute and Caltech. His work continues to shape the theoretical foundations of complex systems science.

Cecilia Feillaمشاهده پروفایل

دانشیار

• Comparative Drama
• Theatre of the French Revolution
• Adaptation Studies
• +۷ مورد دیگر

Cecilia Feilla is an Associate Professor of English and World Literatures and Theatre Arts at Marymount Manhattan College, where she contributes to both literary and theatrical scholarship and pedagogy. Her academic focus spans comparative drama, theatre history, and performance studies, with a strong emphasis on French Revolutionary theatre and its global reverberations. Her research interests include French theatre from the 17th to 19th centuries , adaptation studies , genre theory , and the transnational impact of the French Revolution on performance . She explores how revolutionary ideals were staged, adapted, and reinterpreted across time and cultures, including in early 20th-century China. Her interdisciplinary approach bridges literature, history, politics, and performance. Dr. Feilla’s recent publications reflect a consistent engagement with revolutionary aesthetics, gender, historiography, and pedagogical innovation. Her articles examine topics such as prostitution in Revolutionary drama, the representation of time and history, and immersive teaching models. She has also published on multimodal learning and the adaptation of historical figures like Louise Michel in global contexts. Her awards and fellowships highlight her scholarly and teaching excellence: Fellow, Second Book Institute, University of Tulsa (2023) Senior Faculty Leave Fellowship, Marymount Manhattan College (2023) Runner-up, Margarita Donnelly Prize for Prose Writing (2021) Innovative Course Design Prize, American Society for Eighteenth-Century Studies (2020) Teaching Innovation Award, C-TIE (2018) Sokol Research Grant (2018) Outstanding Faculty Member Award, Humanities & Social Sciences Division (2017) Andrew W. Mellon Innovation Grant (2017) Dr. Feilla has held significant administrative roles, including Director of Assessment (2017–2020), Chair of English & World Literatures (2012–2015), and Director of Learning Communities (2010–2013). She has also been a research fellow at the Folger Shakespeare Library, NYU, and Philipps Universität-Marburg. Her current book project, The Reinvention of Love: Stage Adaptations of the Abelard and Heloise Story , continues her exploration of love, history, and performance. She is actively involved in mentoring and curriculum development, teaching courses such as World Drama, Theatre Histories, Literature & Revolution, and seminars on Romanticism, Gothic fiction, and classical literature.

• Tsetlin Machines
• Reinforcement Learning
• Machine Learning
• +۳ مورد دیگر

Xuan Zhang is an Associate Professor at the Department of Information and Communication Technology, University of Agder. His research focuses on Tsetlin Machines, learning automata, and their applications in machine learning, computer vision, and hyperspectral imaging. Research Trends: Zhang’s recent work includes developing interpretable machine learning models (e.g., Tsetlin Machines), optimizing convolutional architectures for image processing, and applying automata theory to solve multi-armed bandit problems and channel selection in cognitive networks. His field spans theoretical analysis and practical implementations in AI, remote sensing, and health informatics. Scientific Contributions Co-developed advanced Tsetlin Machine variants for XOR/NOT operator convergence, disease forecasting, and image restoration Published in journals like IEEE Transactions on Pattern Analysis and Machine Intelligence , Information Sciences , and Applied Intelligence Explored Bayesian pursuit algorithms, hierarchical learning automata, and particle swarm optimization techniques Contact: xuan.zhang@uia.no

• Wireless Communications
• Network Security
• Quality of Experience (QoE)
• +۷ مورد دیگر

Tasos Dagiuklas is a Professor in the Department of Computer Science and Technology within the School of Engineering and Technology at the University of Bedfordshire. With over 168 publications spanning from 1995 to 2025, he has established himself as a leading researcher in telecommunications and network systems. His extensive publication record demonstrates continuous scholarly contribution across multiple decades in the field. Professor Dagiuklas' research focuses on wireless communications, edge computing, 5G/6G networks, quality of experience (QoE), and federated learning . His work bridges theoretical networking concepts with practical applications, particularly in multimedia delivery and security. He has developed significant expertise in video streaming optimization, network security mechanisms, and resource management in emerging network architectures. His research consistently addresses the evolving challenges of modern communication systems, with recent work increasingly focusing on AI integration in networking. Analysis of his recent publications (2023-2025) reveals a strong trend toward edge computing, federated learning, and security applications in next-generation networks. His work demonstrates a strategic shift from traditional networking concerns to more complex systems involving AI integration, energy efficiency, and heterogeneous environments. The publications show consistent collaboration with researchers across multiple institutions, with particularly strong partnerships with Muddesar Iqbal, Ilias Politis, and Stavros Kotsopoulos. Professor Dagiuklas has made substantial contributions to the academic community through his extensive publication record in high-impact venues including IEEE journals and conferences. His work has evolved from foundational networking research to cutting-edge investigations of AI-enhanced communication systems, reflecting the broader trajectory of the field itself. His research demonstrates both technical depth in specific networking challenges and breadth across multiple application domains.