Find Academic Supervisors

Jan H. MikkelsenView profile

Associate Professor

• Antennas and Propagation
• RF Systems
• Microwave Engineering
• +7 more

Jan H. Mikkelsen is an Associate Professor at Aalborg University's Department of Electronic Systems, part of the Technical Faculty of IT and Design. His research focuses on antennas, propagation, millimeter-wave systems, RF sensors, and biomedical engineering applications such as bone fracture monitoring. He has contributed to projects like the MARS2 satellite service system and the SOFT transceiver initiative, emphasizing software-defined radio and satellite communication. Key technical areas include power amplifiers, UWB technologies, RFID systems for cryogenic environments, and adaptive antenna designs using liquid metal. His work bridges theoretical research with practical applications, addressing challenges in mixed-signal circuit design, noise suppression, and 5G systems. Research interests span from fundamental material characterization (e.g., ferromagnetic resonance in hexaferrite crystals) to applied technologies like wearable Bluetooth earbud optimization and cryogenic RFID systems. His projects often involve collaboration with industry and government grants, such as the Danish Council for Independent Research. He has published extensively on topics ranging from spin-wave RF applications to biomedical impedance measurement techniques, reflecting his interdisciplinary expertise in RF engineering and biomedical systems. Notable contributions include reconfigurable Yagi-Uda antennas using liquid metal and advancements in nonlinear amplifier characterization. Despite no listed awards, his work has been cited in fields like wireless sensor networks and satellite communication. He advises on projects involving UWB localization and has a lab focus on antenna design and millimeter-wave systems.

• Mathematical Biology
• Partial Differential Equations
• Population Dynamics
• +3 more

Angel Calsina Ballesta is a Professor in the Department of Mathematics at Universitat Autònoma de Barcelona (UAB). He has held multiple academic roles, including Catedràtic d'Universitat at the University of Girona (2001–2005) and various teaching/research positions at UAB since 1979. His research focuses on mathematical biology, population dynamics, and partial differential equations, with applications to biosciences and theoretical ecology. Education: PhD in Mathematics (UAB, 1984), earlier degrees in Mathematical Sciences (UAB, 1979–1980). Projects: Lead roles in projects like 'Dinámica de poblaciones y modelización matemática de la evolución biológica' (2015–2018) and 'Modelización matemática, biología teórica y dinámica de poblaciones' (2018–2022). Research interests include size-structured populations, stochastic modeling, PDE analysis, and transient dynamics in continuous media. His work contributes to UN Sustainable Development Goals related to education and environmental sustainability.

Arjan van der SchaftView profile

Professor

• Nonlinear Systems and Control Theory
• Multi-Physics Systems Modeling
• Hybrid Systems Analysis
• +3 more

Arjan van der Schaft is a Full Professor of Mathematics at the University of Groningen, affiliated with the Johann Bernoulli Institute for Mathematics and Computer Science. He holds a PhD from the University of Groningen (1983) and has held roles at the University of Twente before returning to Groningen in 2005. His research focuses on nonlinear systems, control theory, and energy-based modeling of physical systems, particularly port-Hamiltonian systems. Key awards include IEEE and IFAC Fellowships, and the 2013 IFAC Certificate of Excellence. His work bridges mathematical theory with engineering applications, including hybrid systems, network modeling, and control of complex systems like power grids and robotics. He has advised five PhD students and contributed to 130+ journal articles and multiple textbooks.

Malte von SchevenView profile

Researcher

• Adaptive structures
• Fluid-structure interaction
• Software Engineering
• +3 more

Malte von Scheven is a Senior Researcher and Deputy Director at the Institute of Structural Analysis and Dynamics at the University of Stuttgart. He holds a Dr.-Ing. degree (2009) and specializes in adaptive structures, fluid-structure interaction, and computational mechanics. Research Focus: Redundancy matrices for structural assessment, high-performance computing, actuator placement optimization Teaching: Finite element methods, computational mechanics, nonlinear structural analysis Leadership: Deputy Director since 2006, conference organizer for ECCOMAS and SMART symposia His work bridges structural mechanics with bio-inspired design, including studies on sea urchin skeletons as models for segmented shells. He has supervised numerous theses on SFRP composites, topology optimization, and adaptive systems. Scientific Engagement: Published 15+ papers on redundancy matrices and FSI Organized mini-symposia at international conferences (ECCOMAS 2024, SMART 2023) Active in university governance through Faculty Council and TIK committee Recent research investigates mechanical modeling of adaptive structures, with applications in civil engineering and architectural geometry. His redundancy matrix framework provides novel performance indicators for robust design and assemblability assessment.

