Professor Inge Hoff is affiliated with the Norwegian University of Science and Technology (NTNU) in the Department of Civil and Environmental Engineering, where he has served since 2009. Prior to this, he held roles as senior researcher and research leader at SINTEF. Research Interests : Materials for road construction, frost protection, laboratory testing, pavement dimensioning, road rehabilitation, state development modeling, ground-penetrating radar surveys, and concrete/natural stone coverings. Students : Mentors active PhD fellows Lisa Hannasvik, Arman Hamidi, Clara Weber, and Shoiab Ahmad. Teaching : Coordinates courses like TBA4204/BYGT1102 Transport Infrastructure , BYGT2204 Road and Railway Construction , and BA8600 Pavement Structure Dimensioning . Recent publications highlight his expertise in granular material behavior, asphalt durability under climate stressors, and advanced structural assessment techniques. Collaborations with international researchers and presentations at major conferences (TRB, International Conference on Bituminous Mixtures) demonstrate his ongoing contributions to road engineering.
Professor Anne Verhoef is a leading academic at the University of Reading, specializing in environmental and hydrological sciences. Her research focuses on soil-plant systems, climate change impacts, groundwater dynamics, and remote sensing applications in ecological modeling. She collaborates internationally on projects like GEWEX and AMMA, advancing understanding of global hydrological cycles and land-atmosphere interactions. Key Research Areas: Hydrological modeling and prediction Climate change adaptation in semi-arid regions Soil health and pedotransfer functions Evapotranspiration dynamics in tropical ecosystems Remote sensing for biodiversity and water resource assessments Her work integrates field observations, satellite data, and numerical models to address challenges in water resource management, flood mitigation, and sustainable agriculture. She has published widely in top journals such as Reviews of Geophysics , Water Resources Research , and Nature Reviews Earth & Environment . Professor Verhoef contributes to interdisciplinary initiatives, including climate adaptation strategies in transboundary regions and improving land surface models for global Earth system simulations. Her research emphasizes bridging gaps between observational data and predictive frameworks to inform policy and environmental decision-making.
Xiaoping Lu is an Associate Professor at the School of Mathematics and Applied Statistics, University of Wollongong, Australia. She has served as Academic Program Director for the Bachelor of Mathematics (Advanced) program since 2008 and holds an ORCID identifier (0000-0003-1090-8437). Her research focuses on applied mathematics and financial mathematics, particularly in option pricing, stochastic volatility models, and computational finance. Research Themes: Transaction cost modeling, regime-switching financial markets, numerical methods for PDEs, utility-indifference valuation, and stochastic optimization algorithms. Awards: 2024 AustMS-WIMSIG Anne Penfold Street Award 2024 Cheryl E. Praeger Travel Award Leadership: President of the Asia Pacific Consortium of Mathematics for Industry (APCMfI) since 2024; leadership roles in ANZIAM and WIMSIG committees. Teaching: Coordinated courses like MATH142, MATH141, and MATH283; currently available for PhD supervision in topics including financial derivatives and stochastic liquidity risk. Funding: Contributed to grants like 'The AI Tutor' (2024) and industry partnerships for advanced mathematics education.
Yangyang Zhao is a Research Fellow at Princeton University, affiliated with the Resplandy Research Group. His work focuses on climate science and ocean biogeochemistry, particularly coastal hypoxia and nitrous oxide dynamics in the Northern Indian Ocean. Research Interests Interactive marine carbon, nitrogen, and oxygen biogeochemistry Coastal and ocean deoxygenation processes Impact of climate change and human activities on oceanic oxygen dynamics Regional biophysical ocean modeling for nitrous oxide variability Publications Overview Yangyang’s publications span 2012–2025, emphasizing coastal hypoxia, nitrous oxide dynamics, CO2 fluxes, and marine environmental changes. His work integrates observational data with high-resolution physical-biogeochemical models, addressing climate-ocean interactions and anthropogenic impacts. Laboratory Affiliation Yangyang is part of the Resplandy Research Group at Princeton University, which investigates climate science and ocean biogeochemistry through multidisciplinary approaches.
