جست‌وجوی استاد و پژوهشگر

• Biomedical Ethics
• Health Policy
• Medical Sociology
• +۴ مورد دیگر

Dr. Siun Gallagher is a Research Fellow at the Sydney School of Public Health , affiliated with the Faculty of Medicine and Health at the University of Sydney. Her work bridges biomedical ethics, health policy, and qualitative research methodologies. Education : Bachelor of Medicine, Trinity College Dublin Master of Public Health, University of Sydney PhD in Medicine, University of Sydney Research Interests focus on: ethical challenges in clinical practice, professionalism in commercialized medicine, health technology assessment, and equity in healthcare resource allocation. She explores how systemic complexity affects medical decision-making, particularly in assisted reproductive technology (ART) and genomic screening. Recent Publications examine commercial influences in ART, ethical frameworks for ‘add-ons’ in reproductive care, testimonial injustice in patient-clinician interactions, and macroallocation dynamics in health systems. Her work emphasizes qualitative insights into professional values and policy conflicts. Current Projects include the gEnomics4newborns initiative, which integrates ethics and equity into genomic newborn screening. She also critiques informed financial consent and analyzes patient-led demand in ART. Teaching involves the Master of Bioethics program, where she imparts expertise in ethical reasoning and health policy.

Francisco Chiclanaمشاهده پروفایل

استاد

• Fuzzy preference modelling
• Decision making with heterogeneous fuzzy information
• Decision support systems
• +۷ مورد دیگر

Professor Francisco Chiclana is a leading academic in Computational Intelligence and Decision Making at the School of Computer Science and Informatics, De Montfort University (UK). As founder of DIGITS (De Montfort University Interdisciplinary Group in Intelligent Transport Systems), he pioneered research in trust-driven decision frameworks and fuzzy systems. PhD and BSc in Mathematics from University of Granada Coordinated DMU's REF 2014 submission in Computer Science and Informatics Co-developed DMU's Doctoral Training Programme in Intelligent Systems His research focuses on fuzzy preference modelling , consensus reaching processes , and social network analysis for decision support systems. Recent work explores AI applications in trust propagation, power-asymmetric conflict resolution, and large-scale group decision frameworks. Key publications include 15+ peer-reviewed articles in journals like IEEE Transactions on Fuzzy Systems and Information Sciences , covering topics from type-2 fuzzy logic to Nash bargaining compensation mechanisms . His Greenfield-Chiclana Collapsing Defuzzifier won third prize at DMU's Creative Thinking Awards 2010. Outstanding PhD Award (University of Granada, 2000) Finalist in DMU-THE OSCAR AWARDS for Research Excellence (2012) As supervisor of 8+ current and completed PhD students, including Sarah Greenfield and Sergio Alonso Burgos, he has shaped next-generation researchers. His £145K EPSRC-funded project (2006-2009) extended fuzzy logic applications in consensus modelling.

Elizabeth J. Hongمشاهده پروفایل

استاد

• Neuroscience
• Molecular Biology
• Neurophysiology
• +۳ مورد دیگر

Elizabeth J. Hong is a Professor of Neuroscience and Chen Scholar at the California Institute of Technology, serving as Interim Director of the T&C Chen Center for Systems Neuroscience. She holds academic appointments including Assistant Professor (2015-23), Boothe Luce Assistant Professor (2015-21), and Professor (2023–present). Her research focuses on synaptic molecular diversity and its impact on neural circuit computations, using the Drosophila olfactory system as a model. Key contributions include studies on odor-driven behaviors, synaptic physiology, and genetic manipulation strategies for circuit analysis. Education : B.S., California Institute of Technology, 2002 Ph.D., Harvard University, 2009 Research Interests : Her lab investigates how molecular differences at synapses influence physiological function and circuit-level computations. Using Drosophila's genetic toolkit, they combine in vivo electrophysiology, two-photon imaging, and behavioral assays to link synaptic properties to neural coding. Current projects explore odor representation restructuring, CO₂ sensory pathways, and the developmental basis of neural circuits. Awards : Chen Scholar (2021–present) Advisees/Grants : While specific student names aren't listed, the lab recruits trainees interested in synapse biology, neural circuits, and behavioral genetics. Techniques employed include TRACT (transneuronal transcription control) for circuit tracing and optogenetic tools for functional interrogation. Labs/Teams : The Hong Lab collaborates with the T&C Chen Center, focusing on systems-level neuroscience questions. Their work bridges molecular mechanisms with behavior, emphasizing evolutionary and developmental perspectives.

