جست‌وجوی استاد و پژوهشگر

• Bayesian Statistics
• Expert Knowledge Elicitation
• Robust Analyses
• +۳ مورد دیگر

Professor John Paul Gosling is an applied statistician affiliated with the Department of Mathematical Sciences at Durham University . With a background in industry, academia, and the civil service, his work bridges statistical theory and real-world applications, particularly in criminal justice, toxicology, and climate science. Education: MMath in Mathematics (University of York, 1998–2002), PhD in Statistics (University of Sheffield, 2002–2005) Current Role: Professor in Statistics, focusing on human interaction with statistical information His research interests include: Bayesian Statistics : Developing models for complex systems Expert Knowledge Elicitation : Structuring expert input for risk assessment Uncertainty Quantification : Analyzing and communicating uncertainty in data Machine Learning Integration : Combining statistical inference with AI for decision-making Key trends from his recent articles include: Application of Voronoi Tessellations in Bayesian regression and classification Development of emulation techniques for computationally intensive models Focus on legal and public health domains Integration of copula methods for dependent variables He actively supervises PhD students in Bayesian theory and machine learning interfaces and contributes to Statistics research at Durham University.

• Maize genetics
• Genomics
• Quantitative genetics
• +۵ مورد دیگر

Addie Thompson is an Assistant Professor at Michigan State University's College of Agriculture & Natural Resources , affiliated with the Department of Plant, Soil and Microbial Sciences , Plant Resilience Institute , and Plant Breeding, Genetics, and Biotechnology Program . Her expertise spans maize genetics, genomics, and phenomics, with a focus on genotype-environment interactions. B.S. from Iowa State University Ph.D. from University of Minnesota Postdoctoral work at University of Minnesota & Purdue University Research focuses on drought stress adaptation , high-throughput phenotyping , and quantitative genetics in maize and sorghum systems. Current projects include computational modeling of crop traits, field phenotyping technologies, and cross-species stress response analysis. She leads maize genetics research while participating in national initiatives like the Genomes-to-Fields Initiative , with recent publications on phenotypic plasticity, hyperspectral imaging applications, and climate-resilient breeding strategies. Her work connects molecular genetics to agricultural productivity through advanced data modeling and field experimentation. Thompson directs the Thompson Maize Lab which focuses on: Maize and sorghum genotype-environment interactions Phenomics technologies for trait analysis Development of computational breeding tools Climate resilience trait discovery Historical genetic diversity patterns Agricultural workforce development

Chaitanya Patilمشاهده پروفایل

مدرس

• Marine Engineering
• Artificial Intelligence
• Digital Twins
• +۵ مورد دیگر

Dr. Chaitanya Patil is a Lecturer in the Department of Naval Architecture, Ocean and Marine Engineering at the University of Strathclyde, UK, advancing intelligent maritime systems through AI-integrated digital twin development for marine operational resilience. His educational background includes: PhD in Optimization of performance and emission in real driving from Universitat Politecnica de Valencia (2021) MSc in Reciprocating engines from Universitat Politecnica de Valencia (2016) MSc in Automotive Engineering for Sustainable Mobility from Université Bourgogne Franche-Comté (2015) B.Tech in Industrial Engineering from Veermata Jijabai Technological Institute (2012) Research focuses on three interconnected domains: Sensing and Perception (neuromorphic underwater object detection via sensor fusion), Cognition (AI-driven diagnostics/prognostics for predictive maintenance), and Decision-Making (intelligent control for emission reduction and engine optimization). His work directly supports UN Sustainable Development Goals for sustainable industry and climate action. Recent publications demonstrate a cohesive trajectory applying machine learning to marine engine health assessment, emphasizing feature extraction techniques and digital twin validation for fault diagnosis in maritime systems. Funding includes EPSRC, Innovate UK, and SPF grants, with current leadership as Co-investigator on the EPSRC IAA project Neuromorphic Sensor Fusion for Under Water Object Detection (SENSE) (2022-2026) and Principal Investigator on multi-sensor deep sea exploration systems. He actively supervises PhD students in intelligent marine systems research. With professional experience across UK, Spain, France, China and India, he maintains extensive industry collaborations through conference presentations including Digitalisation of Maritime Industry in India (2023) and Application of AI in Engineering symposia (2022).

