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Rosalyn MoranView profile

Professor

• Computational Neuroscience
• Computational Psychiatry
• Neurodegenerative Diseases
• +5 more

Professor Rosalyn Moran is a Professor of Computational Neuroscience and Deputy Director of King's Institute for Artificial Intelligence at King's College London. She holds roles in the Department of Neuroimaging and School of Neuroscience within the Institute of Psychiatry, Psychology & Neuroscience. Her research focuses on computational neuroscience, computational psychiatry, and neurology, particularly integrating brain connectivity with algorithmic principles like the free energy principle. She explores neurotransmitter roles in decision-making and disease modeling, with applications in artificial intelligence and neurodegenerative disorders. Moran serves as an editor for Neuroimage and collaborates with leading institutions. Key projects include global neuroimaging initiatives (UNITY) and low-field MRI advancements in low-resource settings. Her work bridges Bayesian inference, AI, and neurobiology, with recent emphasis on pediatric neuroimaging and treatment-resistant psychosis. Education & Research Interests Rosalyn Moran's research spans computational psychiatry, neuroimaging techniques, and AI applications in healthcare. Her lab investigates serotonin and dopamine signaling, brain connectivity patterns, and predictive coding frameworks. Notable contributions include modeling NMDA receptor dysfunction in encephalitis and developing super-resolution MRI methods for global health contexts. Grants & Collaborations Funded projects include MRC Human Functional Genomics (2024-2028), NIHR Maudsley BRC (2022-2027), and Gates Foundation initiatives for low-field MRI enhancement. Collaborators include Karl Friston (UCL), Read Montague (Virginia Tech), and Klaas Enno Stephan (University of Zurich). Recent events include presenting the Free Energy Principle's role in generative AI (May 2023). Labs & Teams Her lab focuses on computational psychiatry and AI-driven neuroimaging solutions, collaborating with the King’s Global Health Institute to advance medical imaging accessibility in low-income regions.

• Plant Developmental Biology
• Epigenetics
• Plant Genetics
• +5 more

Ueli Grossniklaus is an Ordinary Professor at the University of Zurich within the Faculty of Mathematical and Natural Sciences , affiliated with the Department of Plant and Microbiology . His work focuses on plant developmental biology, particularly epigenetic and genetic mechanisms governing reproduction and adaptation. Key Courses: Epigenetics, Plant Biology Workshop, Group Seminars on Current Research Laboratory Techniques: Advanced methods in plant cell mechanics, transcriptomics, and genome editing Research Interests span plant epigenetics, reproductive biology, and the interplay between environmental stress and genetic regulation. He investigates: Mechanistic control of gametogenesis and fertilization Epigenetic contributions to plant adaptation Evolutionary implications of asexual reproduction Biophysical forces in plant cell growth Publication Trends (2025–2018) reveal expertise in: Arabidopsis and fern model systems Epigenetic regulation (DNA methylation, histone dynamics) Apomixis and hybrid seed failure mechanisms Biomechanics of pollen tubes and carnivorous plants Genome editing tools (CRISPR) and long-read sequencing Scientific Collaborations include interdisciplinary projects on: Microfluidic devices for plant cell analysis Gene drive ecology and ethics 3D imaging of plant reproductive structures Advising and Grants focus on mentoring through research internships in developmental biology, genetics, and systems biology. His lab engages in: Epigenetic response to environmental stress Cell wall mechanics in reproduction Computational modeling of plant growth Laboratory Teams integrate plant biologists, bioengineers, and computational scientists to study: Mechanistic gene regulation Evolutionary developmental biology Microrobotics for cellular force measurement

