جست‌وجوی استاد و پژوهشگر

Edriss S. Titiمشاهده پروفایل

استاد

• Nonlinear Partial Differential Equations
• Applied Mathematics
• Numerical Analysis
• +۵ مورد دیگر

Edriss S. Titi is a University Distinguished Professor and Arthur Owen Professor of Mathematics at Texas A&M University within the College of Arts & Sciences. His research focuses on nonlinear partial differential equations, applied mathematics, and geophysical fluid dynamics. He leads studies on fluid mechanics, atmospheric and oceanic dynamics, data assimilation, and control theory. His work often addresses mathematical rigor in modeling complex systems like climate dynamics and turbulent flows. Research Interests: Nonlinear PDEs and their applications Fluid dynamics and turbulence Data assimilation algorithms Climate and ocean modeling Infinite-dimensional dynamical systems Recent publications emphasize Navier-Stokes equations , primitive equations , and data assimilation in chaotic systems . His methodologies bridge theoretical analysis and computational modeling, with applications to weather prediction and geophysical flows. Collaborations include the Institute for Applied Mathematics and Computational Science (IAMCS) at Texas A&M. Notable contributions include rigorous analysis of global well-posedness for oceanic models and development of CDAnet, a physics-informed deep learning framework for fluid flow downscaling.

Liu Yongمشاهده پروفایل

استادیار

• Applied Econometrics
• Bayesian Econometrics
• Machine Learning
• +۴ مورد دیگر

Yong Liu is an Assistant Professor in the Department of Agricultural Economics at Texas A&M University. His research focuses on applied econometrics, Bayesian methodologies, machine learning, and agricultural policy with emphasis on crop insurance and risk management. He holds a Ph.D. in Agricultural Economics from the University of Guelph (2016), preceded by dual M.S. degrees in Economics and Agricultural Economics from Yunnan University and the University of Guelph, respectively, and a B.S. in Chemistry from Yunnan University. His research explores econometric techniques for agricultural policy evaluation, including causal inference methods and behavioral economics applications. Recent work analyzes climate change impacts on crop yields, the efficacy of insurance subsidies, and the integration of weather data into risk assessment models. Liu’s publications demonstrate a strong focus on improving crop insurance mechanisms through statistical innovations like Bayesian model averaging and spatial-temporal forecasting. His academic contributions span theoretical advancements in density estimation and practical applications in agricultural finance. While no specific awards or grants are listed, his active publication record indicates sustained research engagement in agricultural economics and quantitative methods.

Lucie Luمشاهده پروفایل

مدرس ارشد

• Asset Pricing
• Credit Risk
• International Finance
• +۱ مورد دیگر

Dr. Lucie Lu is a Senior Lecturer in the Department of Finance at the University of Melbourne, affiliated with the Faculty of Business and Economics. She joined the institution in 2023 and specializes in asset pricing, credit risk, international finance, and sustainable finance. Her research examines investor behavior in global markets, risk transmission mechanisms, and sustainable investment strategies. Dr. Lu holds a Ph.D. in Finance from McGill University, an MSc in Finance and Economics from the London School of Economics and Political Science, and a BA in Economics from Fudan University. Her work investigates topics such as heterogeneous investors' roles in risk-sharing, default risk propagation in credit markets, and institutional investors' preferences for sustainable investments. Her recent publications explore cross-market risk transmission, institutional investment dynamics, and structural credit modeling. While no specific awards are listed, her contributions to finance theory and empirical analysis are evident in her scholarly output. Dr. Lu does not currently list advisees or grants in the provided information. Her research extends to interdisciplinary areas, combining quantitative finance with global economic trends, reflecting her expertise in both theoretical and applied financial frameworks.