Richard P. Allan is a Professor of Climate Science in the Department of Meteorology at the University of Reading, United Kingdom. He is affiliated with the National Centre for Earth Observation (NCEO) and the Walker Institute, and has previously worked at NCAS Climate and the Met Office. He served as a lead author for the Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report. His research focuses on Earth's energy budget, climate change, and the global water cycle, utilizing Earth Observation data to assess climate models and understand atmospheric processes. Key areas include radiative forcing, cloud dynamics, precipitation extremes, and ocean warming. He has led significant projects such as the NERC DEEP-C consortium. The 15 most recent publications highlight sustained contributions to understanding climate system responses, particularly in energy imbalance, water vapor trends, aerosol-cloud interactions, and precipitation variability. Articles appear in high-impact journals like Nature , Science , and Geophysical Research Letters , reflecting broad expertise in climate modeling, satellite remote sensing, and hydrological impacts. Lead Author, Intergovernmental Panel on Climate Change (IPCC) Sixth Assessment Report Richard P. Allan has supervised numerous PhD and Master’s students, though specific names are not listed in the provided texts. He has secured major research grants, including from NERC, and leads collaborative projects involving climate modeling and satellite data analysis. His work is instrumental in linking observations to climate predictions and policy-relevant science. He is affiliated with the National Centre for Earth Observation, the Walker Institute, and has been Principal Investigator on projects including NERC DEEP-C, DACCIWA, SMURPHS, and SINATRA, focusing on climate extremes, African weather systems, and Earth’s energy budget.
Minna Palmroth is a Professor of Computational Space Physics at the University of Helsinki 's Faculty of Science , leading the Department of Physics 's Space Physics Research Group. She directs the Kestävän avaruustieteen ja -tekniikan huippuyksikön (Centre of Excellence in Sustainable Space Science and Technology) and serves as the principal investigator for the Vlasiator hybrid-Vlasov simulation framework.
David J. Stensrud is a Professor of Meteorology and Atmospheric Science at Pennsylvania State University, where he has been a faculty member in the Department of Meteorology and Atmospheric Science within the College of Earth and Mineral Sciences. His research focuses on advancing our understanding of severe weather phenomena and improving numerical weather prediction capabilities. Dr. Stensrud received his academic training at Penn State, earning his M.S. in Meteorology in 1985 and his Ph.D. in Meteorology in 1992. His educational background has provided the foundation for his extensive research career focused on atmospheric dynamics and prediction. Dr. Stensrud's research spans several critical areas in atmospheric science, with particular emphasis on mesoscale meteorology , numerical weather prediction , and synoptic meteorology . He is internationally recognized for his work on ensemble forecasting , where he explores how groups of numerical weather prediction models can provide probabilistic forecasts of severe weather events. His research on convective-scale data assimilation aims to improve how observations from radar and satellites are incorporated into high-resolution weather models. Additional research interests include the physical processes behind severe weather phenomena like derechos and heavy rainfall events, the predictability of convective-scale phenomena, and the dynamics of the North American monsoon system. He has made significant contributions to understanding how urban environments influence thunderstorms and how convective systems interact with their larger-scale environment. Analysis of Dr. Stensrud's recent publications reveals a consistent focus on improving severe weather prediction through advanced data assimilation techniques. His work primarily centers on integrating radar and satellite observations into convection-allowing models to enhance forecasting capabilities for thunderstorms and other severe weather phenomena. A notable trend in his research is the increasing sophistication of ensemble approaches to address uncertainties in both initial conditions and model physics. His publications demonstrate a progression from fundamental studies of mesoscale phenomena to increasingly operational applications with potential for real-world forecasting improvements. Dr. Stensrud has served in several important professional capacities that highlight his standing in the meteorological community: Chair, Storm-scale Radar Data Assimilation Workshop, Norman, Oklahoma, October 2011 Member, NOAA/NWS Functional Weather Radar Requirements Integrated Working Team, 2012-2013 Guest Editor, Advances in Meteorology, Special Issue on "Storm-scale data assimilation and NWP", 2013 Commissioner, Scientific and Technological Activities Commission, American Meteorological Society, 2016-2017 Dr. Stensrud has authored more than 150 peer-reviewed publications and a textbook entitled "Parameterization Schemes: Keys to Understanding Numerical Weather Models." He has been actively involved in mentoring graduate students, though specific names of advisees are not provided in the available information. In collaboration with colleagues at Penn State, he helped create a 20-station environmental monitoring network across Pennsylvania with plans to expand to 50+ stations. His research has been supported by various grants that have enabled field campaigns such as the Mesoscale Predictability Experiment (MPEX) in 2013, where his team intercepted severe thunderstorms to collect critical observational data. Dr. Stensrud is involved with several research teams and facilities at Penn State, including work with the Joel N. Myers Weather Center and the Bob and Charlotte Landis Broadcast Room. His research group focuses on analyzing data from dual-polarization radar systems and developing improved techniques for assimilating these observations into convection-allowing models. He collaborates extensively with other researchers at Penn State and beyond, particularly in studies involving the interactions between urban environments and thunderstorms, and the upscale effects of deep convection on larger-scale weather patterns.