Ana Lucicمشاهده پروفایل

استادیار

• Interpretable Machine Learning
• Artificial Intelligence
• Earth System Science
• +۳ مورد دیگر

Ana Lucic is an Assistant Professor in Artificial Intelligence at the University of Amsterdam , with a joint appointment between the Institute for Logic, Language and Computation and the Informatics Institute . Her research focuses on interpretable machine learning applications for scientific discovery and societal impact. Formerly at Microsoft Research AI for Science and Partnership on AI PhD in Explainable Machine Learning from University of Amsterdam (2022) BSc/MSc in Mathematics from McMaster University Research Highlights: Develops mechanistic interpretability methods for deep learning architectures. Created Aurora , a foundation model for Earth system forecasting outperforming traditional operational models in air quality prediction and tropical cyclone tracking. Pioneers Clifford-Steerable CNNs for geophysical data analysis. Actively hiring PhD students for AI transparency research . Collaborative Networks: Contributions to ELLIS Summer School and ICML workshops . Collaborates with Microsoft Research AI for Science team on climate-related ML projects. Involved in organizing TerraBytes workshop at ICML 2025. Recent Advancements: Key role in publishing Aurora model in Nature (2025), demonstrating superior performance in Earth system forecasting. Supervises Ege Erdogan , new PhD student focused on mechanistic interpretability. Actively contributes to open-source AI development through GitHub repositories and technical discussions.

David Rothamerمشاهده پروفایل

استاد

• Combustion Engineering
• Internal Combustion Engines
• Renewable Fuels
• +۳ مورد دیگر

David Rothamer is the Robert Lorenz Professor and Director of the Engine Research Center in the Department of Mechanical Engineering at the University of Wisconsin-Madison. As Associate Dean for Research in the College of Engineering, he leads research strategy, core facility management, and faculty recruitment. His expertise spans combustion, internal combustion engines, renewable fuels, and optical diagnostics. He earned his PhD from Stanford University (2008) and has been at UW-Madison since 2008, receiving an NSF CAREER Award in 2011. Education PhD, Mechanical Engineering, Stanford University, 2008 MS & BS, Mechanical Engineering, University of Wisconsin-Madison, 2002 & 2000 Research Interests Rothamer’s work focuses on optimizing engine performance with renewable fuels using advanced optical diagnostics. His lab develops laser-based techniques to study combustion processes in IC engines, with recent emphasis on sustainable aviation fuels and aerosol filtration during the pandemic. Awards & Recognition ASHRAE Best Paper Award (2022) for aerosol transmission research Robert Lorenz Professorship (2020) SAE Ralph R. Teetor Educational Award (2013) Grants & Collaborations Recipient of $11.5M Army funding for hybrid-electric engine research (2020). Collaborates with industry partners on fuel blending, combustion diagnostics, and emission reduction technologies. Labs & Affiliations Leads the Engine Research Center and holds an affiliation with the Nuclear Engineering & Engineering Physics department. His team operates a state-of-the-art engine lab capable of simulating extreme environmental conditions.

YongJiang Zhangمشاهده پروفایل

دانشیار

• Plant Physiology
• Climate Change
• Environmental Stress Physiology
• +۳ مورد دیگر

Dr. YongJiang (John) Zhang is an Associate Professor of Plant Physiology at the School of Biology and Ecology, University of Maine . His research focuses on plant responses to environmental stresses and climate change, particularly in wild blueberries and trees. His lab uses interdisciplinary approaches including field studies, UAV sensors, and controlled experiments. Dr. Zhang holds a Ph.D. from the University of Miami (2012) and Chinese Academy of Sciences (2011). Education: Ph.D., University of Miami, 2012 Ph.D., Chinese Academy of Sciences, 2011 Research Interests: Plants' physiological and structural adaptations to climate change, including water transport mechanisms, drought tolerance, and carbon balance. Key themes include wild blueberry resilience in Maine, tropical tree physiology, and precision agriculture techniques like UAV-based monitoring. His work integrates multi-scale approaches from lab experiments to ecosystem-level modeling. Lab & Collaborations: The Zhang Lab is located in Murray Hall and Hitchner Hall. Current research includes wild blueberry climate resilience, water-use efficiency of Maine forests, and novel technologies for crop management. Dr. Zhang collaborates with institutions like Harvard University and the Climate Change Institute. Grants & Advising: Oversees multiple graduate students and undergraduate researchers. Recent projects include NSF-funded studies on climate impacts and USDA grants for precision agriculture. Advises on topics like UAV applications and drought resistance genetics.