Sivan Sabatoمشاهده پروفایل

دانشیار

• Interactive machine learning
• Machine learning theory
• Fairness in machine learning
• +۳ مورد دیگر

Sivan Sabato is an Associate Professor at McMaster University's Department of Computing and Software , a Canada CIFAR AI Chair, and faculty member at the Vector Institute of Artificial Intelligence . She holds a joint appointment at Ben-Gurion University's Department of Computer Science while on leave. Her research focuses on machine learning theory, active learning algorithms , and fairness in machine learning . Education: PhD in Computer Science, Hebrew University of Jerusalem Postdoctoral Fellowship, Microsoft Research New England Her theoretical work develops interactive learning frameworks that optimize information costs through algorithmic interaction patterns. Recent publications emphasize differential privacy and discriminative feature analysis with applications to healthcare and social data. She serves as Action Editor for Journal of Machine Learning Research and organizes conference tracks including ICML 2022-2023 and ALT 2021 . Awards include the Alon Scholarship and Google Anita Borg Memorial Scholarship . Advising: Actively supervises Computer Science PhD and MSc students through McMaster's Faculty of Engineering. Research interns can apply via the Vector Institute program with Summer 2026 opportunities.

Ursula Klingmüllerمشاهده پروفایل

استاد

• Systems Biology
• Signal Transduction
• Molecular Biology
• +۵ مورد دیگر

Prof. Dr. Ursula Klingmüller is a Professor at Ruprecht-Karls-Universität Heidelberg and Head of the Division Systems Biology of Signal Transduction (B200) at the German Cancer Research Center (DKFZ) in Heidelberg since 2007. She holds a Venia Legendi in Cell Biology (Heidelberg University, 2004) and Molecular Biology & Genetics (University of Freiburg, 2000). Her career spans leadership roles in systems biology, integrating computational and experimental approaches to understand cellular signaling networks in cancer and other diseases. Education: Diploma in Molecular Biology, Cell Biology, and Virology (University of Heidelberg, 1988) Bachelor of Science (University of Bayreuth, 1985) Doctoral Thesis in Molecular Biology (Heidelberg University, 1992) Research Interests focus on systems biology approaches to signal transduction, particularly the JAK2/STAT5, AKT/ERK, and TGF-β pathways, their roles in cell proliferation, cancer invasion, and dynamic threshold regulation. Her work emphasizes computational modeling of signaling networks and their integration with clinical applications in precision medicine. Key Scientific Contributions include elucidating the context-specific dynamics of ERK phosphorylation, defining the regulatory roles of BAMBI in TGF-β signaling, and advancing personalized dose prediction models for erythropoietin therapies. Her publications reflect interdisciplinary research bridging molecular mechanisms with quantitative modeling. Scientific Awards: FEBS Anniversary Prize (1997) DAAD-Fellowship (1986) DFG-Research Fellowship (1993-1994) Election to the German Ethics Council (2016) Labs & Teams include the Systems Biology of Signal Transduction division at DKFZ, collaborations with the German Cancer Research Center, and leadership in the Master Program Molecular Biosciences at Heidelberg University. She also serves on editorial boards, including as Associate Editor for Nature Systems Biology and Applications , and chairs the Executive Women's Initiative at DKFZ.