Jon Olav Vikمشاهده پروفایل

استاد

• Systems Biology
• Computational Biology
• Aquaculture
• +۷ مورد دیگر

Jon Olav Vik is a Professor at the Norwegian University of Life Sciences (NMBU), affiliated with the Department of Mathematical Sciences and Technology within the Faculty of Science and Technology. He leads the DigiSal project—"Towards the Digital Salmon: From a reactive to a pre-emptive research strategy in aquaculture"—funded under the Research Council of Norway’s Digital Life initiative. He is also a lead modeller in the GenoSysFat project, which aims to enhance omega-3 content in farmed salmon through integrated genomics and systems biology approaches. His research spans systems biology , computational physiology , genotype-phenotype modeling , and ecological dynamics . He works at the intersection of biology, mathematics, and computer programming, developing models to understand how genetics, nutrition, and environment interact in fish and ecological systems. His pedagogical focus includes biostatistics and programming in R, and he teaches courses such as STIN100, STIN300, and STAT100. The 15 most recent publications reflect a consistent focus on systems-level understanding in biology, particularly in salmon aquaculture, metabolic regulation, and genotype-phenotype relationships. These works appear in high-impact journals like Nature , Science , PLOS Computational Biology , and Journal of The Royal Society Interface , demonstrating interdisciplinary reach across computational biology, genomics, ecology, and biostatistics. Key themes include metabolic modeling, microbiome stability, lipidome remodeling, and sensitivity analysis in dynamic models. Jon Olav Vik has contributed to major collaborative efforts including the Infrastructure for Systems Biology Europe (ISBE) , where he helped develop frameworks for "modelling as a service." He has also authored book chapters and technical deliverables on systems biology and modeling practices. He actively supervises students and invites master’s thesis candidates with interests in quantitative biology. While no specific awards are listed, his leadership in national and international research projects underscores his scientific impact. His work supports both fundamental science and sustainable aquaculture innovation.

Margaret Kalacskaمشاهده پروفایل

دانشیار

• Remote Sensing
• Environmental Science
• Hyperspectral Imaging
• +۷ مورد دیگر

Margaret Kalacska is an Associate Professor in the Department of Geography at McGill University, leading the Applied Remote Sensing Lab. Her research focuses on advancing remote sensing technologies like hyperspectral imaging, Remotely Piloted Aircraft Systems (RPAS), LiDAR, and thermal imaging for environmental science and natural hazard monitoring. She has pioneered the use of RPAS-HSI systems, including developing Canada’s first fully operational RPAS-HSI for the Canadian Airborne Biodiversity Observatory (CABO) since 2018. Dr. Kalacska holds a PhD and MSc in Earth and Atmospheric Sciences from the University of Alberta. Her interdisciplinary work spans Canada, Brazil, Tanzania, Ghana, the Peruvian Amazon, Panama, Madagascar, and Costa Rica. Notable achievements include being the first Canadian woman to lead an airborne hyperspectral mission (MAC-13) in Costa Rica (2013) and receiving the Silver Medal from the Canadian Remote Sensing Society (2018). Her lab specializes in integrating cutting-edge remote sensing tools for biodiversity conservation, ecosystem monitoring, and disaster response. Recent projects include the Fish + Forest initiative studying aquatic habitats in Brazil and advancing custom RPAS for hyperspectral imaging. She also collaborates with the National Research Council of Canada and international organizations like NATO. Awards: Fessenden Prize (2014), Silver Medal (2018), Steacie Prize Nomination (2020) Key Projects: CABO, Fish + Forest , RPAS-HSI System Development Technologies: UAV LiDAR, Structure-from-Motion Photogrammetry, Satellite Data Validation Her research bridges environmental science and technology, emphasizing global applications in conservation and climate resilience.

Bruce Stephenمشاهده پروفایل

مدرس ارشد

• Data-Driven Methods
• Power Systems
• Smart Grids
• +۱۲ مورد دیگر

Bruce Stephen is a Senior Lecturer and Strathclyde Chancellor's Fellow in the Department of Electronic and Electrical Engineering at the University of Strathclyde, where he has been since 1999. His work lies at the intersection of data science and power systems engineering, with a strong focus on real-world industrial applications. His educational background includes a BSc in Aeronautical Engineering from the University of Glasgow (1997), an MSc from the University of Strathclyde (1998), and a PhD in Electronic and Electrical Engineering (2005) from the University of Strathclyde. Dr. Stephen's research centers on data-driven methodologies for solving complex engineering challenges in power systems, particularly under conditions of limited data or domain knowledge. His applications span the entire energy value chain—from generation (nuclear, wind, solar) to transmission, distribution, and end-use. He develops software solutions for condition assessment, anomaly detection, and predictive modeling to support asset management and future grid planning. Notably, he co-founded Silent Herdsman Ltd, a spin-out company applying intelligent systems to precision livestock farming. His recent publications highlight a strong trend toward advanced machine learning techniques such as transfer learning, surrogate modeling, and synthetic data generation (e.g., using CTGANs) to improve reliability and decision-making in power systems. These works emphasize explainability, uncertainty quantification, and scalability, particularly in renewable-rich and data-scarce environments. Dr. Stephen is currently the Principal Investigator on the EPSRC-funded Analytical Middleware for Informed Distribution Networks (AMIDiNe) project, aiming to identify barriers to Net Zero through improved data modeling of unmonitored networks. He has also contributed to major projects including EU FP7 ORIGIN, EPSRC APAtSCHE, AGILE, and Transactive Energy Supply Arrangements. He actively advises students and collaborates on interdisciplinary research. His professional activities include organizing the QFF Quarterly Forecasting Forum (2018) and delivering invited talks at industry workshops. He has supervised datasets and research involving structural health monitoring and industrial diagnostics. His work supports UN Sustainable Development Goals related to affordable and clean energy, industry innovation, and climate action.

