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Anestis DounavisView profile

Associate Professor

• VLSI Design Automation
• High-Speed Interconnect Modeling
• Signal Integrity Analysis
• +7 more

Anestis Dounavis is an Associate Professor in the Department of Electrical and Computer Engineering at the Faculty of Engineering, University of Western Ontario. He holds a Ph.D. and is a licensed Professional Engineer (P.Eng.). Research Interests Design Automation of VLSI Circuits Modeling and Simulation of High-Speed Interconnects Signal Integrity (Board, Package, and Chip Level) Electromagnetic Interference and Immunity Analysis Mixed Signal Simulation Model-Order Reduction Techniques Simulation of Microelectromechanical (MEMS) and Optoelectronic Systems His work focuses on developing efficient algorithms for transient analysis of power distribution networks, electromagnetic compatibility, and passive macromodeling techniques. He has published extensively in top-tier IEEE journals, with recent articles spanning waveform relaxation methods, parameterized reduction, and sensitivity analysis. Notable scientific awards include: Ontario Ministry of Research and Innovation Early Research Award (2009) Carleton University Medal for Ph.D. Excellence (2004) Ottawa Centre for Research and Innovation Futures Award (2004) INTEL Best Student Paper Award (2003) University Medal at Master’s Level (2000) He has declined prestigious postdoctoral fellowships, including an NSERC Post-doctoral Fellowship (2003). Teaching recognitions include the University Student Council’s Teaching Honour Roll (2009-2010).

Liam LiView profile

Researcher

• Mixed-Integer Optimization
• Nonlinear Programming
• Electric Power System Operations
• +2 more

Liam Li serves as a Visiting Researcher in the Department of Management Science at Lancaster University Management School. Dr. Li's research specializes in mixed-integer optimization and its applications , particularly addressing complex optimization challenges in electric power system operations . His work develops mathematical models including nonlinear programming and mixed-integer linear/nonlinear programming approaches to solve real-world energy grid problems. His recent publications demonstrate a concentrated research trajectory in power systems optimization, with particular emphasis on transmission switching problems and conic quadratic relaxation techniques. These works bridge theoretical mathematical optimization with practical electrical grid management applications. Dr. Li completed his doctoral research at Lancaster University with a 194-page thesis focused on optimization methods for power system operations, establishing his expertise at the intersection of operations research and electrical engineering.

William Melville DrennanView profile

Professor

• Oceanography
• Atmospheric Sciences
• Air-Sea Interaction
• +3 more

William Melville Drennan is a Professor in the Ocean Sciences Department at the Rosenstiel School of Marine, Atmospheric, and Earth Science, University of Miami. His research focuses on air-sea interaction dynamics, wave-induced stress, and tropical cyclone energy exchange. Current Role: Professor, University of Miami Key Research Areas: Atmospheric Surface Layer, Ocean Wave Modeling, Typhoon Energy Budgets Recent Publications: His work addresses coastal regime flux parameterization discrepancies (2023), nonlinear wave spectrum analysis (2019), and typhoon-induced ocean cooling mechanisms (2017). Research highlights include identifying swell-wind momentum transfer anomalies and improving numerical weather prediction models. Methodologies: Utilizes field campaigns (CLASI, ITOP), buoy observations, and spectral analysis to study turbulent airflow, wave boundary layers, and air-sea flux gradients.

Maria J OlascoagaView profile

Professor

• Oceanography
• Nonlinear Dynamics
• Fluid Dynamics
• +3 more

Maria J Olascoaga is a Professor at the Department of Ocean Sciences within the Rosenstiel School of Marine, Atmospheric, and Earth Science at the University of Miami. She serves as Graduate Program Director for Applied Marine Physics. Her research focuses on nonlinear dynamics in geophysical flows , with emphasis on ocean transport and mixing processes. Key projects include inertial effects on floating object motion, Loop Current system variability, and Lagrangian Coherent Structures in the Malvinas Current. Recent publications highlight her work on Sargassum transport modeling using enhanced Maxey-Riley theory , Lagrangian jet-core structures in the Southwestern Atlantic, and applications of Transition Path Theory for oil spill prediction. Her studies integrate satellite data, drifter experiments, and physics-informed models. She utilizes a thermal shallow-water ocean modeling framework to analyze baroclinic instability and stratified flow dynamics, contributing to understanding of ageostrophic components in coastal regions.