Michalis Zervasمشاهده پروفایل

استاد

• Optical Communications
• Photonics
• Fibre Lasers
• +۳ مورد دیگر

Professor Michalis Zervas serves as Professor of Optical Communications at the University of Southampton's Optoelectronics Research Centre (ORC), leading pioneering research in photonics and laser technologies. His work integrates advanced optical systems with artificial intelligence to solve complex challenges in telecommunications, manufacturing, and medical diagnostics through major collaborations with industry and international research bodies. His primary research spans Optical Communications, Photonics, and Fibre Lasers, with specialized focus on deep learning applications for laser control optimization, coherent beam combination, and optical fibre sensor development. Current investigations include high-power photonics systems for industrial manufacturing and novel laser-based biomedical diagnostic platforms that bridge physics with healthcare innovation. Recent publications (2025) reveal a decisive trend toward AI-photonic integration, where deep learning algorithms enhance precision in laser-material interactions across diverse applications—from microbead cleaning and paint analysis to psoriasis treatment simulation and diatom imaging. This interdisciplinary approach demonstrates consistent methodological innovation in merging computational intelligence with fundamental laser physics. Supervises 6 PhD students including Rosemary Catriona Clark and Fedor Chernikov in ORC's photonics programs Secures major funding from EPSRC (Smart Fibre-Optic High Power Photonics, Hearing Light) and US Air Force Office of Scientific Research Leads collaborative projects with Professor Sir David Payne and Professor Johan Nilsson across national manufacturing hubs As co-leader of the Smart Lasers and Special Fibres research group within the Advanced Laser Laboratory, Zervas drives experimental photonics innovation through state-of-the-art fibre laser systems and optical resonator technologies. His team maintains strategic partnerships with global industry leaders in photonics manufacturing and medical device development.

Andreas Huthمشاهده پروفایل

پژوهشگر

• Ecological Modeling
• Vegetation Dynamics
• Biodiversity Modeling
• +۴ مورد دیگر

Andreas Huth is a prominent researcher at the Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany, where he works within the Department of Ecological Systems Analysis. His research focuses on developing and applying computational models to understand complex ecological systems, with particular emphasis on vegetation dynamics, biodiversity patterns, and environmental interactions. Huth is actively involved in several major research initiatives including the FORMIND project, which simulates forest growth using individual-based vegetation models, and contributes to the UFZ's research program on Smart Models and Monitoring. Huth's research interests span ecological modeling, vegetation dynamics, biodiversity assessment, and environmental system analysis. He specializes in developing sophisticated computational frameworks that integrate atmospheric, ecological, and spatial data to model complex environmental processes. His work often involves coupling different modeling approaches, such as connecting atmosphere and vegetation radiative transfer models to study cloud-vegetation interactions. Huth is particularly interested in understanding spatial patterns in ecological systems, species-habitat relationships, and the impacts of environmental change on biodiversity. His methodological expertise includes agent-based modeling, individual-based modeling, and developing digital twin technologies for environmental systems. Analysis of Huth's recent publications reveals a strong focus on integrating different modeling approaches to address complex environmental questions. His work demonstrates a progression from basic ecological modeling toward more sophisticated integrative frameworks that connect atmospheric processes with vegetation dynamics, and social systems with ecological outcomes. A notable trend is his increasing involvement in digital twin technology for environmental systems, particularly for biodiversity monitoring and prediction. His research spans multiple scales - from microbial ecosystems to continental-scale species distributions - while maintaining a consistent methodological thread of spatially explicit modeling and causal analysis in complex systems. Huth collaborates extensively with researchers across the UFZ and internationally, as evidenced by his co-authorship on numerous interdisciplinary publications. While specific awards are not mentioned in the available information, his consistent publication record in high-impact journals and leadership in major modeling initiatives like FORMIND indicate significant recognition within the ecological modeling community. His work has practical applications for environmental policy, conservation planning, and climate change adaptation strategies. Huth is an active member of the Ecological Systems Analysis research group at UFZ, which develops and applies computational models to investigate key mechanisms in ecological systems. He contributes to several major research platforms including FORMIND (an individual-based vegetation model for species-rich forests) and participates in the UFZ's broader research initiatives on environmental monitoring and sustainable technologies. His work is integrated within the UFZ's research program on Smart Models and Monitoring, which aims to develop innovative approaches for understanding and predicting environmental change.

