Find Academic Supervisors

• Forest Growth and Yield Modeling
• Forest Biometrics
• Pine Plantation Management
• +3 more

Mingliang Wang serves as a Researcher at the Plantation Management Research Cooperative (PMRC) within the Warnell School of Forestry and Natural Resources at the University of Georgia. His expertise centers on forest biometrics, with a specialization in growth and yield modeling for loblolly pine plantations across the southeastern United States, leveraging long-term experimental data to inform sustainable management practices. His research portfolio emphasizes: Forest Growth and Yield Modeling Pine Plantation Dynamics Forest Carbon Sequestration Silvicultural Treatment Impacts Stand Structure Analysis Statistical Biometrics He employs advanced regression techniques and longitudinal studies to quantify effects of thinning, fertilization, and site quality on plantation productivity. Analysis of his 15 most recent publications reveals consistent focus on loblolly pine ecosystems, with dominant themes including carbon stock dynamics, thinning efficacy, and species performance comparisons. Methodologically, he integrates nonlinear mixed-effects models and long-term experimental designs to address critical gaps in plantation forestry science. Dr. Wang actively contributes to the Plantation Management Research Cooperative (PMRC), a collaborative hub advancing science-based solutions for sustainable forest management through partnerships between academia, industry, and government stakeholders.

• Supply Chain Management
• Logistics
• Artificial Intelligence
• +3 more

Batin Latif AYLAK serves as Associate Professor in the Department of Industrial Engineering at the Faculty of Engineering, Turkish-German University, Turkey. Previously, he held an Assistant Professor position at Hitit University starting in 2015. His academic career spans over a decade of research at the intersection of industrial engineering, logistics, and artificial intelligence. His educational foundation includes: Doctorate in Mechanical Engineering from University of Duisburg-Essen (2010-2015) Master's degree in Mechanical Engineering from University of Duisburg-Essen (2008-2010) Bachelor's degree in Industrial Engineering from Istanbul Kültür University (2001-2006) with full scholarship Dr. AYLAK's research pioneers the integration of artificial intelligence in supply chain optimization, with particular emphasis on sustainable logistics systems. His work bridges theoretical advancements with practical applications in blockchain implementation for supply chain transparency, machine learning-driven energy forecasting, and intelligent warehouse management. He has developed novel frameworks like SustAI-SCM for agentic AI in sustainable supply chains and contributed significantly to understanding digital transformation in Turkey's logistics sector. His publication trajectory (2021-2025) reveals a strategic evolution from foundational logistics research toward cutting-edge AI applications. Early work focused on optimization algorithms and blockchain integration, while recent publications demonstrate leadership in agentic AI systems for sustainability, advanced predictive modeling for renewable energy, and pandemic-responsive supply chain solutions. This progression highlights his adaptation to emerging technological paradigms while maintaining core focus on supply chain resilience. No scientific awards or fellowships were documented in the provided materials. Dr. AYLAK has secured competitive research funding including project BAP TAÜ - 2018BM0028 for digital trend analysis in Turkey's logistics sector. While his publications indicate collaborative research with multiple co-authors across institutions, no formal graduate student advisement relationships were specified in the available documentation.

• Financial Markets
• Mathematical Finance
• Derivatives
• +6 more

Vedat Akgiray is a Professor at Bogazici University, holding a Ph.D. from Syracuse University. His teaching and research areas focus on Derivatives , Portfolio Management , Probability , and Financial Markets , with a particular emphasis on Mathematical Finance . He has published extensively on topics such as FinTech, corporate governance, pension systems, and risk management. Education : Ph.D., Syracuse University Email: akgirayv@bogazici.edu.tr

