Find Academic Supervisors

• Environmental Fluid Mechanics
• Open-Channel Flow
• Turbulence Structure
• +7 more

Dr Stuart Cameron is a Senior Research Fellow in the School of Engineering at the University of Aberdeen, where he has been contributing to research since 2007. His work is centered on environmental fluid mechanics, with a focus on open-channel flows, turbulence, sediment transport, and bio-inspired hydrodynamics. He is affiliated with a series of high-impact interdisciplinary research projects involving advanced experimental and theoretical fluid dynamics. His research interests include: Open-channel flow turbulence structure Sediment entrainment and transport mechanisms Flow-biota interactions in aquatic ecosystems Development and error analysis of Particle Image Velocimetry (PIV) techniques Hydrodynamics of bioinspired surfaces and fish-shaped bodies The most recent publications highlight a strong trend in analyzing complex turbulent flows over rough beds, secondary currents, and bio-inspired surface morphologies. His work frequently involves high-resolution experimental techniques and theoretical modeling, often in collaboration with leading researchers such as V. Nikora. Articles span topics from drag forces on sediment particles to hydrokinetic turbine performance and field-based PIV studies in natural water bodies. Notable scientific contributions have been supported by major grants from EPSRC, NERC, and the European Commission. These include projects such as: "Secondary currents in turbulent flows over rough walls" (EPSRC, 2021–2024) "River flow regulation, fish behaviour and status – RIBES" (European Commission, 2020–2023) "Field stereoscopic PIV system for freshwater and marine ecosystems" (NERC, 2019–2020) "Bed friction in rough-bed free-surface flows" (EPSRC, 2014–2017) "HYTECH" (Marie Curie ITN, 2013–2016) "High-resolution numerical and experimental studies of turbulence-induced sediment erosion" (EPSRC & DFG, 2010–2014) Dr Cameron has not advised any named students in the available data, but he collaborates extensively within research teams focused on environmental hydraulics and experimental fluid mechanics. He is involved in the development of advanced measurement systems and theoretical frameworks for understanding complex flows in natural and engineered environments. He is actively engaged in laboratory and field-based research, contributing to both fundamental fluid mechanics and applied environmental engineering challenges. His work bridges engineering, ecology, and physics, particularly in the context of river systems and aquatic habitats.

Aswin GnanaskandanView profile

Assistant Professor

• Computational Fluid Dynamics
• Multiphase Flows
• Biomedical Acoustics
• +3 more

Prof. Aswin Gnanaskandan is an Assistant Professor in the Department of Mechanical & Materials Engineering at Worcester Polytechnic Institute (WPI), where he joined in August 2020. He directs the Computational Multiphase Transport Laboratory, focusing on developing high-fidelity models for multiphase flows with applications in engineering and biomedical fields. His research is funded by NSF, Office of Naval Research, NIH, and the Center for Advanced Research in Drying. Education: PhD, Aerospace Engineering & Mechanics, University of Minnesota (2015) MS, Aerospace Engineering & Mechanics, University of Minnesota (2012) BS, Aeronautical Engineering, Madras Institute of Technology (2006) Research Interests: Computational Fluid Dynamics (CFD), Multiphase Flow Modeling, Biomedical Acoustics, High-Performance Computing, and applications in underwater transportation, propulsion, and biomedical acoustics. His work bridges fundamental fluid mechanics with real-world challenges in energy, health, and environmental systems. Recent Research Trends: His articles focus on microbubble-enhanced ultrasound therapy, cavitation dynamics in propulsion systems, and multiphase flow modeling across scales. Key themes include improving thermal ablation precision in medical treatments and optimizing industrial processes like spray drying through advanced numerical techniques. Awards: Excellence in Research Award (WPI, 2024) NSF Engineering Research Initiation Award (2023) James Nichols Heald Research Award (WPI, 2022) Teaching & Advising: Teaches undergraduate/graduate courses in Fluid Mechanics, Thermodynamics, and Numerical Methods. Advises multiple Major Qualifying Projects and fosters interdisciplinary collaboration through lab activities. His lab actively engages with industry and academic partners on projects like HIFU therapy and sustainable energy solutions. Labs & Teams: Leads the Computational Multiphase Transport Lab, which collaborates on projects involving CFD solver development (MFC 5.0), exascale computing, and biomedical acoustics. Aligns research with UN Sustainable Development Goals (SDG 7, 9, 13).