Johan Meyers is a full Professor at KU Leuven's Faculty of Engineering Science, Department of Mechanical Engineering, where he heads the Applied Mechanics and Energy conversion (TME) research unit. He serves as a contact person for TME and is an active member of the KIES – KU Leuven Institute for Energy and Society. His administrative roles include membership on the Council of the Faculty of Engineering Science, the Mechanical Engineering Department Council and Board, and chairing the HPC Steering Committee. Professor Meyers' research focuses on turbulent flow simulation and optimization, with particular emphasis on wind energy applications, atmospheric pollutant dispersion, and computational methods. His work spans Direct Numerical Simulation (DNS), Large-Eddy Simulation (LES), and model reduction techniques for applications in energy engineering. Current research categories include flow control & optimization, wind farm engineering, and atmospheric pollutant dispersion modeling, with specific applications in radioactive release scenarios and wind turbine system optimization. His recent publications demonstrate a strong trend toward wind energy applications, particularly in optimizing wind farm layouts and operations through advanced computational methods. The research shows significant emphasis on Large-Eddy Simulation techniques to study atmospheric boundary layer interactions with wind farms, with growing interest in hybrid wind-solar energy systems and the effects of surface temperature heterogeneity on flow patterns. His work increasingly integrates machine learning approaches to enhance computational efficiency in wind farm modeling. Professor Meyers actively supervises numerous PhD students including Bon, T., Janssens, N., Jamaer, S., and ALREWENY, A., among others. His research is supported by multiple ongoing projects through 2028, including 'Wind-farm co-design in the North-Sea basin given climate and market uncertainty' and 'Reconstruction of turbulence from partial observations,' primarily funded by research councils and industry partnerships. He leads the Turbulent Flow Simulation and Optimization (TFSO) research group, which develops efficient supercomputing simulation tools for turbulent flow applications in energy engineering. The group specializes in wind farm optimization, atmospheric pollutant dispersion modeling, and airborne wind energy systems, with a particular focus on LES studies of wind farm interactions with the atmospheric boundary layer.
Andrew Gettelman is a distinguished climate scientist at Pacific Northwest National Laboratory whose research spans atmospheric sciences, climatology, and climate modeling. With a D-index of 91 and over 32,652 citations across 343 publications, he ranks 422nd globally and 194th nationally in Environmental Sciences. His research interests focus on fundamental climate processes including cloud microphysics, aerosol-cloud interactions, stratospheric dynamics, and climate model development. Gettelman has made significant contributions to understanding Arctic climate feedbacks, particularly how clouds respond to sea ice loss, and has advanced the representation of aerosols in climate models through his work on the Community Atmosphere Model (CAM). Analysis of his publication trends reveals a consistent focus on improving climate model representations of atmospheric processes, with recent work emphasizing climate sensitivity in the Community Earth System Model (CESM2) and bounding global aerosol radiative forcing. His research bridges fundamental atmospheric science with practical applications for understanding climate change. Among his recognitions, Gettelman has been named to the World's Best Scientists 2025 list. His highly cited works include foundational papers on cloud microphysics schemes and aerosol representation in climate models. Gettelman maintains extensive collaborative networks, frequently working with researchers from the National Center for Atmospheric Research, University of Colorado Boulder, and other leading climate institutions. His research has been instrumental in advancing climate modeling capabilities used in major international climate assessments.
