جست‌وجوی استاد و پژوهشگر

• Climate Science
• Atmospheric Dynamics
• Climate Reanalysis
• +۳ مورد دیگر

Dr Paul Berrisford is a researcher affiliated with the University of Reading and the European Centre for Medium-Range Weather Forecasts (ECMWF). His work focuses on atmospheric dynamics, climate reanalysis, and stratospheric-tropospheric interactions. He has contributed to major projects like the ERA-Interim reanalysis system, advancing data assimilation techniques and climate modeling. His research spans topics including temperature variability, energy transport, hydrological cycles, and polar climate processes. Key research interests include understanding climate dynamics through reanalysis datasets, investigating atmospheric circulation patterns (e.g., North Atlantic Oscillation), and assessing the impacts of stratospheric processes on tropospheric weather systems. His work bridges observational data analysis and modeling, with a focus on improving climate monitoring and prediction systems. Publications highlight contributions to global surface temperature trends, energy balance studies, and atmospheric conservation properties. Berrisford collaborates widely, with co-authors from institutions like ECMWF, the UK Met Office, and leading universities. His research aligns with broader efforts to enhance climate model accuracy and address challenges in climate variability analysis. Labs/Teams: Associated with the ECMWF Reanalysis Team and the University of Reading's Meteorology Department.

Xiaowei Jiaمشاهده پروفایل

استادیار

• Artificial Intelligence
• Data Mining
• Machine Learning
• +۳ مورد دیگر

Xiaowei Jia is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh, affiliated with the School of Computing and Information. He holds a Ph.D. from the University of Minnesota (supervised by Prof. Vipin Kumar) and B.S./M.S. degrees from the University of Science and Technology of China and SUNY Buffalo. His research focuses on integrating scientific theory with machine learning to address societal challenges in environmental science, hydrology, and climate modeling. Key research interests include physics-guided machine learning, spatio-temporal data mining, and fairness-aware models. He has developed frameworks like Physics-Guided Neural Networks (PGNN) and Spatial-Net for heterogeneous data, addressing issues in stream temperature prediction, crop yield modeling, and climate change projections. His work has been recognized with awards including the Best Dissertation Award (Minnesota) and multiple Best Paper awards in top conferences. Dr. Jia teaches advanced machine learning courses, emphasizing knowledge integration into AI systems. His lab collaborates extensively with domain scientists to advance applications in agriculture, hydrology, and environmental monitoring. Ongoing projects include high-resolution methane emission datasets (X-MethaneWet) and fairness-aware learning for resource distribution.

• Climate Science
• Meteorology
• Atmospheric Science
• +۳ مورد دیگر

Andy Turner is a Professor at the University of Reading, specializing in climate science and meteorology. His research focuses on monsoon dynamics, climate change impacts, and atmospheric processes, particularly in South and East Asia. He has contributed to over 130 publications, including studies on monsoon variability, aerosol effects, and extreme weather events. Turner's work explores mechanisms governing monsoon systems, climate model biases, and future projections under global warming scenarios. He collaborates extensively on initiatives like the INCOMPASS field campaign and contributes to IPCC assessments. Despite no explicit mention of awards or students in the provided texts, his research emphasizes interdisciplinary approaches to understanding climate systems and their societal implications.

• Atmospheric Science
• Climate Dynamics
• Meteorology
• +۳ مورد دیگر

Tim Woollings is a Professor at the University of Reading, specializing in atmospheric dynamics, climate variability, and their interactions with oceanic processes. His research focuses on jet streams, atmospheric blocking, storm tracks, and the impacts of climate change on weather patterns. He has extensively studied phenomena such as the North Atlantic Oscillation, extratropical cyclones, and the Gulf Stream's influence on atmospheric circulation. His work often utilizes advanced climate models and observational data to explore large-scale atmospheric patterns and their responses to anthropogenic forcing. Key research themes include the dynamics of mid- and high-latitude circulation, the role of stratospheric processes in weather variability, and the representation of climate change impacts in coupled ocean-atmosphere models. Woollings has contributed to understanding the modulations of jet variability across timescales, the mechanisms behind extreme weather events like blocking highs, and the implications of Arctic warming on European winters. His publications in journals like Journal of Climate , Climate Dynamics , and Nature Geoscience highlight his expertise in linking theoretical frameworks with empirical analyses. Recent work emphasizes projecting future changes in storm tracks and blocking frequencies, as well as evaluating the reliability of climate models in simulating these phenomena. His collaborative projects often involve international teams, addressing both fundamental and applied aspects of atmospheric science.