Stanislav AranovskiyView profile

Lecturer

• adaptive control
• nonlinear systems
• parameter estimation
• +3 more

Stanislav Aranovskiy is a Lecturer with the AUT team at CentraleSupélec in Rennes, France, specializing in Control Science and Engineering. He is affiliated with the Rennes Institute of Electronics and Telecommunications and maintains an active role in the international control community as a member of the IFAC Technical Committee 1.2 since 2016 and the IEEE Control Systems Society's Technical Committee on System Identification and Adaptive Control since 2018. He achieved IEEE Senior Member status in 2018, reflecting his significant contributions to the field. Dr. Aranovskiy's research spans several critical areas in modern control theory: Adaptive control and estimation methodologies Nonlinear systems analysis and control design Advanced parameter estimation techniques Observers design for complex dynamic systems Disturbance attenuation methods Dynamic Regressor Extension and Mixing (DREM) framework development His publication trajectory reveals a strategic evolution from fundamental adaptive control theory toward increasingly sophisticated data-driven approaches. Recent work demonstrates substantial contributions to Model Predictive Control (MPC) frameworks, particularly in maintaining relevant datasets using Willems' fundamental lemma. A defining characteristic of his research is the innovative application of DREM methodology across diverse estimation problems, consistently demonstrating superior convergence properties compared to conventional approaches. This work has found applications in power systems, motor control, and signal processing domains. Professional Recognition: Member of IFAC Technical Committee 1.2 (Adaptive and Learning Systems) since 2016 Member of IEEE Control Systems Society Technical Committee on System Identification and Adaptive Control since 2018 IEEE Senior Member since 2018 As a Lecturer at CentraleSupélec, Dr. Aranovskiy contributes to both teaching and research supervision. His HDR (Habilitation à Diriger des Recherches) completed in December 2023 qualifies him to supervise doctoral candidates in the French academic system. His collaborative research network includes prominent scholars such as Alexey Bobtsov, Roméo Ortega, and Anton Pyrkin, indicating a robust research environment focused on theoretical and applied control systems. Dr. Aranovskiy works within the AUT (Automatic Control) team at CentraleSupélec, which forms part of the Rennes Institute of Electronics and Telecommunications. His research group maintains strong interdisciplinary connections, with publications spanning theoretical control advances to practical implementations in renewable energy systems and electromechanical devices.

Yanbing WangView profile

Assistant Professor

• Transportation Cyber-Physical Systems
• Connected and Automated Vehicles
• Dynamical Systems
• +1 more

Dr. Yanbing Wang is a tenure-track Assistant Professor at Arizona State University's School of Sustainable Engineering and the Built Environment (SSEBE), where she leads applied research initiatives with government and industry partners on intelligent transportation systems and mobility analytics. Before joining ASU in 2025, she conducted postdoctoral research at Argonne National Laboratory's Transportation and Power Systems division and earned her PhD in Civil and Environmental Engineering from Vanderbilt University in 2023. PhD, Civil and Environmental Engineering, Vanderbilt University (2023) BS, Civil and Environmental Engineering, University of Illinois at Urbana-Champaign (2018) Dr. Wang specializes in advancing transportation cyber-physical systems (CPS) through computationally-efficient tools for large-scale empirical data generation and analysis. Her work bridges theory and practice via real-world experimentation with Tennessee's I-24 MOTION testbed and collaboration with public agencies. Key research themes include connected vehicle dynamics, adaptive cruise control personalization, and real-time traffic monitoring frameworks. Her 15 most recent publications (2024-2022) demonstrate interdisciplinary trends spanning transportation engineering, computer vision, control theory, and environmental data science. Articles focus on trajectory reconstruction, multi-object tracking algorithms, digital twin infrastructure, and machine learning applications for traffic stability, with notable emphasis on heterogeneous traffic estimation, parameter calibration, and 3D vehicle tracking benchmarks. Cyber-Physical Systems Rising Star (University of Virginia, 2023) Dwight D. Eisenhower Transportation Fellowship (FHWA, 2018-2023) Sidney P. Colowick Graduate Scholarship (Vanderbilt, 2021) Best Student Paper Award at SMC 2020 Dr. Wang advises MS students like Raswanth Prasath, whose work on multi-object tracking was spotlighted at ASU's Graduate Poster Symposium. Her research has been supported by Department of Energy funding at Argonne and a USDOT grant through the Eisenhower Fellowship. She collaborates with institutions including Toyota InfoTech Labs, Mitsubishi Electric Research Laboratories, and UCLA's IPAM, while leading projects like the I-24 MOTION data infrastructure and CIRCLES congestion reduction initiative.

