Find Academic Supervisors

• Data Science
• Electrical Energy Systems
• Machine Learning
• +7 more

Seyedmahmood Hosseiniimani is a Fixed-term Assistant Professor and Researcher in the Department of Energy (DENERG) at Politecnico di Torino, Italy. He is actively engaged in research and teaching in the domains of electrical energy systems, data science, and smart grid technologies. He contributes to multiple academic programs as a course collaborator and serves on several course councils. Position: Fixed-term Assistant Professor Institution: Politecnico di Torino Department: Department of Energy (DENERG) Research Focus: Data Science, Machine Learning, Electrical Energy Systems, Microgrids, Power Economics His research interests lie at the intersection of data analytics and energy systems, with a strong emphasis on applying machine learning and statistical methods to electricity markets, demand forecasting, and microgrid optimization. He explores topics such as price clustering, inter-zonal congestion, pandemic impacts on energy demand, and demand response in smart grids. The trend in his recent publications shows a consistent focus on data-driven analysis of electricity markets, particularly in the Italian context. His work combines technical modeling with economic and policy implications, targeting journals and conferences in power systems, energy informatics, and sustainable infrastructure. He frequently employs regression models, clustering algorithms, and systematic reviews to extract insights from complex energy datasets. He is a Guest Editor for the journal ENERGIES (2025–present), contributing to scholarly discourse in renewable and sustainable energy. While no formal scientific awards are listed, his editorial role reflects recognition in the academic community. Hosseiniimani supervises PhD student Erminia Consiglio in the field of Electrical, Electronic, and Communications Engineering. His teaching responsibilities include courses such as Smart Grids, Electrical Systems for Buildings, and Fundamentals of Energy Conversion, Transport, and Storage across various engineering programs. He collaborates with senior researchers like Prof. Ettore Bompard and contributes to interdisciplinary research projects aligned with UN SDGs 7, 9, 11, and 12. He is involved in research initiatives related to energy communities, prosumer integration, and data analytics for policy support, working within a dynamic research environment at DENERG focused on sustainable and intelligent energy systems.

L. Britt WilsonView profile

Clinical Professor

• Neurophysiology
• Cardiovascular Neuroscience
• Reflex Physiology
• +7 more

L. Britt Wilson is a Clinical Professor in the Department of Pharmacology, Physiology and Neuroscience at the University of South Carolina School of Medicine, where he also serves as Course Director of Medical Physiology. His research investigates the neural regulation of cardiovascular function, particularly spinal cord mechanisms in reflex cardiovascular control from somatic tissues and how these are altered by inflammation or injury. Education: Ph.D., LSU Medical Center—New Orleans Postdoctoral Training, UT Southwestern Medical Center B.S., West Texas State University His research interests include neurophysiology, cardiovascular neuroscience, pain mechanisms, inflammation, and spinal cord function. He also contributes significantly to medical education, especially in ultrasound curriculum development and physiology instruction. His recent publications span physiology, neuroscience, toxicology, and medical education, reflecting interdisciplinary and translational research. Key research trends include studying cardiovascular reflexes in pain and inflammation, gender differences in stress responses, gene expression in zebrafish toxicology models, and innovations in medical teaching. His work often involves animal models and collaborative clinical studies. Dr. Wilson has contributed to consensus guidelines in ultrasound education and has published in high-impact journals such as Nature , PLoS ONE , and Advances in Physiology Education . His collaborative network includes researchers in neuroscience, toxicology, and medical education. He mentors students and researchers through his laboratory work and curriculum leadership. His lab investigates pharmacological and gene-based interventions to modulate pathological cardiovascular reflexes. He is actively involved in interdisciplinary teams focused on neural control mechanisms and educational innovation.