• Particle physics
• High-energy physics
• Beyond Standard Model
• +7 more

Jørgen Beck Hansen is an Associate Professor at the Niels Bohr Institute , University of Copenhagen, specializing in Experimental Subatomic Physics . His career spans roles at CERN and NBI, focusing on particle physics detectors, high-energy collisions, and computational methods. Education: Ph.D. in Particle Physics (1996) and M.Sc. in Physics (1993) from the University of Copenhagen. Research interests include two-boson physics at the ATLAS detector, precision measurements within the Standard Model, effective Lagrangian densities, and searches for new physics beyond the Standard Model (e.g., Higgsless theories, extra dimensions). He also works on GRID computing and distributed data analysis. Recent trends in his research involve Higgs boson studies, vectorlike top quarks, photonuclear collisions, and detector trigger optimization. Collaborative efforts with the ATLAS Collaboration and Danish NORDUGRID team highlight his interdisciplinary approach. Scientific awards : Skou Stipend (Assistant Professor) from the Danish Natural Science Council Teaching and supervision include mentoring 5 summer students, 2 Ph.D., 4 Master's, and 10 Bachelor's students. He has contributed to popular science through Danish Cosmic Rays at Schools and public lectures. Labs and teams : Actively involved in the ATLAS Collaboration and the Danish NORDUGRID team for distributed computing infrastructure.

• Gravitational Physics
• Cosmology
• Astrophysics
• +5 more

Jose Maria Ezquiaga is an Associate Professor at the Theoretical high energy, astroparticle and gravitational physics section of the Niels Bohr Institute (NBI), University of Copenhagen's Faculty of Science. He joined NBI as an Assistant Professor in 2022 and was subsequently promoted to Associate Professor. Prior to his position at Copenhagen, he held a prestigious NASA Einstein Fellowship at the University of Chicago. His work focuses on exploiting gravitational wave data to explore fundamental physics questions at the intersection of cosmology and astrophysics. PhD from Universidad Autonoma de Madrid (2019) NASA Einstein Fellow at University of Chicago Associate Professor at Niels Bohr Institute (2022-present) Dr. Ezquiaga's research centers on probing gravity and unveiling the nature of dark energy and dark matter through gravitational wave observations. His work spans gravitational lensing of gravitational waves, black hole formation mechanisms, primordial black holes as potential dark matter candidates, and cosmological applications of gravitational wave data. He actively investigates how gravitational wave observations can test general relativity and alternative theories of gravity in extreme regimes. His recent publications (2023-2025) demonstrate a strong focus on gravitational lensing effects in gravitational wave astronomy, with particular attention to waveform distortions, identification techniques, and cosmological applications. His work on spectral sirens and cosmology from gravitational wave data represents an innovative approach to measuring cosmic expansion without traditional astrophysical assumptions. NASA Einstein Fellow Member of LIGO Scientific Collaboration Member of LISA Consortium Member of Cosmic Explorer Collaboration As a member of multiple major international collaborations including LIGO, LISA, and Cosmic Explorer, Dr. Ezquiaga contributes to both theoretical development and observational analysis in gravitational wave astronomy. His research group focuses on developing novel techniques for extracting cosmological information from gravitational wave signals and testing fundamental physics through multi-messenger observations. He has been involved in numerous significant discoveries related to gravitational wave lensing and its implications for cosmology and fundamental physics.