• Mathematics
• Differential Equations
• Nonlinear Analysis
• +3 more

Eduardo Colorado Heras is a Full Professor in the Department of Mathematics at Charles III University of Madrid (UC3M), affiliated with the research group Ecuaciones Diferenciales y Aplicaciones (Differential Equations and Applications). His work centers on nonlinear analysis with applications to physical models, particularly through fractional calculus and coupled PDE systems. Research Focus: Primary interests include: Fractional elliptic operators and inverse problems Coupled nonlinear Schrödinger-Korteweg-de Vries systems Critical exponent phenomena in Brezis-Nirenberg-type problems Existence and regularity of solutions for mixed boundary value problems Variational methods for ground state solutions Publication Trends (2015-2023): Recent works predominantly analyze coupled nonlinear systems (60%), fractional operators (30%), and criticality phenomena (25%), employing variational methods in 85% of publications. Over 70% involve existence proofs for bound/ground states under critical growth conditions. Research Leadership: Principal investigator for 4 competitive grants (2011-2023) from AEI and Spanish Ministry of Economy Supervised 2 doctoral theses (2014, 2019) on elliptic operators Conducted 12+ international research stays (Italy, Spain)

• Simulation Optimization
• Industrial Engineering
• Operations Research
• +5 more

Mevlüde Ebrü Angün is an Associate Professor at Galatasaray University's Faculty of Engineering and Technology, Department of Industrial Engineering. Her research focuses on simulation optimization, industrial engineering, operations research, and disaster management. Doctorate in Operations Research, Katholieke Universiteit Brabant, Netherlands (2004) Postgraduate in Industrial Engineering, Boğaziçi University, Turkey (1998) Undergraduate in Industrial Engineering, Istanbul Technical University, Turkey (1995) Her research interests center on simulation optimization, stochastic programming, and disaster management. She applies these to retail operations, unmanned aerial vehicle (UAV) routing, and humanitarian logistics. Her work combines mathematical programming with practical applications in Turkey and international contexts. Scientific contributions include projects on UAV routing in disaster scenarios, retail assortment planning, and internal audit scheduling. She has supervised postgraduate theses on regression clustering and inventory optimization. Stochastic dual dynamic programming for disaster management Mixed-integer linear programming (MILP) for retail and auditing Risk-averse optimization under uncertainty She has served as a TUBITAK grant reviewer and peer reviewer for journals like Engineering with Computers and European Journal of Operational Research .

• Statistical Inference for Stochastic Processes
• Mathematical Biology
• Mathematical Modeling of Physiological Systems
• +5 more

Susanne Ditlevsen is a Professor in Statistics at the Department of Mathematical Sciences , University of Copenhagen . Her research spans interdisciplinary domains including statistical inference for stochastic processes, mathematical biology, nonlinear dynamics, and computational neuroscience, with applications to physiological systems and marine mammal behavior. Primary research areas: Statistics , Stochastic Processes , Biomathematics Teaching: Undergraduate and graduate courses in Probability , Regression , and Diffusion Models Research Highlights : Developed statistical methods for Hidden Markov Models to analyze narwhal diving behavior (2019), incorporating long-range dependence. Advanced stochastic differential equations with mixed effects for biomedical data (2020), enabling personalized physiological modeling. Co-authored high-impact studies on climate tipping points (2023), including the AMOC collapse warning, which received global media attention. Contributed to neural network modeling (2017) with multi-class oscillating systems and nonlinear dynamics in neuronal systems (2014). Work on α-stable noise and double well potentials (2025) enhances understanding of noise-driven transitions in biological and physical systems. Collaborations : Co-researcher on interdisciplinary projects with Alberto Samson , Eva Löcherbach , and Mads Peter Heide-Jørgensen . Engages with international teams on climate dynamics , computational neuroscience , and biomedical statistics .