Marco Seeberمشاهده پروفایل

استاد

• Public Policy
• Higher Education Governance
• Research Evaluation
• +۵ مورد دیگر

Marco Seeber is a Professor at the University of Agder's Department of Political Science and Management. He holds a PhD from the University of Chieti Pescara (Italy) and has previously worked at the University of Lugano (Switzerland) and Ghent University (Belgium). His research focuses on public policy, governance, and management with specialization in higher education systems, research evaluation, and science policy. Professor Seeber's research examines policy implementation, research metrics, peer review systems, academic careers, internationalization, and interdisciplinarity in higher education. He employs comparative and quantitative methodologies to analyze governance structures and policy impacts across different educational systems. He has received significant recognition including the Swiss Prize for Research in Education (2019) and fellowships from IEEE, AIUM, and AIMBE. As Co-Editor-in-Chief of the European Journal of Higher Education, he shapes scholarly discourse in his field. He currently coordinates the Horizon CSA project IANUS (2025-) and leads courses in organizational theory, research methodology, and leadership.

Kristy Robinsonمشاهده پروفایل

دانشیار

• Educational Psychology
• Student Motivation
• Classroom Environment
• +۴ مورد دیگر

Kristy Robinson is an Associate Professor in the Department of Educational and Counselling Psychology at McGill University , where she investigates classroom teaching practices and contextual factors that enhance student motivation and wellbeing. Her research program focuses on creating theoretical and empirical frameworks to support equitable instructional strategies for students' goal achievement. SSHRC-funded researcher FQRSC grant recipient Key Research Areas Motivational climate theory Expectancy-value-cost models STEM education equity Self-determination theory Emotion dynamics in learning Awards & Recognition Canadian Psychological Society President's New Researcher Award AERA Division C Outstanding Early Career Scholar AERA Motivation SIG Wilbert C. McKeachie Early Career Award Top-Producing Educational Psychology Scholar (2024) Research Platforms Director of MILES Lab (Motivation, Instructional, and Learning Experience Study) Developer of "mFlip" flipped classroom framework

Kishlay Jhaمشاهده پروفایل

استادیار

• Data Mining
• Machine Learning
• Natural Language Processing
• +۴ مورد دیگر

Kishlay Jha is an Assistant Professor at the University of Iowa's College of Engineering in the Department of Electrical and Computer Engineering. He is also a researcher at the Center for Bioinformatics and Computational Biology and the Iowa Initiative for Artificial Intelligence. PhD in Computer Science from University of Virginia (2022) Email: kishlay-jha@uiowa.edu Office: 3320 Seamans Center, Iowa City, IA 52242 Phone: (319) 467-0096 His research focuses on data science and artificial intelligence with emphasis on data mining, machine learning, and their applications in biomedical domains. He develops methodologies for transforming heterogeneous clinical, genomic, and bibliographic data into actionable knowledge for scientific advancement. Recent work includes: Semantic knowledge integration in biomedical language models Dynamic representation learning for evolving systems Hypergraph-based contrastive learning for healthcare applications Continual learning frameworks for time-sensitive domains Knowledge-guided representation learning Biomedical hypothesis generation He leads the Data Mining and Machine Learning Laboratory, where his team develops innovative tools for both biomedical discovery and general AI applications.

Youchang Wuمشاهده پروفایل

دانشیار

• Institutional Investors
• Corporate Finance
• Portfolio Management
• +۸ مورد دیگر

Youchang Wu is an Associate Professor of Finance and John B. Rogers Research Scholar at the Department of Finance, Lundquist College of Business, University of Oregon. His affiliations include the Cameron Center for Finance and Securities Analysis and the Master of Science in Finance program. Research Interests: Institutional Investors, Corporate Finance, Production Networks, Monetary Policy, and Macro Uncertainty Previous Positions: IPA Financial Economist at SEC, Assistant Professor at University of Wisconsin-Madison, University Assistant at University of Vienna, Junior Faculty Member at Peking University Education: PhD in Finance (University of Vienna), Master’s and Bachelor’s in Economics (Peking University) His research explores institutional investor behavior, production network dynamics, and corporate finance mechanisms. Recent projects examine private equity's environmental impact, pension plan investment performance, and trade credit implications in production networks. Scientific Awards: Engelbert Dockner Fellowship (2023) Consumer Protection Research Grant (University of Oregon, 2023) Dave Petrone Financial Literacy and Wellness Research Award (2022) Dean's College Service Award (2022) Wu has served as Associate Editor for China Finance Review International and Guest Editor for Pacific Basin Finance Journal . He has taught courses in derivatives, asset management, corporate finance, and international financial management.

