Find Academic Supervisors

István VargaView profile

Associate Professor

• Traffic Control
• Urban Traffic Modeling
• Intelligent Transportation Systems
• +7 more

István Varga is an Associate Professor in the Department of Control for Transportation and Vehicle Systems at the Faculty of Transportation Engineering and Vehicle Engineering, Budapest University of Technology and Economics. His work bridges theoretical control systems and practical transportation applications, particularly in intelligent traffic management and autonomous mobility. His research interests are centered on traffic control , urban traffic modeling , autonomous vehicles , emission modeling , and intelligent transportation systems . He applies advanced control methodologies such as model predictive control (MPC), set-theoretic control, and LPV modeling to solve real-world traffic problems including congestion, safety, and environmental impact. His work often integrates simulation platforms like VISSIM and MATLAB for system design and validation. The recent publications (2019–2024) reveal a strong trend toward connected and automated mobility , with a focus on V2X communication, platooning in urban environments, dynamic traffic light integration, and testing infrastructure like ZalaZONE. His research also addresses policy-level questions such as speed limit changes and dynamic road pricing using simulation-based impact analysis. The articles consistently emphasize multi-objective optimization, balancing traffic performance with environmental sustainability. István Varga is actively involved in the Hungarian Research Centre for Autonomous Road Vehicles (RECAR), contributing to national-level advancements in autonomous transport technology. His earlier work includes significant contributions to nuclear power plant safety systems, demonstrating interdisciplinary expertise in safety-critical control systems. While specific grants and students are not listed, his extensive publication record and leadership in research initiatives suggest active project involvement and academic supervision. He has contributed to both theoretical frameworks and real-world implementations, including traffic-responsive signal control, emission modeling for motorways, and robust control of industrial systems. His collaborations span academia and industry, with frequent co-authorship with researchers from Budapest University of Technology and Economics and the Hungarian Academy of Sciences.

• Computational Fluid Dynamics
• Vehicle Aerodynamics
• Aerospace Engineering
• +4 more

Dr. Tom-Robin Teschner is a Senior Lecturer in Computational Fluid Dynamics at Cranfield University's Centre for Computational Engineering Sciences. He holds a PhD in Aerospace Engineering from Cranfield University and has previously worked as a software engineer at the German Aerospace Center (DLR). His research focuses on applied aircraft aerodynamics (laminar flow promotion, transition modelling), vehicle aerodynamics (high-performance vehicles), and algorithmic design for reducing computational costs in CFD through hybrid CFD/deep-learning methods. Education: BEng in Aerospace Engineering from Hamburg University of Applied Sciences and University of Seville MSc in Computational Fluid Dynamics from Cranfield University PhD in Aerospace from Cranfield University Research Trends: His recent work combines computational fluid dynamics with machine learning for vortex detection and laminar flow optimization, addressing both aerospace and automotive applications. He collaborates with industry leaders like Airbus , Onera , and McLaren Automotive . Scientific Awards: Erich Becker Scholarship Lord Kings Norton Medal (best PhD thesis among 151 graduates) Advisory & Grants: He supervises research projects on vehicle and aircraft aerodynamics, funded by clients such as ITP Aero (Rolls-Royce), Defence Science and Technology Laboratory , Aston Martin Lagonda , and McLaren Automotive .

Katharina HopfView profile

Researcher

• Nonlinear Partial Differential Equations
• Cross-Diffusion Systems
• Reaction-Diffusion Systems
• +6 more

Katharina Hopf is a Researcher at the Weierstrass Institute in Berlin, where she leads the junior group Multi-species Balance Laws . She also supervises Master thesis projects in analysis and partial differential equations at Humboldt University of Berlin . Research Interests: Analytical aspects of nonlinear evolution PDEs Cross-diffusion and reaction-diffusion systems Interface phenomena and singularities Entropy tools and variational methods Metric gradient flows and mixed-type PDE systems Recent Publications focus on gradient flows, cross-diffusion models, and singularities in PDEs, with applications in viscoelastic phase separation, energy-reaction-diffusion systems, and fluid dynamics. Interdisciplinary work includes modeling reactive gas mixtures in porous media. Scientific Awards: 2020 Faculty Thesis Prize for Mathematics (University of Warwick)

Mitchell McMillanView profile

Research Fellow

• Subduction Zone Geodynamics
• Orogenesis
• Thermomechanical Modeling of Crustal Processes
• +7 more

Dr. Mitchell McMillan is a Postdoctoral Fellow at Georgia Institute of Technology, specializing in geodynamic processes that shape Earth's mountain belts and planetary surfaces. His research integrates thermodynamic modeling with field observations across three distinct domains: Subduction zone fluid dynamics and lower crustal density transformations Wind erosion mechanisms in hyperarid terrestrial and Martian environments Hydrodynamic modeling of fluvial erosion processes His computational work on streambank erosion modeling has produced globally applicable tools available via GitHub, while his recent Earth and Planetary Science Letters publication proposes novel mechanisms for lithospheric foundering. Current projects investigate weak-crust dripping dynamics in the Central Andes and their surface expressions. Key research themes: Crustal metamorphism-driven buoyancy changes Rayleigh-Taylor instability in continental lithosphere Wind erosion quantification in extreme environments Multi-scalar geomorphological modeling