• Statistical mechanics of molecular fluids
• Computer simulations of fluids
• Phase equilibria
• +4 more

Assoc. Prof. Milan Předota, Ph.D., is a faculty member at the Department of Physics, Faculty of Science, University of South Bohemia in České Budějovice, Czech Republic. He holds a habilitation in Physics from Charles University in Prague and has been affiliated with the University of South Bohemia since 2003. Education MSc. in Theoretical Physics (1995), Charles University, Prague (with honors) Ph.D. in Physical Chemistry (1998), Charles University, Prague Habilitation (2013), Faculty of Mathematics and Physics, Charles University Professional Roles Post-doctoral Research Associate (University of Tennessee, USA, 1999-2002) Scientific Staff (Institute of Chemical Process Fundamentals, Czech Academy of Sciences, 1995-2013) Assistant Professor (Faculty of Health and Social Studies, 2003-2007; Faculty of Science, 2008-2013) Vice-Dean for Science (Faculty of Science, 2012-) Associate Professor (Faculty of Science, 2013-) Research Interests : Milan Předota specializes in statistical mechanics of molecular fluids , computer simulations of solid-liquid interfaces , and electronic continuum corrections . His work bridges molecular dynamics with experimental validation in areas like mineral-water interactions , biomolecular modeling , and nonlinear optics . He has pioneered pair approximation methods for polarizable fluids and dielectric property analysis at interfaces. Grant Leadership : He led projects such as "Theory and molecular simulation of electric double-layer at solid-liquid interface" (GAČR, 2003-2005), "Computational Study of Interactions of Organic Matter and Biomolecules with Mineral Surfaces" (GAČR, 2013-2016), and "Molecular description of phenomena in electrical double layer" (GAČR, 2017-2019). His collaborative projects include "Molecular simulations of processes at solid-liquid interfaces" (INTER-EXCELLENCE, 2017-2021). Scientific Impact : His publications span Journal of Physical Chemistry , Molecular Physics , and Langmuir , focusing on mineral-water interactions , electrochemistry , and nanofluidics . He supervised doctoral theses on solid/liquid interfaces and biomolecule-surface interactions , with three ongoing projects as of 2022.

Reza JahanbakhshiView profile

Assistant Professor

• Computational Fluid Dynamics
• Chemically Reactive Flows
• Turbulent and Transitional Flows
• +4 more

Reza Jahanbakhshi is an Assistant Professor at the Florida Institute of Technology , affiliated with the College of Engineering and Science and the Department of Aerospace, Physics and Space Sciences . He also serves as Affiliate Faculty in the Department of Mechanical and Civil Engineering . Research Focus: Computational Fluid Dynamics, Chemically Reactive Flows, Turbulent/Transitional Flows, High Mach Number Flows Contact: rjahanbakhshi@fit.edu | (321) 674-8174 | F.W. Olin Engineering Complex, Room 243 His research explores high-fidelity computational studies of transitional and turbulent fluid flows, with applications in aerodynamics, propulsion, and thermal management. Key areas include: Laminar-to-Turbulent Transition in High-Speed Flows Combustion Modeling in High Mach Number Turbulent Flows Turbulent Shear Flows and Mixing Mechanisms Flow Control Strategies for Drag/Heat Transfer Reduction Publications highlight advancements in DNS simulations, stability theory, and machine learning integration for predictive modeling. His work addresses interdisciplinary challenges in turbulence-chemistry interaction and flow optimization. Current team members include Ph.D. student Shipon Roy and undergraduates Jonathan Pollison and Helen Ibrahim , whose projects focus on airfoil optimization and thermochemical interactions in high-speed flows. Facilities: Utilizes the AI.Panther HPC Cluster for large-scale parallel computing in fluid dynamics research.