Cun-Hui ZhangView profile

Professor

• high dimensional data
• empirical Bayes
• functional MRI
• +6 more

Cun-Hui Zhang serves as a Distinguished Professor and Co-Director of the Financial Statistics and Risk Management (FSRM) and Master of Science in Data Science (MSDS) programs within the Department of Statistics at Rutgers, The State University of New Jersey. His academic office is located at Hill Center 580, 110 Frelinghuysen Road, Piscataway, NJ 08854, and he maintains primary contact via czhang@stat.rutgers.edu. Zhang plays a pivotal role in advancing statistical education through program leadership and curriculum development. His educational foundation includes a Ph.D. from Columbia University, establishing the theoretical groundwork for his distinguished career in statistical methodology. This advanced training directly supports his research in complex statistical frameworks requiring deep mathematical understanding. Zhang's research program addresses fundamental challenges in high-dimensional data analysis, empirical Bayes methods, functional MRI processing, network data modeling, semiparametric and nonparametric techniques, survival analysis, and theoretical statistical inference. His work bridges abstract probability theory with practical applications in biomedical imaging and modern data science, particularly through the development of computationally efficient algorithms for complex data structures. Current projects demonstrate strong emphasis on methodological innovation for real-world data challenges. Analysis of his 2023-2024 publications reveals consistent focus on tensor factor models for dynamic data, adaptive inference in multi-armed bandit problems, debiasing techniques for regularized estimators, and uniform inference for causal effects with high-dimensional covariates. Key methodological contributions include precise regret bounds in bandit algorithms, simultaneous decorrelation methods for matrix time series, and rate-adaptive procedures for symmetric mean estimation. His work consistently connects theoretical guarantees with practical algorithmic implementations. Zhang has received significant recognition through prestigious fellowships: Institute of Mathematical Statistics (IMS) Fellow American Statistical Association (ASA) Fellow As Co-Director of the FSRM and MSDS programs, Zhang actively mentors graduate students and shapes curriculum for professional master's programs in statistics and data science. His research group benefits from sustained grant funding supporting work in high-dimensional statistics, though specific grant details aren't provided in the source material. He contributes significantly to the academic community through program leadership and methodological innovation. Within the Department of Statistics at Rutgers University, Zhang is integral to the research ecosystem, contributing to collaborative projects and fostering interdisciplinary work particularly at the intersection of statistics, machine learning, and biomedical applications. His ongoing research continues to influence both theoretical statistics and practical data science methodologies.

David SchlipfView profile

Research Professor

• Wind Turbine Control
• Wind Farm Control
• Lidar Systems Optimization
• +3 more

David Schlipf is a Research Professor at the Wind Energy Technology Institute (WETI) within the Department of Energy and Biotechnology at Flensburg University of Applied Sciences, a position held since 2018. He also teaches wind energy fundamentals, control engineering, aerodynamics, and advanced mathematics at both Flensburg University of Applied Sciences and the University of Stuttgart. He founded sowento , a renewable energy startup, and holds leadership roles including Operating Agent of IEA Wind Task 32 (since 2016), Treasurer of the European Academy of Wind Energy (since 2017), and Editor at Wind Energy Journal (since 2020). His doctoral research at the University of Stuttgart focused on 'Lidar-Assisted Control Concepts for Wind Turbines'. Subsequent research at the University of Colorado Boulder and NREL specialized in floating wind turbine control. Research Focus: Schlipf's work spans wind turbine/wind farm control, lidar system optimization, and measurement data processing. Key areas include: Advanced control strategies (feedforward, model predictive) Lidar-assisted turbulence measurement and load mitigation Floating offshore wind dynamics International standardization (IEA Wind Task 32) Publications: His 15 most recent articles emphasize lidar integration for turbine/farm optimization. Predominant themes include feedforward control architectures, model predictive strategies for load reduction, floating turbine stabilization, and lidar data processing techniques. Field validations (e.g., CART3 platform, INNWIND.EU 10MW turbine) and international collaboration frameworks are recurrent elements. Leadership & Entrepreneurship: As Operating Agent of IEA Wind Task 32, he coordinates global R&D in lidar-assisted control. He co-founded sowento to translate academic research into renewable energy solutions.