Ezequiel MediciView profile

Adjunct Assistant Professor

• Numerical Modeling
• Heat and Mass Transport
• Porous Media
• +4 more

Ezequiel Medici is an Adjunct Assistant Professor at the Department of Mechanical and Aerospace Engineering, Michigan Technological University. His work bridges numerical and experimental research across multiple disciplines. Research Focus: Modeling phase change and heat/mass transport in porous media and cryogenic systems. Key Applications: PEM fuel cells, volcanic eruption dynamics, cryogenic propellant management, and industrial fluid transport. Publications Trends highlight expertise in: Multi-scale modeling (continuum and pore-network approaches) Cryogenic fluid behavior (liquid hydrogen, supersonic jets) Geophysical shock wave propagation Industrial applications (diapers, heat pipes, oil recovery)

Thomas P.A. van VurenView profile

Researcher

• Stochastic Operations Research
• Machine Learning
• Quantum Gravity
• +3 more

Thomas P.A. van Vuren is a researcher at the Eindhoven University of Technology , affiliated with the School of Mathematics and Computer Science and the Stochastic Operations Research department. His work bridges disciplines such as Stochastic Operations Research , Machine Learning , Quantum Gravity , and Chemical Engineering . His recent research explores Markov Chains and their applications in clustering (2024), Effective Field Theory and Symmetry Breaking in Type IIB string theories (2023), and Turbulent Emulsions with a focus on surfactant dynamics and viscosity asymmetries (2022). These works highlight his interdisciplinary approach to problems in Computer Science , Physics , and Chemical Engineering . Email: t.p.a.v.vuren@tue.nl Collaborations include projects with J. Sanders and S.F.M. van Kempen on AI-driven research (2021-2026), and co-authored works with L. Yi , D. Lohse , and C. Sun on fluid dynamics.

Svetlana TkachenkoView profile

Research Fellow

• Computational Fluid Dynamics
• Renewable Energy Systems
• Building Ventilation
• +7 more

Dr. Svetlana Tkachenko is a Post-Doctoral Research Fellow at the University of New South Wales (UNSW) Faculty of Engineering, Department of Mechanical Engineering. She specializes in computational fluid dynamics and heat transfer modeling with applications in renewable energy systems, building ventilation, and automotive aerodynamics. Her work bridges theoretical modeling with practical industrial applications through collaborations with various industry partners. Education: PhD in Mechanical Engineering, UNSW, Australia (2018) Dr. Tkachenko's research focuses on numerical modeling of fluid flow and heat transfer in renewable energy systems, particularly photovoltaic technologies and building-integrated applications. Her work spans passive cooling techniques for solar panels, building ventilation systems, and thermal management in automotive applications. She employs computational fluid dynamics (CFD), multi-phase modeling, and machine learning techniques to optimize system performance and energy efficiency. Her research has significant implications for improving the efficiency of solar energy systems and building thermal performance. An analysis of her recent publications reveals a consistent focus on heat transfer enhancement in photovoltaic systems, particularly through passive cooling techniques. Her work demonstrates increasing sophistication in modeling approaches, incorporating machine learning for weather data analysis and spectral modeling of PV surfaces. The research trajectory shows progression from fundamental fluid dynamics studies toward practical applications with industry partners. Scientific Recognition: Finalist, 2022 GUD Excellence Awards at the Royal Automobile Club of Victoria in Melbourne for collaboration with Disc Brakes Australia on thermodynamic simulations in brake rotor development Dr. Tkachenko actively supervises research students, currently mentoring two thesis students in renewable energy topics and one in disk brake modeling. She has contributed technical advice to numerous undergraduate and postgraduate theses on topics including photovoltaic cooling, building ventilation, and automotive aerodynamics. She serves as a Chief Investigator on an Australian Renewable Energy Agency (ARENA) grant titled 'Research boost for solar panel efficiency and cost reduction' (2020-2023). Her industry collaborations include partnerships with Disc Brakes Australia, 5B, and international collaborators in France and the UK. Dr. Tkachenko's research group utilizes advanced computational resources including ANSYS, OpenFOAM, and high-performance computing facilities at UNSW's Katana and NCI's Gadi. Her work on smart coatings for PV systems involves collaboration with A&B Smart Materials, an Oxford University-based venture developing novel materials for the photovoltaic industry.

Bertrand CARISSIMOView profile

Lecturer

• Earth Sciences
• Urban Climate Modelling
• Atmospheric Dispersion
• +4 more

Bertrand CariSSIMO is a Lecturer at École des Ponts ParisTech (ENPC), affiliated with the Center for Teaching and Research in Atmospheric Environment (CEREA), a joint lab with EDF R&D. His research focuses on micro-meteorological measurements and numerical modeling for urban climate applications, including pollution dispersion around industrial sites and wind farms. He holds an Engineer degree from the School of Hydraulics, Grenoble; a PhD from Princeton University; and a HDR (Habilitation à Diriger des Recherches). Key research interests include: urban climate dynamics, pollutant dispersion in complex environments, CFD modeling for atmospheric flows, and radiative/convective thermal exchanges in urban settings. His work integrates advanced numerical methods, such as time-staggered schemes for variable density flows, and employs tools like Code_Saturne and MUNICH street network models. Recent studies highlight innovations in parameterizing tree effects in street canyons, low-wind dispersion mechanisms, and thermal modeling of city centers. His interdisciplinary approach combines technical modeling with participatory urban quality assessments.