Briga HynesView profile

Senior Lecturer

• Entrepreneurship
• Innovation Management
• Leadership Development
• +5 more

Dr. Briga Hynes is a Senior Lecturer in Entrepreneurship at the Kemmy Business School, University of Limerick, with expertise spanning entrepreneurship education, innovation leadership, and social enterprise development. She holds a Masters in Business Studies (MBS) and Bachelor in Business Studies (BBS) , and has served as Head of Department of Management & Marketing. Key affiliations include the Centre for Research Training in Foundations of Data Science and the All-Ireland Business Foundation Awards Collaborations span University Hospital Group, Enactus Ireland, and Technology Transfer Office Research Focus : Briga specializes in pedagogical approaches for cultivating entrepreneurial mindsets and innovation leadership across disciplines. Her work addresses: Embedded entrepreneurial learning frameworks Transformational leadership in public/private sectors Social innovation policy impact Healthcare delivery optimization Triple bottom line sustainability Scientific Contributions : Her research on female researchers in STEM informed European Commission's EntreCompEngage framework. Notable funded projects include: €125,000 HEA grant for female STEM commercialization programs €240,000+ EU/National funding for entrepreneurship bootcamps and digital technology adoption Leadership & Engagement : Active in AACSB/AMBA/EQUIS accreditation committees and Athena Swan initiatives, she designs bespoke programs for researchers, entrepreneurs, and employers. Current projects focus on actor-network theory in healthcare and cross-sector innovation dynamics.

Simon CrouchView profile

Research Fellow

• Statistical Modeling
• Epidemiology
• Cancer Research
• +6 more

Simon Crouch is a Senior Research Fellow in Biostatistics at the University of York's Health Sciences department. With a strong mathematical background from Cambridge and Warwick, he leads the analytics team within the Epidemiology and Cancer Statistics Group and works closely with the Haematological Malignancy Research Network (HMRN) and Cardiovascular Health team. His work focuses on statistical modeling of complex epidemiological data related to hematological malignancies. University of Cambridge: MA, MMath in Mathematics University of Warwick: PhD in Mathematics University of Lancaster: MSc in Medical Statistics Dr. Crouch specializes in the statistical modeling of complex epidemiological data, with particular focus on hematological malignancies. His research encompasses predictive modeling, event history analysis, and machine learning applications in cancer epidemiology. He has made significant contributions to understanding myelodysplastic syndromes, lymphoma classification, and survival analysis in blood cancers through population-based studies. His work often involves collaboration with international registries including the European Myelodysplastic Syndromes Registry (EUMDS) and the Haematological Malignancy Research Network. Analysis of his recent publications reveals a strong focus on myelodysplastic syndromes (MDS), with particular attention to risk stratification, survival analysis, and treatment outcomes. His work increasingly incorporates genomic and molecular data to refine disease classification and prediction models. The trend shows progression from purely statistical methodology development toward integrated translational research that combines clinical, genomic, and epidemiological data to improve patient outcomes. Extensive publication record with 113 research outputs including 66 articles, 21 patents, and numerous meeting abstracts Active participation in major international research consortia including MDS-RIGHT and ImmunAID Significant contributions to the development of statistical methodologies for cancer epidemiology Dr. Crouch actively supervises PhD students in mathematical and statistical modeling applied to cancer epidemiology, with particular interest in time-to-event models, complex longitudinal models, and simulation techniques. His research has been supported through multiple projects, including the European Myelodysplastic Syndromes Registry and the MDS-RIGHT project focused on facilitating informed decision-making in hemato-oncology. He contributes to the Advanced Health and Social Statistics module for postgraduate students at the University of York.