• Operations Management
• Algorithmic Decision-Making
• Revenue Management
• +۳ مورد دیگر

Ningyuan Chen is a faculty member at the University of Toronto with affiliations at the Rotman School of Management and University of Toronto at Mississauga's Department of Management. His research spans operations management with a focus on algorithmic decision-making, revenue management, and data analytics. Chen's research interests center on the intersection of algorithms and human decision-making processes, with particular emphasis on how human knowledge can safeguard and improve algorithmic recommendations. His work addresses critical challenges in commercial AI solutions where human analysts have domain-specific insights that may conflict with algorithmic outputs. He investigates conditions under which human knowledge augmentation benefits algorithmic decision-making, particularly when facing algorithmic pitfalls like lack of domain knowledge, model misspecification, and data contamination. Chen's publication trends reveal a strong focus on practical business applications of operations research, with recent work examining assortment pricing with transaction data, vaccine allocation under limited supply, and simultaneous versus sequential product release strategies. His research combines theoretical modeling with practical business implications, often collaborating with Ming Hu and other researchers at the Rotman School. His work demonstrates how data-driven approaches can be enhanced through human expertise, particularly in contexts where pure algorithmic recommendations might fail due to real-world complexities that data alone cannot capture. This research has important implications for business intelligence systems across various industries where human judgment remains critical alongside algorithmic recommendations.

• Human-System Integration
• Digital Twins
• Multi-Agent Systems
• +۲ مورد دیگر

Karel Kruger is an Associate Professor in Automation Systems at the Institute of Manufacturing, University of Cambridge. His research focuses on integrating complex digital and physical systems with human-centric design, particularly through technologies like Digital Twins, Multi-Agent Systems, and Holonic Systems. Prior to Cambridge, he served as a Senior Lecturer and co-leader of the Mechatronics, Automation and Design Research Group at Stellenbosch University (South Africa), where he earned his PhD in 2018. Mechatronic Engineering (BSc) Research Master's Degree PhD (Stellenbosch University, 2018) His work spans manufacturing, maritime, and mining domains, emphasizing human-system integration, workplace safety, and low-cost digital manufacturing solutions. He has contributed extensively to academic discourse through publications on architecture design, Industry 4.0, and human-centered automation. Recent publications highlight his expertise in digital twins for IoT device management, holonic systems for fruit supply chains, and cybersecurity considerations for Industry 4.0. His research bridges theoretical frameworks like ARTI/BASE architectures with practical implementations in manufacturing cells, conveyor systems, and maritime environments.

Martha S. Feldmanمشاهده پروفایل

استاد

• Organization theory and behavior
• Organizational routines and routine dynamics
• Stability and change in organizations
• +۳ مورد دیگر

Martha S. Feldman holds the Johnson Chair for Civic Governance and Public Management at the University of California, Irvine, where she is a Distinguished Professor in Urban Planning and Public Policy, Management, Political Science, and Sociology. She earned her PhD from Stanford University in 1983. Her work focuses on organizational routines, public management, and qualitative research methods. Her research explores how organizational routines drive stability and change, with a focus on their role in decision-making and institutional adaptation. She has pioneered frameworks for understanding routine dynamics, integrating practice theory and process studies. Feldman has served as Senior Editor for Organization Science (2006–2018) and sits on editorial boards of leading journals including Academy of Management Journal and Journal of Management Studies . Her contributions have been recognized with major awards, including the 2009 Administrative Science Quarterly award and two honorary doctorates from the Universities of St. Gallen and Hanken. Her scholarship bridges theory and practice, addressing topics like collaborative governance, inclusive management, and narrative analysis. She has produced over 100 peer-reviewed articles, with a focus on organizational learning, public policy implementation, and methodological innovation in qualitative research.

Daniel Nylenمشاهده پروفایل

دانشیار

• Digital Innovation
• Digital Transformation
• Artificial Intelligence
• +۳ مورد دیگر

Daniel Nylen is an Associate Professor at the Department of Informatics, Umeå University. He holds the qualification of Docent and is recognized as a university teacher. Based at the MIT building in Umeå, he maintains an active research profile with publications spanning from 2008 to 2024. His research focuses on digital transformation processes across diverse sectors, examining how organizations implement and adapt to digital technologies. His work investigates: Digital innovation strategies and frameworks AI implementation in public sector contexts Organizational implications of digitalization Technology adoption in traditional industries Value creation through digital platforms Analysis of his recent publications reveals a clear evolution from early work on digital magazines and forestry industry transformation toward current research on AI implementation, algorithmic decision-making, and digital infrastructure needs in public administration. His research consistently employs detailed case studies to develop nuanced understandings of digital transformation dynamics. Dr. Nylen is actively involved in multiple research projects including 'AI-based automation in forestry' (2024-2026), 'UmArts Art & AI research project' (2023-2027), 'Digital twins for forest planning' (2023-2024), and 'HYDE – Human agency in semi-automated decision-making systems' (2021-2024). He is a member of both the 'AI and society' research group and the 'Swedish Center for Digital Innovation,' collaborating with researchers across disciplines to address complex digital transformation challenges in contemporary organizations.