L.J. SluysView profile

Professor

• Computational Mechanics
• Computational Mechanics of Materials
• Modelling of Failure Processes
• +12 more

Professor L.J. Sluys is a Full Professor and Chair of Computational Mechanics at the Faculty of Civil Engineering and Geosciences, Delft University of Technology (TU Delft). He has been a leading figure in computational mechanics since 1999, heading the Computational Mechanics group and serving as head of the Department of Materials, Mechanics, Management and Design (3MD) from 2018 to 2024. His research is centered on the computational modeling of material behavior, particularly focusing on failure processes and high-performance materials. His research interests include computational mechanics of materials, modeling of failure and fracture processes, multi-scale methods, and the computational modeling of high-performance materials such as composites and concrete. He employs advanced numerical techniques including the finite element method, extended finite element method (XFEM), level-set methods, and cohesive zone modeling to simulate complex mechanical behaviors under static and dynamic loading conditions. His work spans civil, mechanical, and materials engineering domains, with applications in infrastructure, energy, and sustainable materials. The recent publications highlight a strong trend in modeling fracture, fatigue, and degradation in heterogeneous materials such as composites, concrete, and geological formations. His work integrates multi-physics and multi-scale approaches, often coupling mechanical, thermal, and chemical effects. There is a consistent focus on numerical robustness, model validation, and the development of adaptive computational frameworks for simulating progressive damage and failure. Research Fellow of the Netherlands Academy of Arts and Sciences (KNAW) Professor Sluys has taught core courses such as Introduction to the Finite Element Method and Computational Methods in Non-linear Solid Mechanics for over a decade, indicating a strong commitment to academic education. He has supervised numerous students, though specific names are not listed in the provided texts. He leads an active research group in computational mechanics, contributing to both fundamental and applied research in solid mechanics. His work involves collaboration with international institutions and industry partners, particularly in the areas of infrastructure durability and advanced materials.

Georg StadlerView profile

Professor

• Computational Mathematics
• Scientific Computing
• Uncertainty Quantification
• +5 more

Georg Stadler is a Professor of Mathematics and Computer Science at New York University's Courant Institute. His research focuses on computational inverse problems, uncertainty quantification, and PDE-constrained optimization, driven by applications in climate modeling, geophysics, and plasma physics. He holds a PhD from the University of Graz (2004) and has been recognized with awards including the Gordon Bell Prize (2015) and the SIAM Computational Science & Engineering Best Paper Prize (2019). Education: Ph.D. (Dr.), Mathematics, University of Graz, Austria, 2004. M.S. (Mag.), Mathematics, University of Graz, Austria, 2001. M.S., Mathematics and Geometry Education, Graz University of Technology and University of Graz, 2001. Research Interests: Large-scale PDE solvers, Bayesian inverse problems, extreme event probability estimation, and optimization under uncertainty. Applications in climate (sea/land ice, tsunamis), plasma physics (fusion), and computational earth science (mantle flow, plate tectonics). Recent Research Trends: His work emphasizes scalable algorithms for high-dimensional Bayesian inverse problems, with applications to tsunamis, stellarator coil design, and ice sheet dynamics. Recent articles highlight advancements in extreme event probability estimation and robust multigrid solvers for incompressible Stokes equations. Awards: Gordon Bell Prize (2015) for extreme scalability of implicit solvers. SIAM Best Paper Prize (2019) for computational science contributions. Young Scientist ASCINA Award and Springer CSE Prize (2011). Advising & Grants: Current PhD student Sonia Reilly and former advisees include Chen Li and Shanyin Tong. His research is supported by NSF, ONR MURI, and the Simons Foundation. He co-leads the Computational Mathematics and Scientific Computing Seminar at Courant. Labs & Collaborations: Active in Courant’s interdisciplinary groups, focusing on high-performance computing and inverse problems. Collaborates with institutions like UT Austin on mantle dynamics and fusion energy projects.