• Limnology
• Hydrology
• Geographic Information Systems
• +3 more

Dr. Maciej Markowski serves as an Adjunct Professor at the Faculty of Oceanography and Geography, University of Gdansk, with additional affiliation at the institution's GIS Center. His research focuses on freshwater ecosystems in Northern Poland, particularly the Tricity metropolitan area, employing Geographic Information Systems and remote sensing methodologies to analyze lake hydrology and ecological dynamics. His research portfolio centers on Limnology and Hydrology, with specialized expertise in lobelia lakes and post-glacial ponds. Key investigation areas include trophic state assessment, sediment resuspension mechanisms, anthropogenic pressure impacts, and climate change effects on freshwater systems. His methodological approach integrates geospatial analysis with hydrological modeling to address conservation challenges in vulnerable aquatic ecosystems. Analysis of his 15 most recent publications reveals consistent application of GIS techniques across diverse environmental contexts—from modeling wind-wave sediment dynamics in Tricity-area lakes to assessing atmospheric water exchange in river-lake systems. Notable research trends include increasing integration of satellite data for climate monitoring (2023-2024), persistent focus on Baltic coastal ecosystems, and interdisciplinary expansion into bioenergy conversion processes and aeronautical cartography applications. As an active member of the University of Gdansk's GIS Center, Dr. Markowski leverages advanced spatial analysis infrastructure to support regional environmental research. His work directly contributes to conservation strategies for Northern Poland's unique freshwater systems, particularly addressing threats from urbanization and climate variability in the Gdańsk metropolitan region.

Abhnil Amtesh PrasadView profile

Research Fellow

• Atmospheric Science
• Climate Science
• Remote Sensing
• +3 more

Dr. Abhnil Amtesh Prasad is a Research Fellow at the Climate Change Research Centre (CCRC), University of New South Wales (UNSW). He holds a PhD in Physics from the University of Auckland and has expertise in atmospheric science, climate modeling, and renewable energy systems. His current work focuses on satellite remote sensing of clouds, solar irradiance forecasting, and the climatic impacts of aerosols and cloud dynamics. He collaborates with Prof. Steven Sherwood’s Physical Meteorology and Atmospheric Climate Dynamics Group, developing algorithms for geostationary satellite data to improve short-term solar energy predictions. Key research interests include tropical cloud physics, climate change processes, and energy system resilience under future climate scenarios. Dr. Prasad’s research integrates remote sensing techniques with climate models, emphasizing high-resolution simulations and machine learning applications. His work bridges atmospheric science and renewable energy, addressing challenges such as cloud-induced solar intermittency and aerosol effects on energy production. Recent studies include analyzing the 2019–20 Australian bushfires’ impact on solar power and developing frameworks like TorchClim v1.0 for enhancing climate model physics through deep learning. His publications span climate science, renewable energy systems, and atmospheric dynamics, with a focus on practical applications for energy reliability and policy. Despite no listed academic awards or grants, his contributions to interdisciplinary climate-energy research are notable. He maintains active collaborations within the UNSW Clean Energy research network and utilizes advanced facilities for climate modeling and remote sensing analysis.

Christoph GoebelView profile

Professor

• Energy Management Systems
• Renewable Energy Integration
• Smart Grids
• +4 more

Prof. Christoph Goebel is a Professor of Energy Management Technologies at the TUM School of Engineering and Design, Technical University of Munich. His research focuses on optimizing energy systems through advanced algorithms, machine learning, and data-driven approaches. Key areas include renewable energy integration, smart grid technologies, electric vehicle charging optimization, and the application of graph neural networks in power systems. His work bridges theoretical advancements with practical implementation, such as developing platforms like e-SparX for collaborative machine learning in energy research and frameworks like EnergyOS for modular energy management systems. Recent studies explore thermal energy storage models, cost-effective CO2 reduction strategies via heat pumps, and the economic incentives of wind energy data sharing. Goebel's publications (2016–2025) consistently emphasize predictive control, optimization under market constraints, and the integration of ICT innovations into energy infrastructure. Notable contributions include transfer learning models for building thermal dynamics and benchmarking frameworks for energy hardware-software systems.