Cleotilde GonzalezView profile

Research Professor

• Decision Science
• Cognitive Psychology
• Human-Computer Interaction
• +5 more

Cleotilde (Coty) Gonzalez is a Research Professor of Decision Sciences at Carnegie Mellon University, with primary affiliation in the Department of Social and Decision Sciences (SDS). She serves as the Founding Director of the Dynamic Decision Making Laboratory (DDMLab) and Research Co-Director of the NSF National Institute for AI for Societal Decision Making (AI-SDM). Her extensive academic affiliations include the Security and Privacy Institute (CyLab), the Societal Computing program in the Software and Societal Systems Department (S3D), the Human-Computer Interaction Institute (HCII) in the School of Computer Science, and the Center for Behavioral Decision Research (CBDR) and Center for Neural Basis of Cognition (CNBC). Dr. Gonzalez holds a Ph.D. in Management Information Systems and has developed Instance-Based Learning Theory (IBLT), a significant contribution to cognitive science that explains how people make decisions based on past experiences. Her research spans experimental studies and computational modeling of cognitive processes in dynamic decision environments, with applications in cybersecurity, human-machine teaming, and societal decision making. Her recent publications reveal a strong focus on human-AI collaboration, collective intelligence, cybersecurity, and cognitive modeling. The research trends show increasing integration of AI systems with human decision processes, particularly examining how humans and AI can complement each other in complex decision environments. Her work increasingly addresses cybersecurity challenges through behavioral science perspectives, exploring how cognitive models can improve defense mechanisms against social engineering attacks. Lifetime Fellow of the Cognitive Science Society Lifetime Fellow of the Human Factors and Ergonomics Society Member of the Governing Board of the Cognitive Science Society Member at Large of the Policy Council of the System Dynamics Society Committee member of the National Academies Division Committee for the Behavioral and Social Sciences and Education Dr. Gonzalez has mentored over 50 post-doctoral fellows and doctoral students, with many going on to successful careers in academia, government, and industry. Her research has been supported by major collaborative efforts including Collaborative Research Alliances (CRA) and Multi-University Research Initiative grants from the Army Research Laboratories (ARL) and Army Research Office (ARO), as well as projects with the Defense Advanced Research Projects Agency (DARPA). She directs the Dynamic Decision Making Laboratory, which conducts research involving laboratory experiments and cognitive computational models to derive theoretical conclusions about dynamic decision making and develop applications for societal problems.

Albert S. BerahasView profile

Assistant Professor

• Nonlinear Optimization
• Machine Learning Optimization
• Stochastic Optimization
• +5 more

Albert S. Berahas is an Assistant Professor in the Department of Industrial and Operations Engineering at the University of Michigan's College of Engineering. He joined the university in 2020 after completing postdoctoral positions at Lehigh University (2018-2020) and Northwestern University (2018). He holds a PhD in Engineering Sciences and Applied Mathematics from Northwestern University (2018), an MS in Applied Mathematics from Northwestern (2012), and a BSE in Operations Research and Industrial Engineering from Cornell University (2009). His research focuses on designing, developing, analyzing, and implementing algorithms for solving large-scale nonlinear optimization problems. His work spans multiple sub-fields including constrained optimization, optimization for machine learning, stochastic optimization, derivative-free optimization, and decentralized optimization. He is affiliated with the Michigan Institute for Data Science (MIDAS), the Michigan Institute for Computational Discovery and Engineering (MICDE), and the Michigan Center for Applied and Interdisciplinary Mathematics (MCAIM). Berahas has received numerous honors including the Charles Broyden Prize (2025), the Air Force Office of Scientific Research Young Investigator Program award (2025), the IISE Operations Research Division Teaching Award (2024), and the North Campus Dean's MLK Spirit Award for Community Building & Impact (2024). His recent publications demonstrate strong activity in developing novel optimization frameworks with theoretical guarantees for challenging problem settings. His research has been supported by significant grants including from the Office of Naval Research (ONR) and the Air Force Office of Scientific Research. He actively mentors PhD students and has successfully advised Jiahao Shi, who defended his dissertation in March 2025 and joined Amazon. Berahas is also engaged in community outreach, particularly through initiatives like Engage Detroit that aim to empower Detroit's next generation of engineers.

Magnus LinnarssonView profile

Professor

• Political history
• Urban history
• Early modern period
• +4 more

Magnus Linnarsson is a Professor of History at Stockholm University's Department of History, specializing in political history with a focus on early modern and modern Sweden. His research examines institutional change, public-private service organization, and the evolution of the welfare city. He leads undergraduate programs and supervises students at all levels. PhD in History (2010), Lund University Associate Professor (2017), Stockholm University His research spans four centuries of political conflicts over public services, state formation, and urban development. Key works include analyses of Sweden's postal, customs, and welfare systems, comparing hierarchical and contractual state organization models. Recent publications (2024) in Nordic Welfare Cities explore urban citizenship and inclusive welfare systems since 1850, challenging national narratives by emphasizing local governance. Earlier studies (2022–2018) dissected regime shifts, mercantile-state relations, and publicness concepts in tramway and telecom debates. Current projects include: Skiftande regimer (2021–2025): State formation and administrative reform (Vetenskapsrådet-funded) Olika vägar till välfärdsstaden (2021–2025): Nordic urban welfare debates (Riksbankens jubileumsfond-funded) He advocates for interdisciplinary analysis of political economy, institutional loyalty, and spatial dynamics, connecting historical debates to modern policy challenges.