Sohaib ObeidView profile

Assistant Professor

• Aerospace Engineering
• Fluid Dynamics
• Flow Control
• +3 more

Sohaib Obeid serves as an Assistant Professor in the School of Engineering within the College of Engineering, Business & Education at the University of Bridgeport. His office is located in the Engineering & Technology Building, Room #133, and he can be contacted at sobeid@bridgeport.edu. His academic credentials include: B.Sc. in aerospace engineering from the Military Technical College, Egypt M.Sc. in aerospace engineering from the University of Addis Ababa, Ethiopia and the University of Khartoum, Sudan DET in fluids and transfers from Ecole Nationale Supérieur de l'Aéronautique et de l’ espace, Toulouse, France Ph.D. in Mechanical engineering from Clarkson University, USA Dr. Obeid's research spans aerospace engineering, fluid dynamics, and computational methods with significant contributions to aerodynamic performance analysis, active flow control systems, and environmental fluid dynamics. His work integrates theoretical modeling, numerical simulations, and experimental validation to address challenges in aviation and public health. He maintains active research interests in RANS simulations, NARMAX-based control algorithms for airfoil flow separation, and the transport dynamics of respiratory aerosols in indoor environments. His interdisciplinary approach bridges traditional aerospace engineering with contemporary public health concerns, particularly in airborne disease transmission. Analysis of his publication record reveals a clear evolution from fundamental aerospace applications toward interdisciplinary environmental health research. Early work focused on aerodynamic optimization of airfoils and turbomachinery using computational fluid dynamics, while recent publications demonstrate increasing engagement with public health applications through aerosol transport modeling. This trajectory reflects growing recognition of fluid dynamics' role in understanding disease transmission pathways. No scientific awards are documented in the available profile information. Details regarding student advising, research grants, or sponsored projects are not specified in the current profile. His professional background includes service as an Aerospace Engineer at airbases in Sudan and Ethiopia, research positions across nine countries (Sudan, Egypt, Ethiopia, Iraq, France, Brazil, South Korea, and the USA), and faculty appointments at institutions in Sudan, France, and the United States. Information about specific laboratories, research teams, or collaborative initiatives is not provided in the available materials.

Mohammad Ali AyoubiView profile

Associate Professor

• Multibody Dynamics
• Rotordynamics
• Spaceflight Dynamics
• +4 more

Dr. Mohammad Ali Ayoubi is an Associate Professor in the Department of Mechanical Engineering at Santa Clara University's School of Engineering. He holds a Ph.D. in Aeronautics and Astronautics from Purdue University (2007), an M.S. in Aerospace Engineering from Sharif University of Technology (1998), and a B.Sc. in Mechanical Engineering from Amirkabir University of Technology (1991). His research focuses on dynamics and control systems for aerospace applications, including: Multibody and spacecraft dynamics Vibration control of rotating machinery Intelligent control algorithms (fuzzy logic, neural networks) Guidance systems for reentry vehicles and spacecraft attitude control Recent publications (2016-2024) demonstrate strong emphasis on spacecraft control, vibration suppression, and optimal guidance methods, frequently employing advanced techniques like Takagi-Sugeno fuzzy models and data-driven approaches. Awards & Honors: AIAA Leadership Award (2019) ASME Fellow (2016) NASA Faculty Fellow (2013-2014) Researcher of the Year, Santa Clara University (2013) Teaching excellence awards from Purdue University (2004-2006)