• Sustainable Energy
• Renewable Energy Systems
• Environmental Engineering
• +6 more

Iain Staffell is an Associate Professor of Sustainable Energy at the Centre for Environmental Policy , part of the Faculty of Natural Sciences at Imperial College London. He holds interdisciplinary expertise in Physics, Chemical Engineering, and Economics, with 15 years in energy R&D. His work focuses on renewable energy integration, energy storage economics, and decarbonization strategies. Affiliations: Centre for Environmental Policy, Imperial College London Platforms: Renewables.ninja, Demand.ninja, EnergyStorage.ninja, Electric Insights, and Power Swarm Research Interests: Sustainable energy systems, renewable energy economics, energy storage technologies, climate policy analysis, and socio-technical transitions. His work bridges technical and policy dimensions of decarbonization, with a focus on real-world applications. Recent Work Trends: Recent articles address challenges in renewable energy deployment economics, hydrogen roles in energy systems, and the socio-political dimensions of transitioning away from fossil fuels. He emphasizes equity, cost-effectiveness, and systemic resilience in decarbonization strategies. Awards: None explicitly listed in the provided text. Projects: Leads Electric Insights (tracking UK electricity trends) and co-founded Power Swarm (network of energy transition experts). Grants/Advising: Extensive grants in energy systems R&D; no student advisees listed. Labs/Teams: Active in the Centre for Environmental Policy and collaborates globally through Power Swarm.

Michael McElroyView profile

Professor

• Climate Science
• Atmospheric Chemistry
• Environmental Studies
• +3 more

Michael McElroy is the Gilbert Butler Professor of Environmental Studies at Harvard University's School of Engineering and Applied Sciences (SEAS). His research focuses on climate dynamics, atmospheric chemistry, and energy systems, with a strong emphasis on China's decarbonization strategies and renewable energy integration. He investigates interactions between climate, energy infrastructure, and air quality, particularly in high-emission regions like China and India. Key research themes include optimizing renewable energy deployment (wind, solar, hydrogen), mitigating coal phase-out impacts, and developing sustainable transportation infrastructure. His work also addresses global climate patterns, such as Arctic amplification effects on dust emissions and heat stress projections. Highlighted contributions: Offshore wind potential in China, EV charging infrastructure, and policy frameworks for carbon neutrality. Interdisciplinary collaborations span environmental science, engineering, and public policy. Publications frequently analyze trade-offs between energy security, emissions reduction, and socioeconomic factors. His findings inform global climate action through high-impact modeling and policy recommendations.

Chi ZhangView profile

Research Fellow

• Planetary Magnetospheres
• Ion Dynamics
• Magnetic Fields
• +1 more

Chi Zhang is a Research Fellow at the Center for Space Physics and Department of Astronomy, Boston University, specializing in planetary space physics. He earned his Bachelor's degree from China University of Geosciences (Wuhan) in 2018 and completed his PhD in Space Physics at the University of Chinese Academy of Sciences in 2023. Education: Bachelor's Degree in Geosciences, China University of Geosciences (Wuhan), 2018 PhD in Space Physics, University of Chinese Academy of Sciences, 2023 His research centers on planetary magnetospheres with primary focus on Mars, analyzing magnetic field structures and ion dynamics using MAVEN spacecraft measurements. Key investigations include ion escape mechanisms at Mars and their correlation with solar wind variability, contributing to broader understanding of space plasma interactions in planetary environments.

• Atmospheric Sciences
• Astronomical and Space Sciences
• Geophysics
• +3 more

Professor Ingo Mueller-Wodarg serves as a Professor of Physics and Senior Tutor in the Faculty of Natural Sciences at Imperial College London. He is the Co-Principal Investigator of the Radio and Plasma Wave Instrument on ESA's JUICE mission to Jupiter, which successfully launched on 14 April 2023. His research specializes in planetary and satellite atmospheres across the solar system, investigating global characteristics, variability, atmospheric waves, and interactions with the solar wind. Using numerical simulations and spacecraft data from missions like Cassini/Huygens, Venus Express, and ExoMars, he studies the atmosphere-space transition region to understand atmospheric escape mechanisms and long-term evolution. This work reveals fundamental physical processes under diverse planetary conditions, with direct implications for Earth and extrasolar planet research. Affiliated with Imperial's Space Lab and the Space, Plasma and Climate Community, Professor Mueller-Wodarg actively contributes to major international space missions. His leadership in JUICE and prior missions represents significant collaborative efforts in advancing planetary science through spacecraft instrumentation and data analysis.