• Networking and Operating Systems
• Information Security and Assurance
• Network Architecture and Protocols
• +3 more

Sonia A. Fahmy is a Professor of Computer Science and Associate Department Head at Purdue University's Department of Computer Science (College of Science). She holds a PhD from The Ohio State University (1999). Her research focuses on network architectures, protocols, and security, with over 100 refereed publications. Key areas include virtual reality networking, cellular network optimization, and network experimentation tools like NFV-VITAL and ENVI. Her work is supported by NSF, DHS, industry partners, and she leads Purdue's CERIAS cybersecurity initiatives. Education: PhD in Computer and Information Science from The Ohio State University (1999). Research Interests: Network security, distributed systems, wireless sensor networks, and network function virtualization. Notable contributions include the HEED clustering algorithm and Contain-ed latency management system. Awards: NSF CAREER Award (2003), IEEE Fellow. Grants: NSF, DHS, AT&T, Cisco, Juniper, and Meta-funded projects. Professional service includes leadership roles in IEEE ICNP, INFOCOM, and editorial roles in top journals. Advising: Mentored over 20 PhD students and postdocs. Current advisees include Umakant Kulkarni and Yufeng Chen. Research teams collaborate with industry partners like Hewlett-Packard and Sandia National Labs. Labs/Teams: Active in Purdue's CERIAS, leading projects on secure network protocols and experimentation frameworks. Tools developed include EMIST, Testbed Mapping, and iHEED for sensor networks.

George V. LauderView profile

Professor

• Biorobotics
• Ichthyology
• Biomechanics
• +6 more

George V. Lauder is the Henry Bryant Bigelow Professor of Ichthyology at Harvard University, affiliated with the Museum of Comparative Zoology (MCZ) and designated as a Harvard College Professor. He is currently on leave for Spring 2025 and not accepting graduate students for the 2025-2026 academic year. His research focuses on biorobotics, the biomechanics of vertebrate movement (particularly fishes), and evolutionary morphology. Key areas include robotic models of fish locomotion, quantitative flow visualization of shark and ray-finned fish dynamics, and the fluid mechanics of aquatic movement. Education: Not explicitly listed in the provided text. His work bridges biology and engineering, emphasizing interdisciplinary approaches such as robotics to explore ecological and evolutionary questions. Recent studies highlight biomimetic shark skin analysis, tuneable stiffness in robotic fish, and the functional morphology of dermal denticles. Collaborations span fluid dynamics, material science, and theoretical biology. Publications emphasize robotics as a comparative tool, biomimetic design, and the integration of experimental and computational methods. While no awards are explicitly listed, his roles as MCZ Curator and Harvard College Professor reflect institutional recognition. Advising is paused temporarily, but his lab (Lauder Lab) continues research on fish locomotion, robotics, and biological fluid mechanics. The lab is located at 26 Oxford Street, Cambridge, MA, under MCZ facilities.