Dr. Yongchao Huang is a Lecturer (Assistant Professor) in the School of Natural and Computing Sciences at the University of Aberdeen, where he has been employed since August 2023. He also holds affiliations with the University of Oxford and the University of Cambridge through past postdoctoral and collaborative roles. He is actively involved in research, teaching, and academic service, and is currently accepting PhD students. His educational background includes: DPhil in Engineering Science, University of Oxford (2013–2017) Additional training in Machine Learning at Oxford (2015–2019) Dr. Huang's research focuses on fundamental and physics-informed machine learning, with core interests in Bayesian inference, variational methods, generative modeling (especially score-based), reinforcement learning, and interdisciplinary AI applications in mechanics, biology, energy, climate, and finance. A central theme of his work is the inference and sampling of probability densities, particularly through innovative particle-based and physics-inspired computational frameworks. He founded the Computational and Physical Learning (CPL) lab at Aberdeen in 2023. His recent publications (2020–2025) reflect a strong trend in probabilistic machine learning, with increasing focus on physics-based inference methods such as electrostatics, fluid dynamics, and material point methods. These works bridge machine learning with applied mathematics and physical simulation, demonstrating a unique interdisciplinary approach. Topics span Bayesian neural networks, acoustic wave propagation, mortality modeling, and adversarial cybersecurity. Dr. Huang has received academic recognition through invitations to serve on program committees and editorial roles: Program Committee Member, ECAI 2024 Organizing Committee, Bioinference 2024 Guest Editor, Journal of Theoretical Biology Senior Scientific Advisor to a UK firm He has supervised 57 MSc theses independently and currently supervises one PhD student. He has secured research engagement through collaborations with institutions including Oxford, Cambridge, and industry partners. His teaching includes courses such as Introduction to Software Engineering , Software Process and Management , and Computational Intelligence at Aberdeen, as well as practicals in inference at Cambridge. Dr. Huang leads the Computational and Physical Learning (CPL) lab at the University of Aberdeen, a curiosity-driven research group focused on foundational advances in machine intelligence. Though currently a solo researcher due to limited resources, the lab emphasizes end-to-end research and open collaboration. He encourages student mobility and interdisciplinary exploration.
Associate Professor Chengguo Zhang is a researcher at the University of New South Wales (UNSW Sydney) specializing in Mining Engineering and Geomechanics . His work focuses on improving mining safety and sustainability through fundamental and applied research on dynamic rock mass failures , groundwater-mining interactions , and data-driven visualization technologies . He currently serves as the Postgraduate Research Coordinator for the School of Mining Engineering. PhD in Mining Engineering from UNSW Sydney (2015) Coordinates postgraduate research programs Recipient of multiple teaching and research awards Research Interests: Zhang's work addresses critical mining industry challenges through: Quantification of energy sources and dissipation in rock masses for rockburst management Integration of AI data analytics and 3D visualization for geotechnical risk assessment Mine subsidence and coupled hydro-mechanical behavior of rock discontinuities Development of digital ground control management systems Article Trends: His recent publications demonstrate expertise in: Numerical modeling of rock fracturing mechanisms Nonlinear fluid flow analysis in fractured rock masses Shotcrete and ground support system evaluation Hydro-mechanical coupling during shear processes Energy-based coal burst risk classification Scientific Awards: Tim Shaw Award for Innovation in Teaching (2024) International Outstanding Young Scholar Award (2023) UNSW Education Excellence Award (2021) UNSW Research Excellence Award (2018) Research Supervision: Supervises 12 active PhD students (9 as primary/joint supervisor) and has guided 11 PhD completions (7 as primary/joint supervisor), including 3 Dean's Award recipients. Focuses on numerical modeling, data visualization, and machine learning applications in mining geomechanics.
Tomas Karlsson is a Professor and Deputy Head of Department at the Royal Institute of Technology , specializing in Space and Plasma Physics . He teaches courses such as EF2240 Space Physics , EF2245 Space Physics II , and EI1240 Electromagnetic Theory , while serving as examiner or coordinator for advanced projects and thesis work in space-related fields. His research focuses on the interaction between the solar wind and planetary magnetospheres , with specific interests in bow shock physics , magnetosheath jets , solar wind magnetic holes , auroral physics , and comparative studies of magnetospheres across planets and comets. He employs spacecraft data (e.g., MMS , Cluster , BepiColombo ) and simulations to analyze plasma dynamics and space weather phenomena. The 15 most recent publications highlight trends in solar wind turbulence , magnetospheric boundary processes , and planetary plasma interactions , with recurring themes in SLAMS (Short Large-Amplitude Magnetic Structures) , magnetosheath jet formation , and magnetic hole propagation . These works span statistical surveys, hybrid simulations, and multi-mission data analysis.