• Visual Neuroscience
• Autism Spectrum
• Neuro-ophthalmology
• +۲ مورد دیگر

Dr. David Crewther is an Adjunct Professor at Swinburne's School of Health Sciences, specializing in brain function assessment through electrophysiology and neuroimaging. His research investigates atypical visual processing in autism and amblyopia. Research: Focuses on visual attention networks, neural correlates of autism traits, and sensorimotor inhibition. Current projects include neurofeedback optimization and cross-modal sensory integration studies. Funding: Holds ARC grants including 'A grasp in time: Temporal interactions of dorsal/ventral visual streams' (2017-2023).

Helene Balslev Clausenمشاهده پروفایل

دانشیار

• Sustainability transitions
• Emergent technologies
• Participatory governance
• +۴ مورد دیگر

Helene Balslev Clausen is an Associate Professor at Aalborg University's Department of Culture and Learning within the Faculty of Social Sciences and Humanities. She leads the Creative Learning Lab established in 2016, focusing on participatory methods blending indigenous knowledge with emergent technologies. Her work addresses sustainability transitions through three core research streams: anthropology of emergent technologies in the Global South, participatory governance models, and creative ethnographic methodologies. Key projects include addressing climate change in Bangladesh's garment industry (2024–2029) and fostering female entrepreneurship in Uganda through socio-technical solutions (2023–2026). She has been recognized with awards including Teacher of the Year 2021 and a 2020 research prize for work on Mexican social entrepreneurship. Her interdisciplinary approach integrates problem-based learning frameworks with real-world sustainability challenges, emphasizing co-creation in both education and research. Education & Research Focus PhD in Anthropology Specialization in Tourism Sociology and Community Development Research Interests Dr. Clausen's work examines how localized knowledge systems interact with new technologies and global sustainability frameworks. She explores participatory processes that empower communities through creative methodologies like photovoice and drone technology, particularly in contexts such as Mexico's Pueblos Mágicos and Ugandan farming communities. Her research bridges cultural anthropology with policy analysis, emphasizing grassroots innovation and transnational mobility impacts. Grants & Collaborations Co-PI on projects funded by Danish Innovation Fund and Horizon Europe Global partnerships with institutions in Mexico, Uganda, Fiji, and Cuba Labs & Teams The Creative Learning Lab serves as a hub for experimental education and research, implementing initiatives in over 20 countries. It develops frameworks for integrating speculative futures thinking into sustainability education and policy design.

• Climate Science
• Meteorology
• Tropical Cyclone Dynamics
• +۳ مورد دیگر

Alex Baker is a prominent researcher in climate science and meteorology, focusing on tropical cyclones, climate modeling, and atmospheric dynamics. His work explores the impacts of model resolution on storm tracks, tropical cyclone intensification, and mid-latitude climate systems. Collaborating with institutions like the University of Reading and the UK Met Office, he investigates phenomena such as post-tropical cyclones affecting Europe, Atlantic-Pacific cyclone contrasts, and the role of SST gradients in climate biases. Key contributions include studies on cyclone lifecycle variability, extratropical transition processes, and the global decline in tropical cyclone frequency. His research bridges paleoclimatology through stalagmite analysis and modern climate projections, emphasizing high-resolution modeling's role in understanding extreme weather risks and climate change impacts. Research Interests: Tropical Cyclone Dynamics & Intensification Climate Model Resolution Sensitivity Mid-Latitude Storm Tracks Post-Tropical Cyclone Impacts Atlantic-Pacific Climate Variability Paleoseasonality Reconstruction Articles Overview: Recent work highlights the equatorward shift of storm tracks due to Hadley cell contraction, the realism of cyclone intensification in storm-resolving models, and the contrasting Atlantic-Pacific cyclone responses to multidecadal variability. His studies also address the limitations of low-resolution models in predicting European post-tropical cyclone risks and the mitigation of North Atlantic climate biases via increased resolution.

• Climate Science
• Atmospheric Dynamics
• Monsoon Systems
• +۳ مورد دیگر

Amulya Chevuturi is a researcher affiliated with the University of Reading's Department of Meteorology. Their work focuses on climate dynamics, monsoon systems, and seasonal forecasting, with a particular emphasis on South and East Asian weather patterns, Amazon Basin hydrology, and climate change impacts. Dr. Chevuturi has contributed to advancing seasonal prediction models such as ECMWF's SEAS5 and UK Met Office systems, analyzing monsoon onset predictability and hydrological cycle changes under global warming scenarios. Education includes a PhD in Atmospheric Science from Jawaharlal Nehru University (2015). Research interests span atmospheric teleconnections, climate model evaluation, and extreme weather events like cloudbursts in the Himalayas. They collaborate extensively with international institutions including Brazil's climate research networks and the UK's climate services initiatives. Key research trends in their articles include improving subseasonal-to-seasonal prediction accuracy, understanding aerosol impacts on monsoons, and modeling moisture transport mechanisms. They have pioneered studies on river level forecasting in the Amazon and Pearl River Delta regions, linking atmospheric dynamics with hydrological responses.