• Artificial Intelligence
• Supply Chain
• Sustainability
• +6 more

Evelyn Xiaoyue Gong is an Assistant Professor of Operations Management at the Tepper School of Business , Carnegie Mellon University . She holds a PhD in Operations Research from MIT (2023) and a BS in Honors Mathematics and Interactive Media Arts from New York University (2017) . Research Interests : Developing artificial intelligence solutions for supply chains and sustainability with provable performance guarantees. Online assortment optimization, pure exploration in reinforcement learning, and data-driven decision-making . Recent Work Trends : Her publications focus on applying reinforcement learning and optimization algorithms to supply chain sustainability, server deployment under uncertainty, and resource management. Key themes include AI-driven environmental impact reduction and theoretical advancements in online inventory models . Scientific Recognition : Best Dissertation Prize , Supply Chain Conference (2023) Accenture Fellowship (2022-2023) Bayer Women in Operations Research Scholarship (2021) Professional Service : Reviewer for Management Science , NeurIPS 2025 , and IPCO 2025 . Committee member for INFORMS Public Sector Operations Research Best Paper Award (2025).

Ehsan PashajavidView profile

Senior Lecturer

• Stochastic modeling/optimisation
• Microgrids/Smartgrid
• Renewable Energy Resources
• +3 more

Dr. Ehsan Pashajavid is a Senior Lecturer at Curtin University's School of Electrical Engineering, Computing and Mathematical Sciences, within the Faculty of Science and Engineering. His research focuses on stochastic optimization, renewable energy integration, microgrid control, and electric vehicle systems. Research interests include: Microgrid and smart grid control algorithms Renewable energy resource management Power system stability and operation Energy storage optimization Electric vehicle-grid integration His publications demonstrate significant contributions to power system resilience, with recent work emphasizing battery storage economics, fault-tolerant converters, and model predictive control for grid stability. Article trends show strong focus on renewable integration challenges and optimization techniques for modern energy systems. Awards include Senior Member status in IEEE and its Power & Energy, Industrial Applications, and Power Electronics societies. Teaching responsibilities encompass graduate courses in Renewable Power Generation Systems, Smart Grid Control, and Renewable Energy Principles.

Sören LaueView profile

Professor

• Machine Learning
• Optimization Algorithms
• GPU Computing
• +3 more

Prof. Dr. Sören Laue is a Professor of Machine Learning at the University of Hamburg's Department of Informatics. His research focuses on optimization algorithms, machine learning frameworks, and high-performance computing. He leads the Machine Learning research group and developed the GENO optimization framework and the Matrix Calculus toolset. His work emphasizes GPU acceleration, tensor operations, and scalable solutions for classical machine learning problems. Projects: GENO solver (Python-based optimization), Matrix Calculus (derivative computation), and SQL-based tensor operations. Key Research Themes: Optimization frameworks, GPU computing, neural network scalability, and algorithm design. Selected recent publications highlight contributions to tensor calculus benchmarks, GPU-optimized machine learning pipelines, and novel optimization methods. His work bridges theoretical foundations and practical software tools for the machine learning community.

Jackie ChaView profile

Assistant Professor

• Human Factors and Ergonomics
• Healthcare Systems
• Surgical Robotics
• +4 more

Dr. Jackie Cha serves as an Assistant Professor in the Department of Industrial Engineering within Clemson University's College of Engineering, Computing and Applied Sciences. Her research bridges human factors engineering with healthcare innovation, focusing on surgical robotics, physiological signal analysis, and wearable medical technologies to enhance clinical performance and safety. Her academic foundation includes advanced degrees from leading institutions: Ph.D. in Industrial Engineering from Purdue University M.S.E. in Biomedical Engineering from the University of Michigan B.S.E. in Biomedical Engineering from the University of Michigan Cha's research program centers on quantifying human performance in high-stakes medical environments through sensor-based metrics. She investigates nontechnical skills in surgical teams, mental workload during robotic procedures, and ergonomics of exoskeleton implementation in operating rooms. Her work integrates physiological signals, eye-tracking, and proximity sensors to develop objective assessment tools for surgical proficiency and team dynamics. Analysis of her 2023-2025 publications reveals consistent thematic focus on human-robot collaboration in surgery, with emerging trends in AI-driven workload detection (s-DResNet), neural correlates of surgical expertise, and environmental factors affecting robotic surgery outcomes. Key methodological approaches include scoping reviews of human-robot interaction metrics, mixed-methods evaluations of exoskeleton efficacy, and extended reality applications for nontechnical skills training. She leads the ECHO Lab (Engineering for Clinical and Human Outcomes) at Clemson, which develops translational solutions for healthcare human factors challenges. Her lab's work spans from fundamental physiological signal analysis to applied interventions in operating rooms and emergency medical settings.

