Find Academic Supervisors

David HysellView profile

Professor

• Ionospheric Physics
• Space Plasma Physics
• Aeronomy
• +3 more

David Hysell is a Professor in the Department of Earth & Atmospheric Sciences at Cornell University. His research focuses on ionospheric physics, plasma turbulence, and equatorial aeronomy. He leads projects utilizing HF radar networks, satellite data (e.g., ICON), and advanced modeling techniques to study ionospheric instabilities and space weather phenomena. Key tools include the Jicamarca Radio Observatory and collaborative initiatives like the SPARTA Center for space weather forecasting. His work integrates fluid/plasma simulations, automatic differentiation for parameter estimation, and hybrid kinetic models to understand Farley-Buneman instabilities, equatorial spread F, and sporadic E-layer dynamics. Recent efforts emphasize ionospheric forecasting using multi-instrument data fusion and machine learning approaches. Hysell actively participates in international observatory upgrades and geospace radar development to enhance global ionospheric monitoring capabilities. Scientific contributions include advancing ionospheric specification methods using HF beacon networks, investigating solar minimum conditions at equatorial altitudes, and studying plasma wave interactions in high-latitude regions. His research bridges theoretical plasma physics with applied space weather monitoring, addressing both fundamental science and operational needs.

• Coastal Engineering
• Ocean Engineering
• Marine Renewable Energy
• +3 more

Amir Etemad Shahidi is an Associate Professor at Griffith University's School of Engineering and Built Environment, specializing in Civil and Environmental Engineering. He holds roles as Director of Civil Engineering Double Degrees and Deputy Head of Research (former). His research focuses on Coastal Engineering, Marine Renewable Energy, and Climate Change impacts. He has published 110+ papers, with an H-index of 34 and 3500+ citations (SCOPUS). He leads industrial projects in Water/Coastal Engineering and is a member of the Cities Research Institute and Australian Rivers Institute. Education: PhD in Civil Engineering, University of Western Australia (1998) MSc in Civil Engineering, Sharif University of Technology (1991) BSc in Civil Engineering, Sharif University of Technology (1988) Research Interests: Coastal Engineering innovations, renewable energy systems (wind/wave/solar), climate change adaptation strategies, and environmental fluid dynamics. His work bridges theoretical models with practical applications, addressing challenges like coastal protection and sustainable energy integration. Recent studies explore offshore hybrid energy systems and wave energy converter pairing. Grants & Projects: Led major initiatives such as the Blue Economy CRC offshore fish pen design and spatial MCDM tools for renewable energy siting. Collaborations include AECOM, Delft University, and Deltares. Awards: 2015 Learning & Teaching Citation Award, 2018 Australia's leading researcher in Ocean Engineering, and top 2% global researcher (2024). Labs/Teams: Active in Griffith's Coastal Engineering Research Field Station (CERFS) and Hydroinformatics initiatives.

Jon AhnView profile

Professor

• Aerodynamics
• Unmanned Aerial Vehicles
• Aerospace Propulsion
• +4 more

Jon Ahn is a Professor in the Department of Aerospace Engineering at Sejong University, where he has been teaching and conducting research since 2001. His expertise spans aerodynamic design, aerospace propulsion systems, and energy conversion technologies. He serves as Editor-in-Chief of The Journal of Korean Society of Aerospace Sciences and maintains active collaborations with major aerospace institutions in South Korea. Dr. Ahn received his educational foundation from Seoul National University, earning his B.S. in 1986 and M.S. in 1988, both in Aeronautical Engineering. He completed his Ph.D. in Aerodynamics from the Massachusetts Institute of Technology (MIT) in 1997. Professor Ahn's research focuses on the aerodynamic design of aerospace systems, particularly unmanned aerial vehicles (UAVs) including solar-powered, high-altitude, and micro air vehicles (MAVs). His work also encompasses human-powered aircraft, aerospace propulsion system design (gas turbines, jet engines, rockets, propellers, ducted fans, and rotors), and energy conversion technologies including air conditioning systems. His laboratory, the Propulsion Aerodynamics Lab, investigates gas turbine, jet engine, propeller, and rocket technologies alongside solar-powered and human-powered aircraft systems. Analysis of Professor Ahn's publication record reveals a consistent focus on UAV and MAV technologies, with particular emphasis on aerodynamic design, propulsion systems, and solar-powered flight applications. His work spans computational fluid dynamics, experimental validation, and conceptual design frameworks for specialized aircraft systems. Recent publications show increasing attention to sustainable aviation technologies and high-altitude long-endurance UAV systems. 1986: Seoul National University, Alumni Association Award 1988: Korea Government Overseas Fellowship 2006: Sejong University, Best Teacher Award Professor Ahn has served on numerous influential committees including the Ministry of Science and Technology's 21st Century Frontier Committee (1999-2001), the Propulsion System Roadmap Committee (2002-2003), and the UAV Roadmap Committee (2004-2005). He has also advised major aerospace organizations including Korea Aerospace Industry and the Korea Aerospace Research Institute. His academic leadership extends to directorship in the Korean Society of Aerospace Sciences and senior membership in the American Institute of Aeronautics and Astronautics. Professor Ahn's Propulsion Aerodynamics Lab at Sejong University focuses on advancing technologies in aerospace propulsion and aerodynamics, with particular emphasis on practical applications for UAV systems and sustainable aviation solutions.