Mario Harperمشاهده پروفایل

استادیار

• Machine Learning
• Data Science
• Robotics
• +۲ مورد دیگر

Mario Harper is an Assistant Professor in the Department of Computer Science at Utah State University. His research emphasizes Machine Learning, Data Science, Robotics, and their intersections with Finance and Artificial Intelligence. He specializes in autonomous systems, energy-efficient robotics, and AI-driven solutions for transportation and urban sustainability. His work includes developing tools like simulators for electric vehicle systems and stealth-centric navigation algorithms inspired by biological systems. Key research areas include multi-robot coordination, reinforcement learning applications in robotics, and algorithmic approaches to environmental and economic challenges. He has contributed to projects like POSEIDON-SAT for satellite-based fishing vessel detection and electrified transportation equity analysis in urban settings. His publications span topics from trajectory planning in legged robots to AI modeling for economic systems. Beyond research, he designs interactive visualization tools to support policy decisions on sustainable transportation infrastructure. No scientific awards are explicitly listed in the provided information. Mario Harper’s advising and grants focus on robotics, energy systems, and AI applications, though specific student advisees or grant details are not detailed here. He collaborates on projects involving lab tools such as the Unknown Building Exploration Simulator (UBES) and Stealth Centric Autonomous Robot Simulator (SCARS), advancing robotic autonomy in unstructured environments.

Jonathan E. Martinمشاهده پروفایل

استاد

• Synoptic Meteorology
• Atmospheric Dynamics
• Jet Stream Variability
• +۳ مورد دیگر

Jonathan E. Martin is a Professor in the Department of Atmospheric and Oceanic Sciences at the University of Wisconsin–Madison since 1994. He received his Ph.D. in Atmospheric Sciences from the University of Washington in 1992. Research Focus: Mid-latitude cyclones, jet stream dynamics, and weather-climate interactions Key Methods: Multi-scale observational analysis, high-resolution mesoscale modeling, potential vorticity diagnostics Recent Projects: Jet stream waviness trends, subtropical-midlatitude cyclone transformation, snow cover-cyclone feedback His 2025-2024 publications examine extratropical cyclone precipitation distribution, Pacific basin rapid cyclogenesis, and Earth system model validation for cyclone occlusion. Earlier work (2023-2019) addresses: Jet superposition climatology Self-organizing map analysis of jet variability Cyclone-induced Southern Hemisphere waviness Nonlinear jet retraction mechanisms Tornado outbreak jet influences Historical cold pool contraction trends Awarded the 2021 Atmospheric Sciences Librarians International Choice Runner Up for his historical meteorology work, he also authored the textbook Mid-Latitude Atmospheric Dynamics: A First Course (2013). His research spans cyclogenesis, frontogenesis, and climate change impacts on jet streams, with applications in extreme weather forecasting and climate modeling validation.

Manuel J. Rodriguezمشاهده پروفایل

استاد

• Drinking Water Quality Management
• Land Use Planning
• Climate Change Adaptation
• +۳ مورد دیگر

Manuel J. Rodriguez is a Full Professor at the École supérieure d'aménagement du territoire et de développement régional (School of Land Use Planning and Regional Development) at Université Laval, Canada. Holder of the NSERC Industrial Research Chair in Drinking Water Quality Management and Monitoring, he specializes in integrated water quality management from watersheds to urban distribution systems. His work addresses source protection, spatio-temporal water quality analysis, and decision-support tools for municipalities. BSc in Civil Engineering MSc in Land Use Planning and Regional Development PhD in Environmental Engineering Postdoctoral work in England and France His research program emphasizes climate change adaptation, land use planning impacts, and machine learning applications for predicting water quality parameters. Recent publications focus on disinfection byproduct (DBP) management, contamination monitoring, and computational tools for water security. He has supervised over 80 doctoral, master's, and postdoctoral students. Professor Rodriguez has received the 2013 Université Laval Teaching Excellence Award and leads collaborations with entities like the City of Quebec, Canada First, and WaterShed Monitoring. His 2024-2025 articles highlight trends in climate-water interactions, DBP control, and AI-driven water quality assessment. NSERC Industrial Research Chair Active in 2025 publications Teaching excellence laureate He has held administrative roles including Director of CRAD, ÉSAD, and doctoral/master programs in Land Use Planning. His work spans 200+ peer-reviewed articles and 400+ conference presentations, addressing global water challenges from Arctic communities to tropical basins.