• Control Systems
• Signal Processing
• Automation Engineering
• +1 more

Professor Minyue Fu is an Honorary Professor in the School of Engineering at the University of Newcastle, Australia, specializing in Electrical and Computer Engineering. With over 30 years of research experience, he has established himself as a leading expert in control systems and signal processing, having published over 500 research papers with an H-index of 55. His academic journey began with a Bachelor's degree from the University of Science and Technology of China, followed by M.S. and Ph.D. degrees from the University of Wisconsin-Madison. Prof. Fu's research interests span a broad range of topics in control theory and signal processing. His work consistently focuses on fundamental theoretical problems with practical applications in diverse fields including power systems, sensor networks, multi-agent systems, and cyber-physical systems. He has made significant contributions to distributed control algorithms, stochastic systems, quantization effects in control, and networked systems. His recent publications (2021-2024) demonstrate continued productivity and relevance in the field, with research spanning decentralized optimal control, anomaly detection in cyber-physical systems, cart-pole control systems, and mean-field games. These works reflect his ability to bridge theoretical control concepts with practical engineering challenges, particularly in the context of modern networked and distributed systems. Fellow of IEEE (2004) Fellow of IFAC (2022) Fellow of Engineers Australia Fellow of Chinese Association of Automation (2018) Throughout his career, Prof. Fu has held significant editorial positions including Editor of IEEE Transactions on Signal Processing (2010-2014) and Associate Editor for several prestigious journals. His research has been supported by numerous grants, though specific details aren't provided in the current text. His laboratory work has focused on practical implementations of control algorithms in various systems, demonstrating the real-world applicability of his theoretical contributions. Prof. Fu has also supervised numerous students throughout his career, though specific names aren't listed in the available information.

Weiwei HuView profile

Professor

• Applied Mathematics
• Partial Differential Equations
• Mathematical Control Theory
• +3 more

Weiwei Hu is a Professor in the Department of Mathematics at the University of Georgia, specializing in applied mathematics with a focus on control theory and fluid dynamics. Her research bridges theoretical analysis and computational methods to address complex problems in partial differential equations and optimal control systems. She received her Ph.D. in Mathematics from Virginia Tech, establishing the foundation for her expertise in mathematical modeling and analysis. Her educational background directly informs her innovative approaches to fluid dynamics and control problems. Professor Hu's research spans approximation and mathematical control theory of partial differential equations, optimal control of transport and mixing via fluid flows, well-posedness and long-time behavior of mathematical fluid dynamics, data-driven optimal control for network dynamics, computational methods for model reduction, and reliability analysis of renewable systems. She develops advanced theoretical frameworks and numerical algorithms to solve boundary control problems in Stokes and Navier-Stokes flows, with applications in engineering and environmental systems. Her publication record from 2018-2023 reveals consistent advancement in fluid flow control, particularly in optimal mixing and transport phenomena. She has pioneered numerical methods for boundary control of fluid systems while expanding into data-driven approaches for network dynamics and renewable energy applications. Her collaborative work with institutions including Kansas State University, Missouri S&T, and Carnegie Mellon University demonstrates the interdisciplinary impact of her research. Her scientific contributions have been recognized with the prestigious Humboldt Research Fellowship for Experienced Researchers in 2024. Professor Hu has secured over $1.5 million in research funding as principal investigator from NSF, AFOSR, and DARPA, including a 2023-2026 AFOSR grant on hybrid control of semi-dissipative systems and multiple NSF collaborative projects addressing deep-learning-enabled optimization for power systems and computational methods for optimal transport. Her grant portfolio reflects leadership in securing competitive funding for high-impact mathematical research. She actively collaborates with researchers across the United States and Europe on interdisciplinary projects integrating PDE modeling, machine learning, and topology analysis for applications in MRI analysis and renewable energy systems, demonstrating strong leadership in collaborative mathematical research.

Tomislav PlesaView profile

Lecturer

• Synthetic Biology
• Mathematical Biology
• Biochemical Systems
• +4 more

Dr. Tomislav Plesa is a Lecturer and Fellow at Peterhouse, University of Cambridge. His research bridges mathematics and biology, focusing on synthetic biology and the construction of deterministic/stochastic dynamical systems for biological substrates. He completed his PhD at the University of Oxford (2018) and postdoctoral work at Imperial College London (2021). Education: Doctoral Research, Mathematical Institute, University of Oxford (2018) Postdoctoral Research, Department of Bioengineering, Imperial College London (2021) Research Interests: Dr. Plesa investigates design principles of living systems and challenges in biochemical system design. His work includes integral feedback mechanisms, stochastic approximations, noise utilization in molecular computing, and chemical reaction network dynamics. He explores both theoretical and applied aspects of synthetic biology, with a focus on deterministic/stochastic modeling and mathematical approximations. Publication Trends: Recent works (2023–2024) emphasize chemical reaction networks, integral feedback, and stochastic control. Earlier publications (2016–2021) address noise dynamics, bistability, and homoclinic bifurcations. His research spans nonlinear dynamics, biomathematics, and computational biology, often integrating synthetic biology with theoretical frameworks.