• Mechanical Engineering
• Artificial Intelligence
• Tribology
• +3 more

Hassan Shirvani is a Professor of Engineering Design and Simulation at the School of Engineering and the Built Environment, Anglia Ruskin University. He serves as Director of the Engineering Analysis Simulation and Tribology (EAST) Research Group, focusing on industry collaborations to solve engineering challenges. PhD in Mechanical Engineering, University of Bath MSc in Mechanical Engineering, University of Birmingham Member, Institute of Mechanical Engineers (IMechE) His research spans mechanical engineering, artificial intelligence, and biomedical applications, including: Thermal system optimization Machine learning in clinical decision-making Composite metal foil manufacturing Virtual reality medical training systems Flow dynamics in heat exchangers and nozzles AI-assisted diagnostics Hybrid manufacturing processes Hassan's publications reflect expertise in computational modeling, multi-physics simulations, and industrial applications. Notable areas include deep learning for suicide prediction, thermodynamic analysis of sustainable energy systems, and tribology in mechanical components.

• Computational Multiphysics
• Offshore Renewable Energy
• Finite Element Methods
• +5 more

Oriol Colomes Gene serves as Assistant Professor in the Offshore Engineering section within the Faculty of Civil Engineering and Geosciences at Delft University of Technology. He leads the Computational Multiphysics in Offshore Engineering research group, focusing on advanced numerical methods for offshore renewable energy applications. His teaching responsibilities include the “Floating and Submerged Structures” module for Civil Engineering master’s students and “Introduction to Computational Dynamics of Offshore Structures” in the Offshore and Dredging Engineering master’s program. His educational background includes a combined Bachelor’s/Master’s degree in Civil Engineering (2011) and a PhD in Civil Engineering (2016) from Universitat Politècnica de Catalunya, followed by postdoctoral research at Duke University (2016-2020). Colomes Gene’s research centers on computational multiphysics with emphasis on: Development of efficient Finite Element solvers for turbulent flows, free-surface flows, and visco-elasto-plastic solids Fluid-structure interaction in complex geometries Numerical methods for multi-phase and multi-material systems Applications in offshore wind, wave energy, and floating photovoltaics His recent work demonstrates strong integration of theoretical numerical methods with practical offshore renewable energy challenges, particularly in hydroelastic analysis of floating structures and optimization of energy capture systems. His scientific recognition includes: NWO Open Technologieprogramma subsidy for the RAPID-Wind project (2025) Colomes Gene actively supervises research within his Computational Multiphysics group and contributes to major collaborative projects including SPARKLES (2024-2030), which investigates nature-positive floating solar solutions. His research is supported by significant grants targeting offshore renewable energy innovation and computational methodology advancement. His laboratory work focuses on high-performance computing for multiphysics simulations, with particular expertise in developing and validating numerical frameworks for: Free-surface flows interacting with structures Vortex-induced vibrations Complex geometry hydrodynamics Hydroelastic response of very large floating structures

• Computational Fluid Dynamics
• Aerodynamic Shape Optimization
• Simulation-Based Design
• +3 more