Yasushi HamanakaView profile

Professor

• Plasmonics
• Optical Spectroscopy
• Non-linear Optics
• +5 more

Yasushi Hamanaka is a Professor at the Nagoya Institute of Technology , affiliated with the Graduate School of Engineering in the Materials Function Field . He holds a Doctorate in Engineering from Osaka University (1995) and has an academic background in Applied Physics from Osaka University (BSc 1990, MSc 1992). His research focuses on plasmonics , nonlinear optics , and semiconductor nanomaterials , particularly AgInS2 , CuInS2 , and lead halide perovskites . He has secured significant grants from JSPS and private foundations for projects on quantum dot superlattices , pressure-dependent optical properties , and green synthesis methods . Scientific Awards : Meishokai Award (2022.11) Enai Kagaku Gijutsu Zaidan Prize (2016.03) Meishokai Award (2013.11) Professional Memberships : The Japan Society of Applied Physics (2007) Physical Society of Japan (1992) Society of The Nano Science and Technology (2005) Japan Institute of Metals (2015) His laboratory synthesizes metal/semiconductor nanoparticles via liquid-phase laser ablation and colloidal methods , emphasizing environmentally friendly fabrication and optical device applications . Collaborations include high-pressure studies and industrial partnerships for energy conversion materials.

• Condensed Matter Physics
• Superconductivity
• Quantum Transport
• +6 more

Dr. Doru Cristian Sticleț is a distinguished Researcher at the National Institute for Research and Development of Isotopic and Molecular Technologies (INC DTIM) , specializing in Quantum Engineering . With a PhD in Theoretical Physics from Université Paris-Sud (2012) and an MSc from Utrecht University (2009), his work bridges fundamental research and applied quantum technologies. PhD: Theoretical Physics , Université Paris-Sud (2012) MSc: Theoretical Physics , Utrecht University (2009) His research spans Condensed Matter Physics , Superconductivity , Topological Materials , and Quantum Transport . Key areas include Majorana bound states in semiconductor-superconductor hybrids, Berry phases, quantum dynamics in non-Hermitian systems, and Josephson junctions. He leads projects on quantum computation with Schrödinger cat states and stability analysis of organic battery materials via DFT simulations. Recent collaborative projects focus on: Full-stack error-corrected quantum processors using cat codes (2020–2024) Thermodynamic stability of conjugated sulfonamides MOFs for Li-ion batteries (2021–2023) Entanglement in non-Hermitian Hamiltonians (2021–2023) Quantum transport in 2D transition metal dichalcogenides (2020–2022) Foundational work for Romania's participation in the European Quantum Technologies Flagship (2018–2021) His peer-review activities and project coordination roles highlight his contribution to advancing quantum research infrastructure in Europe.

Samira Shirzaei NicholsView profile

Assistant Professor

• Operations Research
• Public Health
• Gender Equity
• +4 more

Samira Shirzaei Nichols serves as an Assistant Professor in the Department of CISA (Computer Information Systems and Analytics) at the College of Business, University of Central Arkansas (UCA), with contact details including email sshirzaei@uca.edu, office COB 305D, and phone (501) 450-5331. Her academic role integrates quantitative analytics with real-world problem-solving across public health, social equity, and business operations. Her research spans Operations Research, Public Health, and Gender Equity, employing machine learning, statistical modeling, and simulation to address epidemiological forecasting (HIV/COVID-19), gender pay disparities in academia/business, and service system optimization. Key methodologies include ARIMA/SARIMA time-series analysis, RNN neural networks, mixed-methods approaches, and Society 5.0 simulation frameworks, demonstrating interdisciplinary rigor in translating theoretical models to societal challenges like refugee health access and grocery store operational efficiency. Analysis of her 15 publications (2014-2025) reveals an accelerating focus on public health crises since 2020, with 60% of recent work dedicated to pandemic response modeling and gender equity analysis. While early research centered on supply chain optimization (2014-2018), post-2020 outputs pivot toward urgent health applications—evidenced by 5 COVID-19 forecasting studies—and structural inequities, using comparative data (2018 vs. 2021) to quantify gender pay gaps across academic disciplines. Her work consistently bridges technical analytics with human-centric outcomes. No information is available regarding student advising, grant funding, laboratory facilities, or research teams from the provided sources, though her prolific publication record indicates active scholarly engagement.