Gregory J. CarboneView profile

Professor

• Climate Variability
• Drought Monitoring
• Climate Change Impacts
• +1 more

Gregory J. Carbone is a Professor in the Department of Geography at the University of South Carolina. His research investigates climate variability and change impacts on water resources and agriculture, with emphasis on drought monitoring systems and climate scenario development. He earned his Ph.D. from the University of Wisconsin-Madison (1990), M.A. from University of Kansas (1984), and B.A. from Clark University (1982). His research develops tools for drought assessment in data-scarce regions and examines how spatial scale affects climate impact assessments. Research focuses on drought monitoring techniques, climate extremes, and the application of climate information in water resource management. Recent work explores uncertainty in precipitation indices, agricultural sensitivity to drought, and regional climate projections. He co-developed the Carolinas Dynamic Drought Index tool used by water managers. His publications demonstrate consistent innovation in drought monitoring methodologies, with recent advancements in spatial visualization of climate impacts and statistical downscaling techniques. Research integrates geospatial analysis, remote sensing, and statistical modeling. Teaching excellence recognized through multiple awards: Michael J. Mungo Distinguished Professor of the Year (2025) Mortar Board Excellence in Teaching Award (2012) Mungo Undergraduate Teaching Award (2005) He has supervised 6 MS students and served on 50+ thesis committees. Major grants include $3.75 million from NOAA for the Carolinas Integrated Sciences & Assessments program. Professional service includes editorial roles for Physical Geography and leadership in the American Association of Geographers.

Olivier FARGESView profile

Senior Lecturer

• Thermal Engineering
• Energy Systems
• Fluid Dynamics
• +3 more

Olivier FARGES is a Senior Lecturer and HDR (Habilitation à Diriger des Recherches) holder at the University of Lorraine, affiliated with ENSGSI (École Nationale Supérieure de Géologie et Sciences Industrielles) within the Groupe INP. He serves as Director of Industrial Partnerships at ENSGSI and is part of the LEMTA Laboratory (CNRS-University of Lorraine), focusing on multiphysics and multiscale modeling of heat transfer in complex environments. His academic roles include teaching courses such as Heat and Mass Transfer, Fluid Mechanics, Scientific Computing Modeling, and Renewable Energy. Dr. FARGES holds a Ph.D. in Energy and New R&D (2014) and an Engineering degree in Energy Engineering (2010), both from the École de Mines Albi. His research emphasizes coupled conductive-radiative heat transfer in porous media, thermal property characterization of heterogeneous materials, and Monte Carlo-based computational methods for energy systems. He has contributed to advancements in photovoltaic system modeling, solar thermal power optimization, and urban climate studies. His work bridges theoretical and applied thermal engineering, with applications in sustainable energy systems, material science, and industrial partnerships. Key research themes include radiative transfer modeling, multiphysics simulation frameworks, and the development of innovative tools for thermal property measurement and energy performance assessment.