Dr. Jason Hicken is an Associate Professor in the Mechanical, Aerospace, and Nuclear Engineering Department at Rensselaer Polytechnic Institute (RPI), and co-director of the Rensselaer Augmented and Virtual Environment. His research focuses on computational fluid dynamics, aerodynamic shape optimization, and simulation-based design. He holds a Ph.D. in Aerospace Engineering from the University of Toronto Institute for Aerospace Studies (2009), with postdoctoral training at Stanford University. Notable awards include the AFOSR Young Investigator Award (2015) and NSF CAREER Award (2016). His research interests span high-order numerical methods, entropy-stable discretizations, and optimization techniques for complex systems. He has contributed to advancing finite-difference operators, summation-by-parts schemes, and multi-disciplinary design optimization. His work bridges computational engineering and applied mathematics, addressing challenges in fluid dynamics, thermal systems, and aerospace applications. His lab, the Optimal Design Lab (http://www.optimaldesignlab.com/), develops innovative tools for engineering design optimization. Key achievements include developing entropy-stable numerical frameworks and integrating machine learning techniques for preconditioning in advection-dominated flows. His research has been applied to electric motor design, thermal management systems, and additive manufacturing. Awards recognize his contributions to foundational methods in computational engineering and aerospace optimization.

Svetlana V. PorosevaView profile

Professor

• Turbulence Modeling
• Uncertainty Quantification
• Computational Fluid Dynamics
• +4 more

Dr. Svetlana V. Poroseva is a Professor at the Department of Mechanical Engineering, University of New Mexico (UNM), with a distinguished career in turbulence physics, uncertainty quantification, and bio-inspired design. Her work bridges computational fluid dynamics (CFD) with applications in renewable energy, power systems survivability, and aerospace engineering. Her educational background includes a Ph.D. in Fluid and Plasma Mechanics (1996) and an M.S. in Physics (1989) from Novosibirsk State University, Russia. She has held faculty positions at UNM since 2010, progressing from Assistant to Professor (2023). Her research focuses on high-order turbulence closures, data-driven modeling, and evidence theory for multi-model predictions, with a strong emphasis on quantifying uncertainty in simulations. Dr. Poroseva’s recent publications highlight advancements in bio-inspired rotor design, DNS analysis of mixing layers, and solar energy accessibility studies. She has developed software tools like FIESTA and Power System Graph Converter, both under open licenses. Her work spans turbulent flow validation, power grid topology optimization, and aerosol transmission modeling, particularly during the pandemic. Scientific Awards UNM School of Engineering Dean’s Excellence Lectureship Award (2022) Harrison Faculty Excellence Award (2021-2022) Rainforest Innovation Award (2022) AIAA Associate Fellow (2013) Fellowships at Stanford, CNRS, and CISM She advises numerous graduate and undergraduate students, leads the UNM AIAA Student Chapter, and collaborates internationally on projects involving NASA, Sandia, and European institutions.

Alex WhiteView profile

Senior Lecturer

• Thermofluids
• Two-Phase Flow
• Thermodynamics
• +6 more

Dr. Alex White is a Senior Lecturer in Thermofluids at the Department of Engineering, Cambridge University, and a Fellow and Director of Studies at Peterhouse. He earned his undergraduate and PhD degrees from King's College, Cambridge, and conducted postdoctoral research in Cambridge, Lyon, and Toulouse before returning to Cambridge in 2000 as part of the Energy Group. His research focuses on two-phase flow (vapour-droplet flows), thermodynamics of power generation, Computational Fluid Dynamics (CFD), and heat pumps. His work includes theoretical and numerical studies on warm dense matter, electron transport, and energy storage systems like pumped thermal and compressed air storage. Recent publications emphasize warm dense matter physics, inertial confinement fusion, and thermal energy storage innovations. His theoretical analyses and simulations span high-energy-density plasmas, nonlocal electron stopping power, and hybrid energy systems. While no scientific awards are documented, his contributions to thermofluids and extreme condition physics are significant.