Markus Kellerمشاهده پروفایل

استاد

• Viticulture
• Grape Physiology
• Irrigation Management
• +۴ مورد دیگر

Markus Keller is a **Château Ste. Michelle Distinguished Professor** in the **Department of Horticulture and Landscape Architecture** at **Washington State University (WSU)**, affiliated with the **Prosser Irrigated Agriculture Research and Extension Center (IAREC)**. His research focuses on grapevine physiology, viticulture production systems, and environmental stress management. He holds a **Ph.D. (1995)** and **M.S. (1989)** in Agricultural Engineering from the **Federal Institute of Technology (ETH Zurich), Switzerland**. **Research Interests**: Dr. Keller’s work addresses crop physiology, irrigation strategies, cold hardiness, berry shrivel, and mechanized viticulture. His projects include developing deficit irrigation frameworks, understanding water movement in berries, and predicting frost damage risks using machine learning. He collaborates with industry partners like the USDA and Washington wine producers. **Key Contributions**: His studies on grapevine water relations, berry development disorders, and cold tolerance have advanced sustainable viticulture practices. He leads teams investigating precision agriculture tools for vineyards, including hyperspectral imaging and decision-support systems. **Grants & Funding**: Supported by grants from USDA, Washington wine tax, and juice processors. His work integrates applied research with grower education on frost protection and yield optimization. **Lab & Collaborations**: Directs research at WSU’s Viticulture and Enology program, collaborating with international teams on climate resilience and grapevine health. Mentors Ph.D. and M.S. students in experimental design and field studies.

Susan D Hovorkaمشاهده پروفایل

استاد پژوهشی

• Geologic Carbon Sequestration
• Environmental Science
• Subsurface Geology
• +۳ مورد دیگر

Susan D. Hovorka is a Research Professor at the Bureau of Economic Geology, Jackson School of Geosciences at The University of Texas at Austin. She holds a BA in Geology from Earlham College and MA/PhD from the University of Texas. Her work focuses on geologic sequestration of CO₂ to mitigate climate change, leading projects like the Gulf Coast Carbon Center and the SECARB ‘Early Test’. She also engages in K-12 science education through programs like STORECO₂NOW. Research Interests: Geologic carbon sequestration in deep sedimentary environments Subsurface CO₂ storage efficiency and monitoring Public outreach and pre-college STEM education Articles Trends: Focus on CO₂ storage site selection, leakage detection, and regulatory frameworks Integration of geomechanics, sensor technology, and machine learning for monitoring Assessment of CCS potential in offshore and onshore environments Scientific Awards: 2008: Texas Monthly’s 35 People Shaping the Future 2006: Association for Women in Communications Award 2005: Jackson School’s Joseph C. Walter Jr. Award Advising & Grants: Supervised 4 graduate students (e.g., Melianna Ulfah, Madeleine Laidlaw) Principal Investigator of Gulf Coast Carbon Center (funded by DOE-NETL, industry partnerships) Labs/Teams: Leads the Gulf Coast Carbon Center, a hub for applied CO₂ sequestration research Co-developer of the Frio Pilot Test and SECARB projects

Serge Guillasمشاهده پروفایل

استاد

• Functional Data Analysis
• Uncertainty Quantification
• Environmental Statistics
• +۴ مورد دیگر

Professor Serge Guillas is a faculty member at the University College London (UCL) Department of Statistical Science. His research focuses on functional data analysis, uncertainty quantification, environmental statistics, and emulation of complex computer models. He leads the NERC consortium on Uncertainty Quantification of Natural Hazards and has held roles such as Work Package Leader for quantifying uncertainties in natural hazard models. His work integrates statistical methods with geophysical and climate modeling, emphasizing tsunami risk analysis, climate dynamics, and ozone exposure studies. Education: PhD in Statistics from Paris 6 University (2001), followed by roles at the University of Chicago, Georgia Institute of Technology, and UCL. Current roles include teaching STAT1006 and STAT7001 courses. Research interests span functional regression, spatial data analysis, and probabilistic hazard modeling. Recent work explores machine learning-driven climate models, ozone exposure health impacts, and real-time data assimilation software (ParticleDA.jl). He collaborates globally, including with institutions in Georgia, Italy, and Indonesia, to advance tsunami modeling and disaster risk reduction. Key awards include ESRC-DFID-NERC funding, MAPS Faculty Postgraduate Research Prize (for student Ah Yeon Park), and leadership roles in SIAM’s Uncertainty Quantification group. Active in mentoring PhD students and securing interdisciplinary grants. Labs/Teams: Involved with the UCL Institute for Risk & Disaster Reduction and leads statistical emulation efforts in climate and geophysical modeling. Collaborates on fusion reactor design (ExCALIBUR project) and global temperature uncertainty quantification (GETQUOCS initiative).