Bo XiongView profile

Researcher

• Machine Learning
• Knowledge Graphs
• Graph Neural Networks
• +4 more

Bo Xiong is a researcher at the University of Stuttgart in the Analytic Computing group. His research focuses on machine learning and knowledge graphs , with a particular emphasis on geometric embeddings and hyperbolic neural networks. His research interests include: Knowledge graph embeddings Hyperbolic and pseudo-Riemannian geometry in AI Temporal knowledge graph reasoning Structured multi-label prediction Recent publications highlight his work on geometric relational embeddings, complex query answering, and temporal fact reasoning using advanced manifold-based techniques.

Saud AlhusainiView profile

Assistant Professor

• Neurology
• Movement Disorders
• Parkinson's Disease
• +4 more

Saud Alhusaini MD PhD is an Assistant Professor of Neurology at the Warren Alpert Medical School of Brown University and serves as a Neurologist/Movement Disorders Specialist at Rhode Island Hospital. His research integrates imaging genomics and multimodal brain imaging approaches to investigate neurological disorders including Parkinson's disease, essential tremor, and epilepsy. He is affiliated with the Carney Institute for Brain Science and collaborates extensively with clinicians, geneticists, electrophysiologists, MRI specialists, neuropsychologists, and data scientists. Education: PhD from the Royal College of Surgeons in Ireland (RCSI) MSc in Neuroscience from Trinity College Dublin MD from University of Dublin, School of Medicine Adult neurology residency at McGill University/Montreal Neurological Institute Clinical research fellowship at Yale School of Medicine Clinical fellowship at Stanford University Medical Center Dr. Alhusaini's research focuses on identifying key endophenotypes and subclinical biomarkers to elucidate the underlying mechanisms of complex neurological conditions. His work spans multiple areas including movement disorders, epilepsy, and brain structure genetics. He has made significant contributions to understanding the genetic architecture of brain structures through his involvement with the ENIGMA consortium, which conducts large-scale collaborative analyses of neuroimaging and genetic data across institutions worldwide. An analysis of his publication record reveals a consistent pattern of high-impact research at the intersection of neurology, genetics, and advanced imaging techniques. His recent work demonstrates particular expertise in Parkinson's disease genetics, epilepsy network analysis, and movement disorder diagnostics. The breadth of his research, spanning from basic genetic mechanisms to clinical applications, highlights his comprehensive approach to understanding neurological disorders. Dr. Alhusaini has received funding from the Rhode Island Research Foundation, Brown Physicians, Inc., and Advance RI-CTR to support his research initiatives. His collaborative approach is evident through his numerous multi-institutional projects and extensive co-author network across Brown University departments including Neurology, Neurosurgery, and Pathology and Laboratory Medicine.

Eduardo Mercado IIIView profile

Professor

• Bioacoustics
• Cognitive Psychology
• Marine Ecology
• +5 more

Eduardo Mercado III is a Professor in the Department of Psychology at the University at Buffalo, College of Arts and Sciences. His research focuses on bioacoustics, cognitive psychology, and marine ecology, particularly the vocal behavior of humpback whales and its implications for understanding human impact on marine ecosystems. He is also known for his work in perceptual learning, autism spectrum disorder, and comparative cognition. Scientific Awards Guggenheim Fellowship Harvard Radcliffe Institute Fellowship Research Trends His recent publications emphasize bioacoustic analysis of humpback whale songs, including their spectral entropy, cyclical variations, and adaptive adjustments to anthropogenic noise. Additional work explores perceptual learning mechanisms in autism, neural network modeling for acoustic classification, and cognitive processes in canines and rodents. Projects Mercado’s “Singers as Sentinels” project combines acoustic analysis of humpback whale songs with public awareness initiatives about ocean noise pollution. The project will produce a book, Why Whales Sing and Dolphins Don’t , and a web-based interface for public engagement.