Hans Georg BeyerView profile

Professor

• Renewable Energy Systems
• Energy Meteorology
• Wind Energy Forecasting
• +4 more

Hans Georg Beyer is an Affiliated Professor in Energy Engineering at the Faculty of Science and Technology, The University of the Faroe Islands. His work focuses on sustainable energy systems with emphasis on renewable energy integration and meteorological aspects of power generation. With extensive publication history spanning over three decades, he has established himself as a leading researcher in renewable energy systems analysis. Professor Beyer's research interests center on sustainable energy supply systems based on renewables, with special emphasis on relating system performance characteristics to meteorological conditions. His work in Energy Meteorology covers analysis and modeling of spatial and temporal statistics of wind and irradiance fields, including forecasting methods for wind speed and solar irradiance with horizons of 6-35 hours and near now-casts in minute time scales. In Renewable Energy Systems, he investigates layout, dimensioning, modeling and performance analysis of grid-connected and stand-alone solar, wind and hybrid systems. His research bridges meteorological science with practical energy engineering applications, particularly for island and remote communities. His publication record shows consistent research activity with 55 research outputs documented, including significant contributions to solar and wind energy forecasting, hybrid system design, and grid integration challenges. Notable work includes the development of methods for satellite-derived irradiance data applications in PV system monitoring and performance assessment. Solar Energy Best Paper Award, ISES 1999 Solar World Congress, Jerusalem Professor Beyer has been instrumental in several major collaborative projects including PVSAT-2 (satellite-based PV system performance monitoring), SWERA (UNEP solar resource assessment), and various European initiatives focused on renewable energy integration. His work demonstrates strong international collaboration, particularly with German, Brazilian, and other European research institutions. While specific grant details aren't provided in the source material, his extensive publication record in high-impact journals suggests substantial research funding support throughout his career.

• Smart Energy Systems
• Renewable Energy Integration
• Thermal Energy Storage
• +3 more

Amirmohammad Behzadi is a doctoral researcher at KTH Royal Institute of Technology, specializing in smart energy systems within the Fluid and Climate Technology group. His work focuses on designing, controlling, and optimizing sustainable heating, cooling, and electricity systems for buildings. His research spans Hydrogen-integrated microgrids Machine learning for energy management Thermal storage solutions Decarbonization of commercial/residential buildings Renewable energy hybridization and has been recognized in the World's Top 2% Scientists (2022-2024) by Stanford/Elsevier. Behzadi's peer-reviewed publications (15 most recent) demonstrate expertise in AI-driven optimization Fuel cell applications Hybrid ventilation systems Grid-connected renewable solutions Borehole thermal energy storage with a focus on cold climate adaptations. His scientific contributions include being selected as a top project by the Royal Swedish Academy of Engineering Sciences (IVA, 2024) and receiving the Best Researcher Award at the University of Tehran's 28th Research Festival (2021). His educational background includes an M.Sc. in Energy Conversion from the University of Tehran and a B.Sc. in Mechanical Engineering with top honors.

• Predictive Maintenance
• Machine Learning
• Fault Detection
• +5 more

Dr. Lilach Goren Huber is a Senior Lecturer and R&D Projects Leader at the ZHAW School of Engineering, specializing in predictive maintenance and data-driven solutions for industrial systems. She leads multiple projects focusing on AI applications in anomaly detection (e.g., wind turbines, solar power plants), physics-informed machine learning for sensor error correction, and fault prognostics under data scarcity. Her work bridges academic research with industrial implementation, emphasizing scalable deep learning frameworks for commercial fleets and energy infrastructure. Research interests include predictive maintenance strategies, machine learning for industrial IoT, and hybrid prognostics combining domain knowledge with AI. She has published extensively in journals like International Journal of Prognostics and Health Management and Journal of Big Data , with a focus on renewable energy systems, SCADA data analysis, and cross-domain transfer learning. Current Projects: Physics-informed ML for elastomer sensors, end-to-end fault prognostics for power grids, and hybrid prognostics research. Past Contributions: Developed decision support systems for laser cutting machines, optimized hydroelectric maintenance schedules, and created risk-based frameworks for Swiss national road safety equipment. She actively contributes to the Expert Group Smart Maintenance and serves as a project leader in the ZHAW-PARC initiative. Her work addresses technical challenges like data contamination, sensor calibration errors, and real-world implementation barriers in industrial AI adoption.