William Panمشاهده پروفایل

استاد

• Spatial Analysis
• Demography
• Land Use Science
• +۷ مورد دیگر

William Pan is the Elizabeth Brooks Reid and Whitelaw Reid Professor of Population Studies and Global Environmental Health at Duke University, holding joint appointments at the Duke Global Health Institute (DGHI) and the Nicholas School of Environment. He also serves as Adjunct Professor in the Department of International Health at Johns Hopkins Bloomberg School of Public Health. With over 20 years of experience, Pan leads large, multi-institutional research teams focused on human-environment dynamics affecting health in low- and middle-income countries, primarily in Latin America's Amazon region. His research spans several critical areas: mercury and chemical exposures from artisanal gold mining; forecasting vector-borne disease risks using climate, land use, and surveillance data; migration's role in infectious disease transmission; lead exposure among hunters; and nature-based solutions for agroforestry, climate resilience, and disease mitigation. Pan received his DrPH from UNC-Chapel Hill with a focus on biostatistics, demography, and spatial analysis, and holds an MPH from Emory University. Pan's laboratory has produced significant research on malaria forecasting systems now adopted by two countries, mercury pollution impacts in gold mining communities, and environmental health in the Amazon. His team has secured major grants from NIH, NASA, and Conservation International for projects including ELIMINAR-Malaria and satellite-informed malaria early warning systems. NASA: Developing an Early Warning System for Malaria Risk in the Amazon Amarakaeri Reserve: Impacts on Human Health and the Environment from Resource Extraction Mercury Pollution & the Madre de Dios watershed research Pan has mentored numerous doctoral students, post-doctoral fellows, and master's students who have gone on to positions at institutions including Johns Hopkins University, CDC, and various public health organizations. His work bridges academic research with practical applications, serving on expert panels including the MINAMATA Effectiveness Evaluation Panel and Technical Advisory Group for the Tripartite One Health initiative.

Sukumar Natarajanمشاهده پروفایل

استاد

• Building Energy Modeling
• Occupant Behavior
• Climate Change Adaptation
• +۲ مورد دیگر

Sukumar Natarajan is Professor in the Department of Architecture & Civil Engineering at University of Bath, where he directs the EPSRC Centre for Decarbonisation of the Built Environment (dCarb) and serves as Deputy Director of the Centre for Energy and the Design of Environments (EDEn). His research examines building energy modeling, occupant behavior, and climate adaptation strategies. Natarajan's work addresses thermal comfort in vulnerable communities, with field studies in refugee camps and informal settlements. Current projects include developing low-cost energy advisors (ENLITEN) and climate-resilient shelter design (CREST). His team creates high-resolution weather datasets for building simulation under climate change. He leads international collaborations on sustainable building design, including Newton Fund projects on peak energy reduction in India. Recent work investigates overcooling phenomena in hot climates and adaptive comfort standards. Natarajan contributes to climate-resilient design guidelines and assesses social media for heat wave detection. His group maintains open datasets on thermal comfort in refugee shelters.

• Applied Econometrics
• Agricultural Land Markets
• Renewable Energy (Wind Energy)
• +۳ مورد دیگر

Dr. Matthias Ritter is a Senior Researcher at the University of Tübingen's Faculty of Economics and Social Sciences, holding a position at the Chair of Marketing. Previously, he served as an Associate Professor and Assistant Professor at Jönköping International Business School (Sweden) and held roles including Junior Professor of Quantitative Agricultural Economics at Humboldt University Berlin. He earned his PhD in Economics (Dr. rer. oec.) from Humboldt University Berlin in 2011, focusing on econometrics and economic statistics. Education: PhD in Economics, Humboldt University Berlin (2011) Postdoctoral Researcher, Technical University Berlin (2013) Diploma in Mathematics (university unspecified) Research Interests: Ritter’s work centers on applied econometrics, agricultural land markets, renewable energy (especially wind energy), and weather risk management. His research bridges economic theory with practical applications in climate change adaptation, land valuation, and energy policy. Recent studies include analyzing bargaining power in agricultural land markets and modeling wind energy potential in urban areas. Key Awards: Best Paper Award (GEWISOLA, 2021) Humboldt Award for Excellence in Teaching (2020 shortlist) Stifterverband Prize (2018) for land market research Finanzkompass Innovation Award (2013) for dissertation Teaching & Advising: Ritter teaches courses in data science, agricultural economics, and renewable energy economics. He has advised students in both bachelor’s and master’s thesis seminars but no named advisees are listed. His research has explored interdisciplinary topics such as wind turbine efficiency, climate modeling, and digital teaching strategies post-pandemic. Labs/Teams: Engaged with agricultural economics and energy policy research groups, focusing on collaborative projects involving land markets, renewable energy integration, and climate risk assessment.