• Maritime safety management and leadership
• Maritime accident and casualty analysis
• Maritime Autonomous Surface Ships (MASS)
• +3 more

Tae Eun Kim is an Associate Professor in Maritime Safety Management at UiT The Arctic University of Norway, working within the Department of Technology and Security. Her research, teaching, and industrial collaboration focus on maritime safety and human factors, with particular expertise in maritime safety management, accident analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. Dr. Kim's research spans four interconnected domains: maritime safety management and leadership, maritime accident and casualty analysis, Maritime Autonomous Surface Ships (MASS), and human factors in maritime operations. She has developed assessment instruments like the Safety Leadership Self-Efficacy Scale (SLSES) and conducted STAMP-based causal analyses of maritime accidents. Her work on MASS addresses safety challenges in mixed navigational environments and examines leadership competencies for autonomous shipping operations. Her human factors research explores how technological advancements impact navigators' performance, crew dynamics, and safety outcomes, including gender parity issues in the maritime industry. Dr. Kim's publication record reveals a strong focus on the intersection of maritime safety, technology, and human performance. Her recent work increasingly addresses autonomous shipping technologies, with numerous publications on AI decision transparency, learning analytics in maritime simulator training, and multi-modal data analysis for nautical skill development. She has conducted systematic reviews on simulator training approaches and scenario design, contributing significantly to methodology development in maritime education and training. Her research demonstrates a clear trajectory toward integrating emerging technologies with traditional maritime safety practices as the industry transitions toward greater automation. Dr. Kim is actively involved in several significant research projects, including the i-MASTER EU Horizon Europe Research and Innovation Project, the REFRAME project, and the SPRICE project (Multidisciplinary approach for spray icing modelling). She is a member of both the Advanced Maritime Ship Operations research group and the Maritime Safety Science (MARSCI) Research Group, demonstrating her commitment to collaborative research in maritime safety science. Dr. Kim teaches several specialized courses at UiT, including SVF-3206 Safety Management and Accident Investigation, TEK-3014 Navigation Technology, MFA-2100 Maritime Digitalization, MFA-8010 Maritime HTO (Human-Technology-Organisation) and Innovation, and MFA-2018 Maritime Administration and Leadership. Her teaching portfolio reflects the interdisciplinary nature of her expertise, bridging engineering, safety science, and organizational behavior in maritime contexts.

• Antenna Design
• Microwave Engineering
• Dielectric Materials
• +2 more

Wolfgang Bösch is a Professor at Graz University of Technology's Institute of Microwave and Photonic Engineering, specializing in advanced RF components and measurement techniques. His research advances high-frequency systems through innovations in antenna technology and electromagnetic theory. Research domains include: metamaterial-based antennas, precision measurement calibration, microwave filter optimization, and 3D-printed RF components. Recent work demonstrates strong focus on millimeter-wave systems and reconfigurable antenna arrays. Publications highlight expertise in: machine learning for filter design, metasurface applications, PCB transitions for high-frequency systems, and uncertainty quantification in RF engineering. Research consistently addresses miniaturization and performance optimization challenges. Awards recognize contributions to measurement science and antenna design: Fellow of IET, Houska Prize, and best paper awards. Current laboratories investigate liquid crystal antenna systems and error calibration methodologies for next-generation wireless systems.

Reza FotouhiView profile

Professor

• Robotics (Dynamics and Control)
• Structural Dynamics and Vibrations
• Computational Mechanics (Finite Element and Optimization)
• +4 more

Reza Fotouhi is a Professor in the Department of Mechanical Engineering at the University of Saskatchewan, specializing in Robotics (Dynamics and Control), Structural Dynamics and Vibrations, Computational Mechanics, and Biomechanics. He leads research in agricultural robotics, finite element modeling, and teleoperated systems. Education: BSc, MSc (Iran) MSc, PhD (University of Saskatchewan) His research focuses on human-robot interaction, vibration control for flexible manipulators, composite material applications, and teleultrasound systems. He has developed mobile platforms for crop phenotyping and optimized control strategies for robotic arms. Recent Article Trends: His work spans telerobotic medical systems, agricultural automation, advanced control algorithms (e.g., Particle Swarm Optimization), and structural analysis of composite materials. Key subfields include musculoskeletal imaging, path planning, and dynamic modeling of flexible systems. Research Groups: Applied Mechanics and Machine Design Control Systems, Robotics and Fluid Power Engineering for Agriculture