• Artificial Intelligence
• Multi-agent systems
• Machine learning
• +5 more

Toshiharu Sugawara is a Professor in the Department of Computer Science and Engineering at Waseda University's Faculty of Science and Engineering, School of Fundamental Science and Engineering, a position he has held since April 2007. With a Ph.D. in Engineering from Waseda University, his research spans multiple domains in artificial intelligence and multi-agent systems, maintaining active collaborations across international institutions and contributing significantly to the field through numerous publications and awards. Dr. Sugawara received his BS and MS degrees in Mathematics from Waseda University in 1980 and 1982, respectively, followed by his Ph.D. in 1992. Before joining Waseda University as faculty, he worked as a Research Scientist at NTT Laboratories from 1982 to 2007, with a visiting researcher position at the University of Massachusetts at Amherst in 1992-1993. He also held part-time lecturer positions at University of Electro-Communications (2003-2007), Waseda University (2004-2006), and Tokyo University of Agriculture and Technology (1990-1991). His research interests focus on artificial intelligence with particular expertise in multi-agent systems, machine learning, cooperation and coordination mechanisms, soft computing, computational social science, and social informatics. His work bridges theoretical foundations with practical applications in network management and information systems. Recent publications demonstrate a strong trajectory toward interpretable multi-agent reinforcement learning, efficient path planning algorithms, and modeling social behaviors in complex networks. His research group has made significant contributions to multi-agent path finding, cooperative task execution, and understanding virtual economies in social media platforms. Dr. Sugawara has received numerous prestigious awards including multiple Best Paper Awards at JAWS conferences (2014, 2015, 2018), ACM SAC 2015, and various research paper awards from Japanese academic societies. His work on multi-agent systems has been consistently recognized for its theoretical rigor and practical impact. As an advisor, Dr. Sugawara has mentored numerous students who have become prominent researchers in their own right, with many co-authoring papers that have received awards. His laboratory maintains strong collaborations with industry partners, particularly in the areas of network management and intelligent systems. Current research directions include developing interpretable multi-agent reinforcement learning frameworks, optimizing multi-agent coordination in constrained environments, and analyzing social dynamics in virtual economies.

• Quantum Computing
• Quantum Foundations
• ZX-calculus
• +7 more

John van de Wetering is an Assistant Professor at the Theoretical Computer Science group of the Informatics Institute, University of Amsterdam, working with the QuSoft research center. He co-authored the open-access book Picturing Quantum Software and developed the PyZX quantum compiler. His research spans quantum computation and quantum foundations, focusing on diagrammatic methods like the ZX-calculus and ZH-calculus. Quantum circuit optimization and verification Quantum foundations via algebraic/compositional methods Co-creator of PyZX His recent publications explore multi-qutrit systems, completeness of graphical calculi, and quantum state representations. Supervises students in quantum computing, including Lia Yeh and Sarah Li. Directs the new Master's program in Quantum Computer Science at UvA. Actively contributes to open-source projects and international conferences. Notable collaborations include Aleks Kissinger, Neil J. Ross, and QuSoft researchers. Uses GitHub for DiZX development (qudit extension of PyZX). No explicit scientific awards mentioned.

Matthias SchlottbomView profile

Associate Professor

• Numerical Analysis
• Computational Mathematics
• Radiative Transfer
• +4 more

Matthias Schlottbom is an Associate Professor specializing in Mathematics of Computational Science, with a focus on numerical methods and their applications in physics, biology, and engineering. His research integrates advanced computational techniques with interdisciplinary problems, including radiative transfer, photonic crystals, and chemotaxis modeling. Research Interests: Schlottbom’s work spans numerical analysis, finite element methods, and machine learning. He develops high-order discretization schemes, iterative solvers for anisotropic transport, and mathematical frameworks for biological network formation. Publications: Recent articles highlight his contributions to accelerating radiative transfer simulations, extending component mode synthesis for Helmholtz equations, and analyzing diffusion limits in kinetic models. His work often bridges computational mathematics with practical applications in photonics and multiscale systems. Collaborations: He actively collaborates on datasets for optical simulations, radiative transfer algorithms, and photonic crystal modeling, contributing to open-access repositories like 4TU.Centre and Zenodo. Activities: Schlottbom has organized workshops such as the Kinetic Theory Workshop in the Netherlands and delivered keynotes on residual minimization and data-driven methods for transport equations. Scientific Awards: No specific awards or fellowships are mentioned in the provided materials. Advising & Grants: Details about students, advising roles, or grant funding are not included in the available data.