• Machine Learning
• Time Series Analysis
• Space Weather Prediction
• +۴ مورد دیگر

Soukaina Filali Boubrahimi serves as an Assistant Professor in the Computer Science Department within the College of Engineering at Utah State University. Her academic appointment is based in the SER 332 building located at 4205 Old Main Hill, Logan, UT 84322-0001. She maintains a research-active position with a focus on computational methods for complex temporal data analysis. Dr. Filali Boubrahimi's research program centers on time series analysis , machine learning , and space weather prediction , with particular emphasis on solar flare forecasting and counterfactual explanation systems. Her work bridges theoretical machine learning advancements with practical applications in heliophysics, hydrology, and social media analysis. The research portfolio demonstrates significant expertise in handling imbalanced temporal datasets, developing novel data augmentation techniques, and creating interpretable AI systems for critical prediction tasks. Analysis of her recent publication trajectory reveals consistent contributions to counterfactual explanation frameworks for time series data (Info-CELS, M-cels, ACTS), space weather prediction systems (solar flare and energetic particle event forecasting), and generative modeling approaches (AVATAR, ChronoGAN). Her work frequently addresses the challenges of severely imbalanced datasets through contrastive learning and sophisticated preprocessing techniques, demonstrating methodological innovation in handling rare but critical space weather events. While no specific awards are documented in the available information, her research program appears substantial based on the volume and quality of recent publications spanning multiple high-impact domains. The research demonstrates strong interdisciplinary connections between computer science, space physics, and environmental science. Her laboratory activities focus on developing machine learning frameworks for temporal data analysis, with particular attention to space weather prediction systems. The research group appears to specialize in creating robust models for rare event prediction, explainable AI systems for time series classification, and novel data augmentation techniques for imbalanced temporal datasets. Current projects likely include the development of multimodal fusion approaches for solar energetic particle prediction and spatio-temporal modeling for hydrological applications.

Xiusi Chenمشاهده پروفایل

پژوهشگر ارشد

• Large Language Models
• Natural Language Processing
• AI for Science
• +۵ مورد دیگر

Xiusi Chen is a Postdoctoral Research Fellow in the Blender Lab at the University of Illinois Urbana-Champaign (UIUC), working under Prof. Heng Ji. His research focuses on improving reasoning, alignment, and decision-making capabilities of Large Language Models (LLMs). Previously, he completed his Ph.D. in Computer Science at UCLA under Prof. Wei Wang, and earned M.S. and B.S. degrees in Computer Science from Peking University under Prof. Jun Gao. His educational background includes: Ph.D. in Computer Science, University of California, Los Angeles (UCLA), advised by Prof. Wei Wang M.S. in Computer Science, Peking University, advised by Prof. Jun Gao B.S. in Computer Science, Peking University, advised by Prof. Jun Gao Dr. Chen's research program targets three interconnected areas: advancing Large Language Models (particularly in low-resource reasoning and alignment), developing NLP applications for AI in Science and recommendation systems, and modeling complex decision-making processes in sports domains. His work bridges theoretical foundations with practical implementations, resulting in numerous publications in top-tier conferences including ACL, ICML, ICLR, and KDD. Analysis of his recent publications reveals a strong focus on making LLMs more efficient, reliable, and capable of complex reasoning tasks across diverse domains. His significant academic contributions include: 2023 Best Poster Award (Honorable Mention) at SDM 2023 2023 SIAM Student Travel Award 2021 and 2022 SIGIR Student Travel Grants from ACM SIGIR Multiple academic scholarships from Peking University Co-creation of the widely adopted Amazon Reviews'23 dataset (500k+ HuggingFace downloads) Dr. Chen actively serves the research community as Workshop Organizer for KDD 2025, Program Committee member for major conferences (KDD, WSDM, ICML, NeurIPS, ICLR, AAAI), and journal reviewer. He maintains a strong commitment to mentoring, offering dedicated time for students (especially from underrepresented groups) to discuss research and career development. Starting Fall 2025, he will be seeking academic positions to continue his research on language agents and decision-making systems. Currently based in the Siebel Center for Computer Science, Dr. Chen collaborates with the Blender Lab team on advancing NLP and LLM capabilities. His work has practical impact through widely adopted resources like the Amazon Reviews'23 dataset and theoretical contributions through his publications on reasoning frameworks and alignment techniques.