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.

• Electrical Engineering
• Signal Processing
• Fault Detection
• +5 more

Tarik Namas is a Senior Lecturer in the Department of Electrical and Electronics Engineering at the International University of Sarajevo's Faculty of Engineering and Natural Science. With over 15 years of academic experience, he has held roles including Teaching and Research Assistant (2006-2009), Technical and Industrial Instructor at Jubail Industrial College (2009-2011), and IT Assistant at Prince Sultan Military College. His expertise spans Electrical Engineering , Signal Processing , and Power Systems , with a focus on fault detection, impedance analysis, and augmented reality applications in healthcare.

Christoph MüllerView profile

Professor

• Climate Change Ecology
• Nitrogen Cycle
• Soil Science
• +7 more

Christoph Müller is a Professor of Experimental Plant Ecology at Justus Liebig University Giessen (since 2009) and a Visiting Professor at University College Dublin's School of Biology and Environmental Science (since 2007). His work bridges soil science, plant ecology, and climate change biogeochemistry. PhD in Soil Science (Lincoln University, NZ, 1995) MSc in Soil Water Management (University of Reading, 1991) Diploma in Horticulture (FH, 1990) Research centers on climate change impacts on terrestrial ecosystems , focusing on elemental cycles and trace gas production in soils. He pioneered 15N/13C isotope tracing to quantify gross nitrogen transformations and developed Ntrace software for analyzing these processes. His landmark Giessen FACE experiment (20+ years) demonstrates how elevated CO2 alters rhizosphere microbiomes and nutrient dynamics. Recent publications (2021-2023) reveal mechanisms linking soil clay minerals to nitrogen cycling, quantify DNRA patterns across ecosystems, and explore biochar-nitrapyrin synergies for emission reduction. Grants from EPA Ireland and Department of Agriculture Ireland support his work on greenhouse gas mitigation and sustainable fertilization . Collaborations span institutions like UCD, with co-authors including Gerald Moser , Daniela Senkbeil , and Lea Meng . Current editorial roles involve European Journal of Soil Science and Frontiers in Terrestrial Microbiology . His methodology integrates stable isotope tracing , metabarcoding , and process-based modeling to unravel soil-plant-microbe interactions.

• Energy Engineering
• Fuel Cell Technology
• Thermal Systems Modeling
• +3 more

Marcin Wołowicz, PhD in Engineering , is a researcher at the Department of Rational Use of Energy within the Institute of Heat Engineering at Warsaw University of Technology. His academic career focuses on advanced energy system modeling and optimization, with particular emphasis on fuel cell technologies and thermal energy storage solutions. Key research areas: Fuel Cell Modeling & Design Expertise: Thermal System Optimization Specialization: Energy Storage & CO2 Reduction Wołowicz's publication record demonstrates sustained contribution to: Molten Carbonate Fuel Cell applications (11+ papers) Combined Heat and Power systems Thermal integration in power plants Seasonal energy storage solutions Waste heat utilization Supercritical power plant optimization His technical work involves both theoretical modeling (GateCycle, Hysys) and experimental validation across various energy scales from 100cm² laboratory cells to 800MW power stations.