Dušan GordićView profile

Professor

• Energy Engineering
• Sustainable Development
• Waste Heat Utilization
• +5 more

Dušan Gordić is a Professor in the Department of Energy and Process Engineering at the Faculty of Engineering, University of Kragujevac. His research focuses on energy efficiency, waste heat utilization, and sustainable industrial processes, with a particular emphasis on public infrastructure and food production systems. He holds a professorial position since 2012 and contributes to academic leadership through his chair in energy systems. His research interests span energy engineering, environmental impact assessment, and emerging technologies like AI-driven energy management. He has conducted case studies on kindergarten energy performance, industrial decarbonization, and 3D printing applications in education. His work integrates both theoretical and applied approaches, addressing challenges in renewable energy adoption and public building optimization. Key research themes: Energy systems, HVAC efficiency, sustainable manufacturing, and waste-to-energy solutions. Notable projects: Rooftop photovoltaic integration for food facilities, waste heat recovery in industrial compressors, and GPT applications in public building management. Dr. Gordić collaborates with municipalities and industries to develop practical solutions for energy efficiency, including thermal insulation strategies and carbon footprint reduction in urban settings. His publications frequently explore Balkan case studies, emphasizing regional sustainability challenges.

• Meteorology
• Climate Science
• Atmospheric Boundary Layer
• +5 more

Martin Janssens is an Assistant Professor in Meteorology at Wageningen University & Research . His research focuses on atmospheric boundary layer dynamics, mesoscale cloud organization, and climate modeling. He has contributed to projects like CloudRoots-Amazon22, exploring cloud-photosynthesis interactions in tropical regions, and investigates the impact of trade cumulus self-organization on radiation budgets. Janssens co-supervises PhD candidates in areas such as shallow convective clouds and forest fire plume dynamics. His work emphasizes bridging scales in Earth system modeling, including digital twin frameworks for climate projections. He has published extensively on topics like mesoscale circulations, cloud dynamics, and large-eddy simulations. Notable collaborations include work on carbon dioxide exchange in tropical tropospheres and the governance of solar geoengineering experiments. Key Projects : Unravelling mesoscale organization of shallow convective clouds for climate projections Evaluating atmospheric models for the Copernicus Monitoring Service Fluid dynamics of forest fire plumes Dynamical systems analysis of cloud patterns (PhD project 2019–2023) Research Themes : Trade wind cumulus dynamics and self-organization Amazon rainforest-atmosphere interactions Numerical modeling of boundary layer processes Advising & Grants : Co-promoter of three active PhD projects focusing on cloud dynamics, atmospheric modeling, and fire plumes. His research has been featured in high-impact journals like Geophysical Research Letters and Communications Earth & Environment .

• Optimization
• Aerodynamics
• Machine Learning
• +2 more

Andrew Ning is a Professor in the Department of Mechanical Engineering at Brigham Young University, with a joint appointment at the National Renewable Energy Laboratory. He leads the FLOW Lab, focusing on optimization, deep learning, and aerodynamic simulation methods for wind energy systems and aircraft design . Education PhD & MS in Aeronautics and Astronautics from Stanford University BS in Applied Physics from Brigham Young University His research spans optimization , aerodynamics , and machine learning , addressing challenges in wind farm layout, aerostructural design, and urban air mobility vehicle analysis. The FLOW Lab develops advanced computational tools including vortex particle methods, beam theory implementations, and meshless simulation techniques. Recent publications demonstrate expertise in gradient-based optimization , unsteady potential flow , and multirotor aerodynamics . Key application areas include electric propulsion , solar aircraft , and floating offshore wind turbines . His work integrates high-fidelity modeling with computational efficiency through novel algorithm development. Office hours for Winter 2025: Mondays 3:30-4:00pm, Tuesdays 4:00-5:00pm, Wednesdays 11:00am-12:00pm, and Thursdays 1:00-2:00pm.

Hans MuellerView profile

Research Professor

• Space Plasma Physics
• Heliosphere and Astrospheres
• Exoplanetary Atmospheres
• +2 more

Hans Mueller is a Research Professor at Dartmouth College's Department of Physics and Astronomy, specializing in space plasma physics. His work focuses on numerical modeling of heliospheres and astrospheres, plasma-neutral interactions, and exoplanetary atmosphere evaporation. Education: B.S. and M.S. from Ludwig Maximilian University of Munich, Ph.D. from Dartmouth College Affiliation: Dartmouth College, Department of Physics and Astronomy Courses Taught: Quantum Physics of Matter (P40), Applied Math Methods for Physicists (P22) His research integrates simulations of astrophysical environments with observational data from missions like IBEX, VOYAGER, and Hubble Space Telescope. Current projects include studying heavy neutral atoms in the solar system, stellar wind interactions with interstellar medium, and heliosphere analogues around other stars.