• Ecohydrology
• Hydrology
• Landscape Ecology
• +6 more

Professor Dörthe Tetzlaff is a leading figure in ecohydrology, serving as Head of Department (A1) Ecohydrology at the Leibniz Institute of Freshwater Ecology and Inland Fisheries (IGB) and as Full Professor of Ecohydrology at Humboldt-Universität zu Berlin, Faculty of Mathematics and Natural Sciences, Geography Department. She also holds an Honorary Professorship at the University of Aberdeen, Scotland. Her work bridges theoretical hydrology with practical applications for water security and environmental management. Professor Tetzlaff's research focuses on ecohydrological processes, particularly using stable water isotopes to understand water cycling, catchment functioning, and landscape connectivity. Her work spans from pristine natural systems to complex urban environments, with particular emphasis on drought resilience, water security, and nature-based solutions. She has pioneered tracer-aided modeling approaches to quantify water storage, fluxes, and ages across the soil-plant-atmosphere continuum. Her publication record shows a clear trend toward increasingly sophisticated integration of multi-tracer approaches with ecohydrological modeling, with recent work focusing on urban systems, drought impacts, and nature-based solutions. The publications demonstrate expertise across hydrology, biogeochemistry, and ecological applications, with strong methodological development in isotope hydrology and modeling techniques. Polubarinova-Kochina Hydrologic Sciences Mid-Career Award of the American Geophysical Union AGU (2024) Water Resource Prize of the Rüdiger Kurt Bode Foundation (2024) Member of the Berlin-Brandenburg Academy of Sciences and Humanities (2023) Fellow of The European Academy of Sciences (2022) Fellow of the Geological Society of America GSA (2020) Professor Tetzlaff actively supervises numerous PhD students and postdoctoral researchers, with her group focusing on cutting-edge ecohydrological research. She leads multiple significant research projects including WETSCAPES2.0, ECCO, ISO-SCALE, and BiNatUr, which address critical questions about water security, climate change impacts, and nature-based solutions in urban environments. Her work is supported by substantial funding from various national and international sources. She leads the Ecohydrology research group at both IGB and Humboldt-Universität zu Berlin, which employs an integrative approach combining field measurements, isotope techniques, and advanced modeling to understand water dynamics across diverse landscapes. The group collaborates extensively with international partners across Europe, North America, and Asia, contributing to global understanding of hydrological processes.

Maria FällmanView profile

Professor

• Molecular microbiology
• Bacterial pathogenesis
• Infection biology
• +7 more

Maria Fällman is a Professor at the Department of Molecular Biology at Umeå University, where she also serves as Deputy Head of Department. She is affiliated with Molecular Infection Medicine Sweden (MIMS), a leading research center for molecular infection medicine in Sweden. Dr. Fällman's research focuses on understanding the molecular mechanisms behind bacterial adaptation to different environments, with particular emphasis on Yersinia pseudotuberculosis and Salmonella enterica Typhimurium. Her group investigates gene regulation critical for establishing and maintaining infections, bacterial stress responses, and the molecular mechanisms of the Type Three Secretion System (T3SS). The lab has developed advanced methods for RNA extraction from complex tissue samples and performs in vivo gene expression analyses. Her publication record shows consistent contributions to understanding bacterial pathogenesis, with recent articles in high-impact journals including Nature Communications, Science, and PLOS Pathogens. Her work spans from fundamental molecular mechanisms of bacterial virulence to computational approaches for analyzing pathogen stress responses. A significant contribution is the PATHOgenex database (http://www.pathogenex.org), containing gene expression data of over 30 human pathogens exposed to different stress conditions. Dr. Fällman leads the Maria Fällman Lab, which has made important discoveries including the finding that sub-lethal doses of Yersinia result in persistent infection in mice with reprogramming of bacterial gene expression. Current projects focus on stress response modeling and deciphering heterogeneous populations of infecting bacteria using single-cell RNA-seq.