• Artificial Intelligence in Manufacturing
• Production Engineering
• Circular Economy in Manufacturing
• +۴ مورد دیگر

Dr. Amon Göppert serves as Professor and Chair of the Intelligence in Quality Sensing group at RWTH Aachen University's Laboratory for Machine Tools and Production Engineering (WZL). His work integrates artificial intelligence into manufacturing processes to enhance quality control, production efficiency, and sustainable practices. Göppert's research spans intelligent manufacturing systems with core expertise in AI-driven production engineering, circular economy applications, and advanced assembly systems. He investigates how machine learning optimizes production ramp-up, disassembly processes, and flexible manufacturing while developing sensor-based quality control solutions for industrial applications. His recent publications reveal strong trends toward AI implementation in production planning, with emphasis on worker assistance systems for disassembly, digital twin applications for real-time control, and mobile robotics in line-less assembly environments. Key focus areas include sustainable manufacturing, metrology innovation, and adaptive scheduling systems. Göppert leads multiple high-impact research initiatives: AI-driven Product Development: Machine learning for smart measurement strategies in metrology MetaVision Consortium: Industrial metaverse applications for AI-supported vision systems Generative AI for Non-Destructive Testing optimization Cluster of Excellence Internet of Production participation As Chief Engineer at WZL, he oversees technical implementation of research projects and collaborates with industry partners to translate innovations into practical manufacturing solutions, particularly in adaptive assembly systems and quality sensing technologies.

Floor Middelمشاهده پروفایل

استادیار

• Child Protection
• Decision-Making in Child Protection
• Bias in Decision-Making
• +۵ مورد دیگر

Floor Middel serves as an Assistant Professor in the Department of Pedagogical and Educational Sciences at the Faculty of Behavioural and Social Sciences, University of Groningen. Her academic work bridges research, teaching, and practical application in child protection systems with a focus on decision-making processes and addressing systemic biases. Dr. Middel's research interests center on understanding and improving decision-making in child protection systems through rigorous examination of how ethnicity, migration background, and gender influence child welfare investigations and outcomes. Her work employs intersectional analysis to uncover disparities in decision-making processes and examines how stereotypes might mediate these disparities. She also explores the role of digital technologies in modern social work practice and develops assessment tools to measure meaningful participation of children in protection systems. Analysis of Dr. Middel's scholarly output reveals a cohesive research trajectory focused on equity and evidence-based practice in child protection. Her publications demonstrate growing international recognition, with work spanning comparative analyses of child protection systems across Europe, investigations into decision-making ecology, and development of practical assessment tools. The research consistently addresses the UN Sustainable Development Goals related to reducing inequalities and promoting just, peaceful, and inclusive societies. Fulbright scholarship (2019) Jo Kolk travel grant (2019) NWO idea generator (2019) Travel grant for U4 Summer school 'Methods and Methodologies: Complexities and Responsibilities in Gender Research' (2018) Travel grant Swiss National Science Foundation (2018) As an educator, Dr. Middel mentors undergraduate students and teaches across multiple courses including Interview Practical, Report Practical, Statistical Models 2, and Qualitative Research Methods. She delivers guest lectures on Decision-making in Child Protection for master's students, supervises traineeships and theses in Orthopedagogy, and coordinates the international summer school 'The Future of Child and Family Welfare Policy: Looking Through Different Lenses.' Her teaching directly connects with her research expertise, providing students with evidence-based perspectives on contemporary child protection challenges.