• Computational Fluid Dynamics (CFD)
• Hydraulic Turbines
• Cavitation Modeling
• +4 more

Jean Decaix is a Researcher at the University of Applied Sciences and Arts Western Switzerland (HES-SO Valais-Wallis - Haute Ecole d'Ingénierie ) within the Department of Energy and Environmental Techniques . His work focuses on hydropower systems , computational fluid dynamics (CFD) , and cavitation modeling for hydraulic turbines. Decaix contributes to projects like SCCER-SoE (Supply of Electricity center) and XFlex Hydro , aiming to enhance grid stability through advanced turbine operation. Decaix's research spans Francis and Pelton turbines , with a focus on flow topology , unsteady cavitating flows , and hydraulic short-circuit modes . He develops freely distributable CFD tools for building airflow and turbine efficiency, validated through experimental measurements and numerical simulations . Notable projects : SCCER-SoE (2017-2020): Innovation roadmaps for geothermal and hydropower Solution de transfert d'énergie par pompage-turbinage à petite échelle (2015-2017): Economic model development for small-scale hydropower Decaix's 15 most recent publications (2015-2024) cover topics like cavitation suppression , vortex rope dynamics , Pelton turbine efficiency , and CFD validation for building energy systems. His work emphasizes renewable energy integration and mechanical stress reduction in hydropower plants.

Sung-Woo LeeView profile

Associate Professor

• Medical Physics
• Radiation Oncology
• Radiotherapy
• +3 more

Sung-Woo Lee serves as an Associate Professor in the Department of Radiation Oncology at the University of Maryland School of Medicine, based at the Central Maryland Radiation Oncology Center in Columbia, MD. His educational background includes: Bachelor of Science and Master of Science in Nuclear Engineering from Hanyang University, Seoul, Korea Master of Science in Health Physics from Texas A&M University Ph.D. in Nuclear Engineering (specializing in Health Physics and Medical Physics) from Texas A&M University (2003) Dr. Lee's research focuses on Medical Physics and Radiation Oncology , with expertise in stereotactic radiosurgery systems (Gamma Knife/CyberKnife), image-guided radiotherapy, treatment planning optimization, and imaging dose assessment. His work bridges engineering principles with clinical radiation oncology applications to enhance precision in cancer treatment. Analysis of his 2014 publications reveals concentrated research on comparative effectiveness of stereotactic radiosurgery platforms for brain metastases, CyberKnife prescription parameter optimization, and quantification of imaging dose impacts in robotic radiosurgery. His 2008 foundational work established clinical validation protocols for dual-tube kV localization systems in radiotherapy treatment rooms. Dr. Lee maintains active clinical engagement at the Central Maryland Radiation Oncology Center, where he applies medical physics expertise to advance radiotherapy technology implementation and quality assurance protocols.

Gwenn SmithView profile

Professor

• Neuroimaging
• Geriatric Psychiatry
• Neurodegenerative Disorders
• +6 more

Gwenn Smith, PhD, is a Professor of Psychiatry and Behavioral Sciences at Johns Hopkins University School of Medicine. She serves as Director of the Division of Geriatric Psychiatry and Neuropsychiatry and Co-Director of the Center for Translational Molecular Imaging at Johns Hopkins Bayview Medical Center. Her primary research facility is located at the Department of Psychiatry, 5300 Alpha Commons Drive, Baltimore. Dr. Smith leads a research program focused on molecular neuroimaging of neurodegenerative and mood disorders. For over two decades, her work has centered on: Developing PET imaging methods to study neurobiological mechanisms of cognitive decline Investigating monoaminergic system dysfunction in late-life depression and dementia Mapping treatment response mechanisms for brain stimulation therapies Identifying early biomarkers for Alzheimer's, Parkinson's, and related disorders Her publication portfolio demonstrates consistent focus on multimodal neuroimaging approaches integrating PET, MRI, and proteomic analyses. Recent work emphasizes: Interactions between serotonin degeneration and amyloid deposition Optimization of deep brain stimulation for Alzheimer's disease Neurobiological signatures of psychosis across neurodegenerative disorders Advanced 7T MR spectroscopy applications Dr. Smith directs several neuroimaging initiatives including studies on fornix deep brain stimulation (ADvance trial), blood-brain barrier opening using focused ultrasound, and traumatic brain injury in athletes. She maintains active collaborations across neurology, neurosurgery, and radiology departments to advance translational applications of neuroimaging.