Tamas Monaمشاهده پروفایل

پژوهشگر

• Epidemiology
• Plant Pathology
• Meteorology
• +۵ مورد دیگر

Dr. Tamas Mona is a Postdoctoral Research Associate in the Department of Plant Sciences at the University of Cambridge , affiliated with the Epidemiology and Modelling Group . His work focuses on environmental suitability models for large-scale epidemiological forecasting, particularly in wheat rust outbreaks across Africa, the Middle East, and Asia. Collaborations include the UK Met Office, CIMMYT, and institutions in Ethiopia, Kenya, Bangladesh, and Nepal. PhD in Environmental Sciences (2019), Eötvös Loránd University MSc in Meteorology (2013), Eötvös Loránd University BSc in Physics with Meteorology (2011), Eötvös Loránd University Research interests integrate meteorological applications with epidemiological models to predict crop disease outbreaks. Key projects involve tracking transmission pathways for stem rust pathogens and analyzing how irrigation creates green bridges for intercontinental pathogen spread. Publications emphasize environmental science and computational epidemiology . Current collaborations span Sub-Saharan Africa (EIAR, ATI, KARLO) and South Asia (BWMRI, NARC) through initiatives like the Global Food Security IRC . Modeling frameworks developed by Mona contribute to policy advisory systems for emerging pest threats, aligning with DEFRA and UK government strategies.

Damon Centolaمشاهده پروفایل

استاد

• Social Networks
• Behavior Change
• Network Diffusion
• +۵ مورد دیگر

Damon Centola is the Elihu Katz Professor of Communication, Sociology, and Engineering at the University of Pennsylvania, with appointments in the Annenberg School for Communication, the Department of Sociology, and the School of Engineering and Applied Sciences. He directs the Network Dynamics Group , focusing on how social networks drive behavior change and collective intelligence. Research Interests: Social networks, health behavior, AI ethics, climate action, and network diffusion. Notable Awards: Harrison White Outstanding Book Award (2019), US Patent #8713143 (2014), and fellowships at Stanford and Wharton. Recent Work Trends: Investigates AI's impact on medical decisions, structured networks for error reduction, and social norms in climate action. PhD Student: Calvin Isch (2023).

Frances Stewartمشاهده پروفایل

استادیار

• Wildlife Biology
• Conservation and Management
• Ecological Forecasting
• +۳ مورد دیگر

Frances Stewart is an Assistant Professor and Canada Research Chair in Northern Wildlife Biology at Wilfrid Laurier University's Faculty of Science, Department of Biology. She leads the WILDlab research group focusing on applied wildlife biology in northern regions through field projects, modeling, and community collaboration. She holds a PhD in Environmental Studies from the University of Victoria, and BScH and MSc degrees in Ecology from the University of Guelph. Her research specializes in quantifying wildlife responses to landscape changes using camera trapping, ecological forecasting, and spatial modeling. Current projects investigate species co-occurrence, habitat selection, and biodiversity conservation in Canada's rapidly changing northern ecosystems, with emphasis on integrating Indigenous knowledge. Publications (2019-2024) demonstrate strong focus on wildlife conservation, climate change impacts, and ecological modeling. Dominant themes include boreal caribou conservation, landscape connectivity, anthropogenic disturbance effects, and predictive ecology frameworks. Methodologically, her work combines field data with advanced statistical approaches to inform conservation decisions. Awards and Honors: Canada Research Chair in Northern Wildlife Biology Wilburforce Leader in Conservation Science Canadian Society of Ecology and Evolution Conference Presentation Award (2018) Advising and Grants: Supervises 2 postdoctoral fellows, 3 PhD candidates, and 4 MSc students Secured funding from NSERC, Weston Foundation, POLAR, and MITACS Emphasizes professional development through conference attendance and publication support Lab and Team: Leads the WILDlab (Wildlife Integration for Land use Decisions Lab) with active field projects across northern Canada. The team collaborates with government agencies (Natural Resources Canada), Indigenous communities, and international researchers to address wildlife management challenges in changing northern ecosystems.