Asra Aslamمشاهده پروفایل

مدرس

• AI and Machine Learning
• Health Data Science
• Computer Vision
• +۶ مورد دیگر

Dr. Asra Aslam is a Lecturer in Data Science at the University of Sheffield's School of Information, Journalism and Communication. She holds a PhD in Computer Vision and Deep Neural Networks from the University of Galway, Ireland, and has extensive industry experience as a Machine Learning Research Scientist at mindtrace.ai. Currently leading the NIHR DynAIRx project's AI efforts and serving as General Chair of Women in Computer Vision (WiCV), she specializes in health data science, medical imaging, and smart city applications. **Research Interests**: Machine Learning for Healthcare (clinical codelists, electronic health records) Computer Vision (fire detection models, object detection systems) Transportation Analytics (London Underground rail asset identification) Data-driven medical equity projects **Grants & Collaborations**: £100k NIHR Team Science Grant on Medical Equity Alan Turing Institute collaboration with Transport for London Co-PI on University of Liverpool/Alan Turing Institute project **Notable Achievements**: 2024 Computing.co.uk Rising Star of the Year 2024 WeAreNovi Education Leader Award Organized 13th WiCV Workshop at CVPR 2024 Secured NVIDIA GPU grants for PhD research **Teaching**: Develops data science and health informatics modules focusing on AI applications in healthcare and smart cities.

Sudheer Chavaمشاهده پروفایل

استاد مدعو

• Credit Risk
• Banking
• Corporate Finance
• +۴ مورد دیگر

Sudheer Chava is an Adjunct Professor at Georgia Institute of Technology’s School of Computational Science and Engineering, concurrently serving as the Alton M. Costley Chair and Director of the Master of Science in Quantitative & Computational Finance (QCF) program. He also leads the Financial Services Innovation Lab. Chava holds a Ph.D. from Cornell University (2003), an MBA from Indian Institute of Management Bangalore, and prior industry experience as a fixed income analyst in India. His academic journey includes roles at University of Houston and Texas A&M before joining Georgia Tech in 2010. His research focuses on Credit Risk, Banking, Corporate Finance, and Financial Technology, with publications in top journals like the Journal of Finance, Journal of Financial Economics, and Review of Financial Studies. Notable achievements include the Ross Award (2008), Brattle Prize Finalist (2008), and multiple research grants such as FDIC-CFR and Morgan Stanley grants. He has taught courses ranging from Derivatives to Cases in Financial Crisis at both undergraduate and doctoral levels. Chava’s work explores intersections of finance and technology, including E-commerce’s impact on retail sectors, implications of minimum wage policies on small businesses, and applications of machine learning in financial risk prediction. His lab, the Financial Services Innovation Lab, drives research into fintech solutions and market dynamics. He also serves as an Associate Editor for the Journal of Banking and Finance and Journal of Credit Risk, highlighting his leadership in academic publishing.

• AI Ethics
• Social Media Analysis
• Online Communities
• +۳ مورد دیگر

Anna De Carvalho Guimarães is a researcher at KTH Royal Institute of Technology, Sweden, focusing on bridging AI technology development with regulatory frameworks like the EU AI Act. She holds a postdoc position under Tobias Oechtering, collaborating with Stockholm University and Scania. Previously, she was a Teaching Fellow at the University of Warwick (UK) and completed her PhD at Saarland University/Germany under Prof. Gerhard Weikum, with research at the Max Planck Institute for Informatics. Her research interests span AI ethics, privacy, transparency, and fairness in AI systems, alongside analyzing social media dynamics, online political discourse, and cloud computing performance. She has published extensively on controversial discussions in social platforms, community behavior in knowledge-sharing networks, and adversarial politics on Twitter. Her current project addresses misalignments between legal requirements and technical limitations in AI systems, aiming to create actionable compliance guidelines. Though no formal awards are listed, her work demonstrates significant contributions to interdisciplinary research between law and computer science. Her academic journey includes teaching roles and collaborative projects across Europe, maintaining an active research agenda that combines technical innovation with societal impact considerations.

• Hydrology
• Environmental Science
• Civil Engineering
• +۳ مورد دیگر

Dr. Sevvandi Kandanaarachchi is an Associate Professor in the School of Science at RMIT University's City Campus, Australia. Her research focuses on environmental data analytics, hydrology, and civil engineering applications. Key areas include water quality monitoring, sediment transport modeling, and algorithm development for environmental systems. Her work integrates machine learning with environmental science, addressing challenges in early event detection, anomaly identification, and predictive modeling for water resources. Notable contributions include frameworks for high-frequency sensor data analysis and meta-modeling approaches for stream turbidity prediction. Dr. Kandanaarachchi collaborates on interdisciplinary projects involving civil engineering, atmospheric sciences, and computational methods. She holds a PhD and has published extensively in peer-reviewed journals such as Hydrological Processes and PLOS One . No specific grants, awards, or student advisees are listed in the provided information.