• Mathematical Analysis
• Applied Mathematics
• Homogenization
• +4 more

Carmen Perugia is an Associate Professor in the Department of Science and Technology (DST) at the University of Sannio . Her academic career spans both Mathematical Analysis and Earth Sciences , with a focus on homogenization , control theory , and paleoclimatic reconstruction using coccolithophore assemblages . Teaching: Mathematics and Computer Science for Biology, Geology, and Biotechnology students. Research: Combines partial differential equations with marine paleoceanography , linking mathematical modeling to climate change analysis. Publication Trends reveal dual expertise: 1) mathematical analysis of degenerate elliptic equations , Bingham flows , and Ginzburg-Landau models , and 2) paleoclimatic studies using coccolithophore proxies to analyze North Atlantic and Mediterranean Sea dynamics over the last 30 ka. Her homogenization research addresses imperfect interfaces and oscillating boundaries , while her control theory work derives observability inequalities for hyperbolic equations . Collaborations include international researchers from Finland , Germany , India , and Portugal . Her teaching emphasizes mathematical foundations for biological and geological applications , with office hours by appointment on Tuesdays and Thursdays .

• Energy Network Optimization
• Mathematical Programming
• Time Series Forecasting
• +3 more

Milena Petkovic is a Researcher at the Applied Algorithmic Intelligence Methods department of the Zuse Institute Berlin (ZIB) . Her work focuses on energy network optimization, mathematical programming, and spatio-temporal forecasting in complex systems. Education: Not explicitly mentioned Current affiliation: ZIB, Germany Her research interests include: Mathematical modeling of energy networks Hybrid forecasting approaches combining machine learning and optimization Real-world applications in natural gas transmission systems Analyzing regime changes in gas nomination time series Recent publications highlight trends in: High-dimensional time series prediction for energy systems Constraint-based optimization under supply-demand balance Deep learning applications for gas flow dynamics Hybrid methods integrating FAR, LSTM, and mathematical programming

• Neurosciences
• Cognitive and computational psychology
• Applied mathematics
• +4 more

Dr Paul Expert is a Lecturer in Health Informatics at the Global Business School for Health at University College London since January 2022. His interdisciplinary research bridges complex systems theory, graph/simplicial network analysis, and health informatics. PhD in Physics (Centre for Complexity Sciences, Imperial College London) BSc & MSc in Physics and MSc in Statistics (University of Geneva) His research focuses on: Developing topological data analysis methods for complex systems Mapping patient movement patterns to nosocomial infection risks Creating graph-based biomarkers for schizophrenia Investigating psychedelic effects on brain function Advancing dynamic connectivity frameworks for fMRI data Paul's publications demonstrate cross-disciplinary impact across neuroscience , medical informatics , mathematical modeling , and network theory . His recent work includes: 2025: Force field decomposition on graphs 2025: Maternal sepsis risk factors 2024: Dynamic functional connectivity frameworks 2023: Anesthesia-induced consciousness changes 2022: Electronic health record quality standards

• Civil Engineering
• Construction Materials
• Concrete Technology
• +3 more

Ahmed-Kamel Tedjditi serves as a Teacher-Researcher at CESI Strasbourg Campus within the Engineering and Digital Tools research team, focusing on civil engineering applications for sustainable construction and building performance optimization. His academic credentials include: Doctorate in Civil Engineering from University of Tlemcen (2021) with thesis on cork concrete optimization Master of Research in Civil Engineering from University of Tlemcen (2017) examining reinforced concrete behavior coefficients Bachelor's Degree in Civil Engineering from University of Tlemcen (2015) Tedjditi's research centers on developing innovative construction materials including bio-sourced, low-carbon, and geo-sourced alternatives. He investigates numerical modeling of hygrothermal transfers, energy performance of buildings, and durability mechanisms in concrete/mortars. His expertise spans strength of materials, concrete pathologies, soil mechanics, fluid mechanics, and thermal modeling of construction systems, with emphasis on sustainable material solutions for modern infrastructure. His publication record (2018-2024) reveals concentrated research on cork-based concretes and fiber-reinforced composites, particularly examining thermal conductivity, mechanical properties, and rheological behavior. Key trends include optimizing natural aggregate incorporation (especially cork), analyzing fiber reinforcement impacts (polyester, steel, polypropylene), and developing low-carbon concrete formulations for enhanced building energy efficiency. No scientific awards were documented in the provided materials. Tedjditi actively supervises numerous end-of-study engineering projects and delivers introductory research courses across preparatory and engineering cycles, though specific grant funding details remain unreported. As part of CESI's Engineering and Digital Tools research team, he contributes to initiatives focused on new construction materials development and numerical modeling for building performance analysis, operating from the Strasbourg Campus research facility at Tanneries Park.