Raj DharaView profile

Assistant Professor

• Mathematical Analysis
• Partial Differential Equations
• Functional Analysis
• +8 more

Dr. Raj Dhara is an Assistant Professor at the Department of Mathematical Modeling, Lodz University of Technology. His academic work spans mathematical analysis of degenerate PDEs, fractional calculus, and computational methods, alongside interdisciplinary research in materials science focusing on optoelectronic properties and sensor development. Key Research Areas: Partial Differential Equations Functional Analysis Nonlocal Equations Organic Electronics Optoelectronic Sensors Nanoscale Modeling The 15 most recent publications highlight expertise in both mathematical theory and applied materials science, with a focus on nonlinear systems, eigenvalue problems, and molecular design for light-emitting devices. Conference contributions include multiscale modeling techniques for MEMS arrays.

• Asset Pricing
• Climate Finance
• Macro-finance
• +5 more

Prof. Dr. Ole Wilms is an Assistant Professor at the University of Hamburg's Faculty of Business, Economics and Social Sciences , Department of Economics, focusing on Macroeconomics and Fiscal Policy . He also holds a part-time Associate Professorship in Finance at Tilburg University. Education : Ph.D. in Management and Economics from University Zurich, M.Sc. in Quantitative Finance from Kiel University, B.Sc. in Economics from Kiel University. Research Focus : Asset pricing, climate finance, macro-finance, machine learning applications in economics, investor disagreement effects on financial markets, and nonlinear dynamic model methodologies. Publications : Published in top journals including the Journal of Finance , Review of Financial Studies , and Journal of Financial Economics , with recent emphasis on climate risk pricing and economic modeling techniques. Academic Affiliations : Active in research teams at both University of Hamburg and Tilburg University, mentoring doctoral researcher Marlene Renkel. Contact : ole.wilms@uni-hamburg.de

• Partial Differential Equations
• Control Theory
• Fluid Dynamics
• +1 more

Takéo Takahashi serves as an Inria Research Director and leads the SPHINX project team at Inria Nancy–Grand Est, affiliated with the Institut Élie Cartan de Lorraine (IECL) under the University of Lorraine's Faculty of Science and Technology in Vandœuvre-lès-Nancy, France. His role centers on advanced mathematical research within the institution's Partial Differential Equations team. His research expertise spans partial differential equations, control theory, and fluid dynamics, with emphasis on controllability, stabilization, and well-posedness of fluid systems. Key investigations include Navier-Stokes equations, Oseen systems, Burgers equation, and fluid-structure interactions, alongside interdisciplinary applications in cosmic-ray physics and population dynamics. Analysis of Takahashi's 2024-2025 publications reveals a dominant focus on mathematical control theory for fluid dynamics, particularly Carleman estimates for Oseen systems and small-time controllability. His work bridges theoretical PDE analysis with practical applications, extending to astroparticle physics through graph neural network implementations for cosmic-ray reconstruction. As head of the Inria SPHINX project team, he directs research on complex systems modeling and control theory development within the Nancy–Grand Est region.

Luis David Avendaño-ValenciaView profile

Associate Professor

• Structural Dynamics
• Structural Health Monitoring
• Condition Monitoring
• +7 more

Luis David Avendaño-Valencia is an Associate Professor in the Department of Mechanical Engineering at the University of Southern Denmark's College of Engineering. His research focuses on structural dynamics, monitoring, and damage detection under time-dependent environmental and operational conditions, integrating signal processing, statistics, and machine learning. Education: PhD in Mechanical and Aeronautical Engineering (2016), BEng in Electronic Engineering (2007) External Roles: External Censor at Censorkorps (2023–present), Member of the Danish Center for Applied Mathematics and Mechanics (DCAMM) (2018–present) His work emphasizes system identification and damage diagnosis algorithms for wind turbines, marine systems, and other structures. Key methodologies include Gaussian Process Regression, Bayesian updating, and Linear Parameter Varying (LPV) models. He has contributed to offshore wind turbine blade diagnostics, marine diesel engine monitoring, and uncertainty quantification in vibration analysis. Recent publications highlight hybrid physics-data-driven approaches and multivariate regression techniques to mitigate environmental/operational variability. Collaborations span maritime engineering, wind energy, and machine learning-based diagnostics. He teaches courses on machine learning for structural monitoring, structural vibrations, and time-series methods. Supervision includes PhD projects on digital twins of axial piston pumps and operational regime clustering for wind turbines.