Christine Duvalمشاهده پروفایل

دانشیار

• Nuclear Engineering
• Materials Science
• Chemical Engineering
• +۳ مورد دیگر

Christine Duval is an Associate Professor in the Department of Chemical and Biomolecular Engineering at Case Western Reserve University (CWRU), part of the Case School of Engineering. She is also a member of the Cancer Imaging Program at the Case Comprehensive Cancer Center. Her research focuses on developing advanced materials and processes for separating f-elements (lanthanides and actinides) with applications in nuclear fuel recycling, nuclear medicine, and rare earth element recovery from waste streams. Duval holds a PhD from Clemson University (2017) and a BS from the University of Connecticut (2011). Her research interests span membrane technology, materials science, and environmental engineering, with a particular emphasis on sustainable separations and nuclear waste management. Notably, her lab explores functionalized membranes and biomimetic materials for selective ion adsorption. Duval has received prestigious awards, including the Presidential Early Career Award for Scientists and Engineers (PECASE) in 2025, NSF CAREER Award in 2023, and the DOE Early Career Research Award in 2020. Her publications highlight innovations in membrane design, electrochemical sensing, and actinide/lanthanide separations. The Duval Lab actively recruits PhD and postdoctoral researchers for Fall 2025, focusing on wastewater treatment and critical mineral recovery. The lab emphasizes community outreach, including educational events and collaborations with national labs like Argonne National Lab. Awards and honors include recognition for mentoring, teaching, and contributions to the field of separations science. Duval’s work bridges fundamental research with practical applications, addressing global challenges in energy sustainability and environmental protection.

Yi Huangمشاهده پروفایل

استاد

• Atmospheric Radiation
• Remote Sensing
• Climate Dynamics
• +۳ مورد دیگر

Yi Huang is a Professor in the Department of Atmospheric and Oceanic Sciences at McGill University, Canada. His research focuses on atmospheric radiation and its role in climate and weather variability, with emphasis on remote sensing techniques and radiative feedback analysis. He leads a research group integrating satellite observations and numerical modeling to address climate and weather challenges. His group actively collaborates with international institutions and has supervised numerous graduate students and postdocs. Key research areas include radiative kernel analysis, stratospheric water vapor dynamics, and Arctic climate feedbacks. The group maintains an active website with publication lists and research data. Education: Ph.D. in Atmospheric and Oceanic Sciences (not explicitly detailed in text), but mentions visiting at McGill (2018-2020). Research interests span atmospheric radiation, radiative remote sensing, and climate feedback mechanisms. Recent work includes studies on Arctic radiative processes, spectral radiative kernels, and stratospheric water vapor impacts on global circulation patterns. The Huang Group collaborates with institutions like Environment and Climate Change Canada and has secured grants for climate monitoring projects. Graduate students and postdocs are involved in satellite data analysis, climate model evaluation, and field campaigns. Labs/Teams: The group operates within McGill's Atmospheric and Oceanic Sciences department, leveraging advanced computational facilities and satellite datasets. Collaborations include international initiatives like the HiSRAMS instrument development project.

Félix Santiago-Collazoمشاهده پروفایل

استادیار

• Compound Flood Modeling
• Hydrologic and Hydraulic Modeling
• Coastal Watershed Analysis
• +۴ مورد دیگر

Félix Santiago-Collazo is an Assistant Professor at the University of Georgia's School of Environmental, Civil, Agricultural & Mechanical Engineering. His research focuses on compound flood modeling, hydrologic and hydraulic processes in coastal watersheds, and numerical simulation of environmental systems. He holds a Ph.D. and is a licensed Professional Engineer (P.E.). His work integrates hydrodynamic modeling, field data, and computational techniques to address challenges in flood resilience, plastic transport dynamics, and tropical cyclone impact assessments. Notable projects include island-scale flood modeling for Puerto Rico, low-gradient estuary forecasting in Florida, and development of reduced-physics numerical frameworks for coastal hazards. Publications emphasize multi-hazard approaches for flood risk mitigation, with contributions to ASCE manuals and interdisciplinary studies linking inland-to-ocean litter transport. Recent trends highlight collaboration between physical experiments and advanced computational methods to improve disaster preparedness and environmental management. He advises no listed students but contributes to grants focused on coastal resilience and environmental engineering applications. His research labs focus on hydraulic infrastructure resilience and numerical modeling tools for compound hazard assessment.