Miguel Mahechaمشاهده پروفایل

استاد

• Ecosystem Responses to Climate Extremes
• Biogeography and Ecosystem Functioning
• Earth System Data Science
• +۴ مورد دیگر

Miguel Mahecha is Professor of Environmental Data Science and Remote Sensing at the University of Leipzig, where he serves as Institute Head of the Institute for Earth System Science and Remote Sensing. He is also affiliated with the Remote Sensing Centre for Earth System Research, a collaboration between Leipzig University and the Helmholtz Centre for Environmental Research (UFZ). Mahecha is a member of the German Centre for Integrative Biodiversity Research (iDiv) and serves as Principal Investigator in the Centre for Scalable Data Analytics and Artificial Intelligence. Additionally, he is a Fellow of the European Laboratory for Learning and Intelligent Systems and co-spokesperson for the National Research Data Infrastructure for Earth System Sciences (NFDI4Earth). Full Professor for Modelling Approaches in Remote Sensing, University of Leipzig (since 03/2020) Research Group Leader: Empirical Inference in the Earth System, Max Planck Institute for Biogeochemistry, Jena (12/2012 - 03/2020) PostDoc, Max Planck Institute for Biogeochemistry, Jena (10/2009 - 11/2012) PhD in Environmental Sciences, ETH Zürich (06/2006 - 09/2009) Diploma in Geoecology, Bayreuth University (10/2000 - 04/2006) Mahecha's research focuses on understanding ecosystem responses to climate extremes and human-environment relationships during these events. He investigates macro-ecological dynamics and ecosystem functioning using data-driven methods and high-dimensional Earth observations. A key contribution is his co-development of the Earth System Data Cube concept, which integrates empirical methods with theoretical understanding to analyze complex Earth system interactions. His work spans biogeography, ecosystem functioning, and advanced data science methodologies for environmental monitoring. His recent publications demonstrate a strong emphasis on analyzing compound climate extremes, particularly heatwaves and droughts, and their impacts on ecosystems. Mahecha has pioneered methods using Earth System Data Cubes to integrate diverse environmental datasets, enabling novel insights into biosphere-atmosphere interactions. His research increasingly incorporates artificial intelligence and machine learning approaches to understand spatiotemporal patterns in ecological systems, with applications in real-time forest monitoring and biodiversity assessment. Fellow of the European Laboratory for Learning and Intelligent Systems Co-spokesperson for NFDI4Earth (National Research Data Infrastructure for Earth System Sciences) Mahecha leads multiple significant research projects including Digital Forest (real-time forest monitoring), NFDI4BioDiversity, and XAIDA (extreme events: AI for Detection and Attribution). His work receives funding from diverse sources including EU, DFG, and Stiftungen Inland. He collaborates extensively with the German Centre for Integrative Biodiversity Research (iDiv) and the Centre for Scalable Data Analytics and Artificial Intelligence. His research group, Earth System Data Science (ESDS), focuses on developing methods to extract valuable information from long-term environmental observations to understand coupled Earth system dynamics. At the Remote Sensing Centre for Earth System Research, Mahecha's ESDS group investigates how ecosystem functions respond to climate extremes, societal vulnerability to environmental hazards, and nonlinear interactions in coupled Earth systems. The group leverages citizen science data, remote sensing observations, and advanced computational methods to address pressing environmental questions.

Marcell K. Petersمشاهده پروفایل

پژوهشگر

• Biodiversity
• Community Ecology
• Climate Change
• +۵ مورد دیگر

Dr. Marcell K. Peters is a Senior Academic Councillor at the Chair of Animal Ecology and Tropical Biology (Zoology III) at the University of Bremen. His research focuses on biodiversity patterns, ecosystem functioning, and climate-land use interactions in tropical and montane environments, with extensive fieldwork in East Africa and the Amazon. He leads projects under DFG and EU funding, including the UPSCALE initiative. Habilitation in Zoology (University of Würzburg, 2018) PhD in Biology (University of Bonn, 2008) Diploma in Biology (RWTH Aachen & University of Bonn, 2003) Research spans multi-taxa community ecology, army ants and ant-following birds, DNA barcoding applications, and climate change impacts on pollination networks. Google Scholar highlights recent work on climate-agriculture interactions in sub-Saharan Africa, trait-based community assembly, and network resilience in biodiversity hotspots. His publications emphasize elevational gradients, disturbance ecology, and functional diversity across Mount Kilimanjaro studies. Current affiliations include the DFG Research Unit Kilimanjaro and EU-funded UPSCALE project. He employs advanced methods like airborne LiDAR for biodiversity prediction and investigates nutrient use by ant communities across continents.