• Approximation Theory
• Numerical Analysis
• Machine Learning
• +12 more

Emma Perracchione is an Associate Professor in the Department of Mathematical Sciences "G.L. Lagrange" (DISMA) at Politecnico di Torino, where she conducts research at the intersection of approximation theory, machine learning, and scientific computing. Her work focuses on kernel-based methods, inverse problems, and applications in space weather and solar physics. She is actively involved in teaching and research leadership, including PhD supervision and national projects. PhD in Mathematics, University of Turin (2017, cum laude) M.Sc. and B.Sc. in Mathematics, University of Turin (2013, 2011) Her research interests center on approximation theory and its applications, particularly greedy methods and two-layered kernel machines used for feature reduction in geomagnetic storm forecasting and optimal sampling for solar nanosatellites. These efforts contribute significantly to advancements in inverse problems and scientific computing . Her expertise spans machine learning , imaging , and data-driven modeling , with applications in climate action and space weather. The most recent publications highlight a strong trend in developing and analyzing variably scaled kernels , feature selection via greedy algorithms, and machine learning applications in solar and astrophysical contexts. These works integrate numerical analysis with real-world data from solar wind and imaging instruments, demonstrating a blend of theoretical rigor and practical relevance. Scientific awards received include: GNCS Young Researchers Funding (2020) GNCS Young Researchers Funding (2016) "Luciana Picco Botta" Study Award (2015) COST Short Term Scientific Mission (STSM) grant (2015) Emma Perracchione supervises PhD student Matteo Trombini in the Mathematical Sciences program (40th cycle, 2025–ongoing) and leads the PRIN-funded project GOSSIP – Greedy Optimal Sampling for Solar Inverse Problems (2025–2027). She has taught various courses including Linear Algebra and Geometry , Numerical Methods and Scientific Computing , and advanced topics on Kernels for Machine Learning in aerospace, automotive, and computer science engineering programs. She is a member of the Space Weather Italian Community (SWICo) and the National Scientific Computing Group (GNCS-INdAM) , and serves as Guest Editor for Dolomites Research Notes on Approximation . She has also participated in organizing major conferences such as DWCAA24 and GIMC-SIMAI Young.

Hui LiView profile

Professor

• Cancer Biology
• Molecular Genetics
• Oncogene Addiction
• +3 more

Hui Li is a Professor in the Department of Pathology at the University of Virginia Medical School, leading the Li Lab. The lab is dedicated to understanding intergenic splicing mechanisms and their role in cancer development, particularly glioblastoma (GBM). Key research focuses include RNA trans-splicing, cis-Splicing of Adjacent Genes (cis-SAGe), and the discovery of the AVIL gene as a critical oncogene in GBM. The lab's work challenges traditional views on gene interaction and aims to develop targeted therapies with minimal side effects. Supported by the Funds for Excellence in Science and Technology and the IVY Foundation Biomedical Innovation, the lab collaborates with institutions like Vanderbilt University for brain donation studies. Dr. Li actively engages with patients and families, addressing concerns about genetic predisposition and clinical trial updates. The lab also explores drug development pipelines targeting AVIL and evaluates compounds from external partnerships, such as Rokit Pharma’s lead GBM drug. Dr. Li’s research spans oncogene addiction in pediatric and breast cancers, with a focus on translational medicine. The lab’s findings are disseminated through publications and updates on the UVA website. Email contact is available at hui.li@virginia.edu .

• Urban Climate
• Climate Modeling
• Atmospheric Physics
• +7 more

Steven Caluwaerts is an Associate Professor at Ghent University's Faculty of Sciences, Department of Physics and Astronomy (WE05). His research focuses on urban climate science, climate modeling, and meteorology, with particular expertise in urban climate modeling, weather modeling, observational networks, and citizen science applications. He is deeply involved in European climate research initiatives, particularly those related to urban environments and climate change impacts. Dr. Caluwaerts' research interests span urban climate systems, high-resolution climate modeling, and the impacts of climate change on urban environments and cultural heritage. His work integrates advanced computational techniques with field observations to address critical questions about urban heat islands, climate adaptation strategies, and building heritage preservation. He has developed innovative approaches for downscaling climate data to urban scales and has made significant contributions to understanding how climate change affects building materials and urban infrastructure. His publication record reveals a strong focus on urban climate modeling and climate change impacts, with particular emphasis on creating high-resolution climate data for urban areas, validating climate models with observational networks, and assessing climate risks to building heritage. Recent work shows increasing attention to practical applications of climate science, including heat stress monitoring for public health and sports events, climate adaptation strategies for European cities, and the development of tools for processing crowdsourced meteorological data. Dr. Caluwaerts collaborates extensively with researchers across Europe, particularly within the CORDEX framework, and has supervised numerous PhD students whose work focuses on urban climate modeling, climate change impacts on buildings, and urban heat island effects. His research is supported by various European and Belgian climate initiatives, with applications in urban planning, heritage conservation, and public health. He is actively involved in citizen science initiatives that engage schools and the public in urban climate monitoring, demonstrating his commitment to making climate science accessible and relevant to broader society. His work with the MetObs toolkit exemplifies this approach, providing user-friendly tools for processing non-traditional meteorological observations.