Dr. Patrick S. Market is a Professor of Atmospheric Science and currently serves as the Director of the School of Natural Resources at the University of Missouri. He also acts as Interim Co-Director of the Missouri Water Center. His research focuses on synoptic and mesoscale dynamics, particularly winter weather, heavy rainfall, flash flooding, and severe local storms. He has contributed to advancements in precipitation efficiency studies and operational forecasting techniques. His work explores the role of artificial intelligence in weather prediction and communication, emphasizing the continued importance of human expertise in an automated forecast process. Dr. Market has secured grants for data stream maintenance and digital equity planning, and he has led educational initiatives integrating research into synoptic meteorology classrooms. Notable collaborations include projects with the National Weather Service and studies on the Ozark Plateau's topographical influence on weather systems.
Rupert Klein is a Professor at Freie Universität Berlin in the Department of Mathematics and Computer Science , specializing in Geophysical Fluid Dynamics . His research spans atmospheric dynamics, numerical methods, and gas dynamics of combustion. Research Interests : Geophysical Fluid Dynamics and Atmospheric Modeling Multiscale Asymptotic Analysis Wave Propagation and Turbulence Combustion and Pressure Gain Combustion Climate Dynamics and Data Assimilation Scientific Awards : DRS Award for Excellent Supervision (2014) ECMWF Fellowship (renewed 2017) His recent work includes multiscale models for atmospheric flows, vortex dynamics, and combustion processes. Key collaborations involve DFG SPP 1276, CRC 1029 (TurbIn), and CRC 1114 (SCCS) projects. He contributes to numerical methods for low-Mach-number flows and geophysical simulations.
Dr. David R. Themens is an Associate Professor in Space Environment within the Space Environment and Radio Engineering (SERENE) group in the School of Engineering at the University of Birmingham. He specializes in modeling and mitigating the impacts of space weather on radio communications and navigation systems, with a particular focus on the ionosphere's effects on these technologies. Dr. Themens earned his academic credentials from Canadian institutions: BSc (Hons) in Physics from the University of New Brunswick (2011) MSc in Atmospheric and Oceanic Science from McGill University (2013) PhD in Physics from the University of New Brunswick (2018) His research primarily focuses on four interconnected areas: ionospheric modeling, ionospheric physics, measurement techniques, and radio propagation. Dr. Themens is particularly interested in the interaction between the ionosphere and the atmosphere, specifically how lower atmospheric forcing drives variability within the ionosphere and the interactions between the ionosphere and thermosphere. He is the principal developer of the Empirical Canadian High Arctic Ionospheric Model (E-CHAIM) , a high-latitude alternative to the International Reference Ionosphere (IRI) used for HF/UHF signal propagation modeling. His work includes exploring synergistic properties of different earth observation instruments, measurement technique development, data assimilation, and empirical modeling. Analysis of Dr. Themens' recent publication record reveals a strong emphasis on space weather phenomena, ionospheric modeling, and radio propagation. His work spans from fundamental ionospheric physics to practical applications in navigation and communication systems. Key themes include the development and validation of ionospheric models, analysis of space weather events (including the May 2024 geomagnetic superstorm), and the impact of solar phenomena on Earth's upper atmosphere. His research increasingly incorporates advanced data assimilation techniques and leverages multiple observational platforms including radar systems, GNSS networks, and satellite measurements. Dr. Themens holds significant leadership positions in the international space science community: Co-Chair of IAG-GGOS Joint Study Group on Understanding Ionospheric and Plasmaspheric Processes (2023-present) Chair of URSI Data Assimilation Working Group (2023-present) Co-Chair of IAGA Geospace Data Assimilation Working Group (2023-2027) URSI Commission G Early Career Representative (2023-2029) Chair of Canadian Association of Physicists Division of Atmospheric and Space Physics (2022-present) Dr. Themens actively mentors graduate students and is 'always looking for new Ph.D. students interested in the ionosphere, data assimilation, and radio propagation.' His research has been supported through contracts with Defence Research and Development Canada (DRDC) and various international collaborations. He leads the Canadian High Arctic Ionospheric Models (CHAIMs) project, which builds upon his doctoral work developing the E-CHAIM model. At the University of Birmingham, he teaches courses in Space System Engineering and Design, Space Mission Analysis and Design, and Space Environment.