Ahmet Duran ŞahinView profile

Professor

• Wind Power Engineering
• Solar Irradiation
• Wind Energy
• +4 more

Professor Ahmet Duran Şahin is a faculty member at Istanbul Technical University's Department of Meteorological Engineering within the College of Engineering. His research focuses on renewable energy systems, particularly wind and solar power, with an emphasis on floating photovoltaic systems, climate change impacts, and energy policy. He has contributed to over 45 publications and led 14 projects, including studies on climate-resilient campus design and extreme weather analysis. Key research areas include optimizing renewable energy technologies under extreme conditions, evaluating carbon footprints in urban settings, and enhancing wind farm performance through integrated climate projections. His work frequently involves numerical simulations and computational fluid dynamics. Awards include the 6. Kadir Has Awards (2010), H2020 Above-Threshold Award (2017), and Incentive Award (2006). Projects span topics like floating solar power prototypes, meteorological infrastructure for railways, and sustainable energy transitions in Sub-Saharan Africa. His contributions to academia include advising numerous graduate students (not explicitly listed) and collaborating on interdisciplinary initiatives, such as integrating climate data with urban planning and energy systems.

• Climate Change
• Solar Irradiation
• Artificial Neural Network
• +4 more

Roles & Affiliations: Assistant Professor at Istanbul Technical University's Department of Meteorological Engineering. Active in research and projects since 1999, with a focus on climate change, meteorological data analysis, and renewable energy applications. Research Interests: Oztopal specializes in climate change scenarios, precipitation patterns, wind energy prediction, and satellite-based meteorological data validation. His work integrates artificial neural networks and genetic algorithms for environmental modeling. Projects: Principal Investigator (PI) for projects like 'Development of a Satellite-Based Precipitation Algorithm for Türkiye' (2021–2024) and 'Hydrology-SAF CDOP 2 Phase' (2017–2022). Contributed to risk analysis for high-speed rail meteorological conditions and validation of satellite precipitation products. Publications: Over 17 peer-reviewed articles focusing on climate modeling, wind power prediction, and meteorological parameter analysis. Notable works include studies on extreme precipitation scenarios and innovative trend methodologies in Turkey.

Trieu MaiView profile

Researcher

• Renewable Energy Systems
• Power System Economics
• Energy Policy
• +13 more

Trieu Mai is a Researcher at the Capacity Expansion & Electricity Markets Group within the Grid Planning and Analysis Center at the National Renewable Energy Laboratory (NREL). His work focuses on renewable grid integration, energy system transformation, electrification, and clean energy policy, utilizing advanced power system models and energy-economic tools. Bachelor of Physics, University of California, Davis Master of Physics, University of California, Santa Cruz PhD in Theoretical Physics, University of California, Santa Cruz Research interests include 100% Renewable Energy Systems , Power System Economics , and Technology Innovation Impact Analysis , with a strong emphasis on modeling the evolution of electricity systems toward net-zero emissions. His work evaluates the costs, benefits, and impacts of high renewable penetration and grid flexibility solutions. Recent publications highlight continent-scale electricity system optimization , net-zero emissions strategies , and policy-driven energy system transformations . Key trends in his research involve time series aggregation techniques , multi-model collaborations , and interregional energy market analysis . Achievement Award, Utility Variable-Generation Integration Group (2013) Excellence Award, Energy Systems Integration Group (2019) NREL Chairman’s Award (2011, 2015) NREL Distinguished Member of Research Staff (2021)