Benoît GoyeauView profile

Researcher

• Fluid Dynamics
• Porous Media Flow
• Thermal Convection
• +3 more

Benoît Goyeau is a researcher at the Mathematics and Computer Science for Complexity and Systems laboratory. His work focuses on fluid dynamics, porous media flow, thermal convection, and mathematical modeling of transport phenomena. He has contributed extensively to understanding interfacial fluid-porous medium interactions, boundary layer dynamics, and multiphase flow systems. Recent research emphasizes compressible flow modeling, membrane fouling mechanisms, and stability analysis of natural convection in porous-fluid systems. His research integrates experimental approaches with computational fluid dynamics, addressing challenges in heat transfer, mass transport, and material science. Key contributions include advancements in jump boundary condition theories for fluid-porous interfaces and pore network modeling of shear-thinning fluid behavior. Collaborations span multi-institutional teams, with frequent co-authorships on topics like thermosolutal convection and interfacial momentum transfer. Publications highlight innovations in porous media mechanics, including ATR-FTIR analysis of biomolecule interactions and experimental studies on convective flow structuring. His work bridges theoretical models with practical applications in energy systems, biomedical engineering, and materials characterization.

• Quantum Chromodynamics
• Hydrodynamics
• Heavy-ion Collisions
• +3 more

Jacquelyn Michelle Noronha-Hostler serves as Associate Professor in the Department of Physics at the University of Illinois Urbana-Champaign and holds a parallel appointment as Associate Professor at the National Center for Supercomputing Applications (NCSA), demonstrating her dual expertise in theoretical nuclear physics and high-performance computational methods. Her research program leverages supercomputing infrastructure to model extreme states of matter created in relativistic nuclear collisions. Her primary research domains encompass Quantum Chromodynamics (QCD), relativistic hydrodynamics, heavy-ion collision dynamics, and quark-gluon plasma characterization. She specializes in developing computational frameworks for smoothed particle hydrodynamics to investigate collective flow phenomena, conservation laws for quantum numbers (baryon number, strangeness, charge), and precision signatures of phase transitions in nuclear matter. Her work bridges theoretical predictions with experimental data from facilities like the Relativistic Heavy Ion Collider and Large Hadron Collider. Analysis of her 2025 publications reveals three dominant research thrusts: (1) precision studies of collectivity using exotic isotopes like neon-20 in small collision systems, (2) Bayesian statistical approaches to locate the QCD critical point through holographic duality methods, and (3) jet quenching phenomena in quark-gluon plasma characterized by nuclear modification factors and elliptic flow. These efforts consistently involve large international collaborations, as evidenced by multi-institutional authorship across her 124 total research outputs. No scientific awards were documented in the provided materials. While student advising details are absent from the scraped content, her active grant-funded research program (implied by NCSA affiliation and computational focus) likely supports graduate researchers. Specific grant mechanisms remain unmentioned in the available text. Her NCSA appointment indicates leadership within computational physics teams utilizing supercomputing resources for nuclear theory simulations. Though specific laboratory names aren't provided, her work inherently connects to the Blue Waters and Delta supercomputing initiatives at NCSA, where she contributes to developing hydrodynamic frameworks like v-USPhydro for relativistic collision modeling.

YAN WentaoView profile

Associate Professor

• Additive Manufacturing
• Computational mechanics

Dr. YAN Wentao is an Associate Professor at the Department of Mechanical Engineering, National University of Singapore (NUS), where he joined in August 2018. He holds a PhD from Tsinghua University (2017) and a Bachelor's degree from the same institution (2012). Prior to NUS, he was a postdoctoral fellow at Northwestern University and a guest researcher at the National Institute of Standards and Technology. His research focuses on Additive Manufacturing and Computational Mechanics , specifically developing multi-scale models for process-structure-property relationships in metal 3D printing. His work integrates experimental validation with high-fidelity simulations to optimize manufacturing processes. Analysis of his 15 most recent publications (2016-2021) reveals a strong emphasis on: Powder dynamics and defect mechanisms in laser/electron beam processes Multi-physics modeling of melt pool behavior and microstructure evolution Data-driven approaches for process optimization and quality control Novel applications in functional materials and composites Awards include: 9 awards in the 2022 AM-Bench Simulation Challenges Materials Research Letters Impact Award (2022) He has supervised doctoral students to graduation, including Dr. Chen Fan. Leads the Yan Research Group at NUS, which collaborates internationally and has hosted visiting scholars like Dr. Shinji Sakane.

Sterling OrtegaView profile

Assistant Professor

• Neuroimmunology
• Multiple Sclerosis
• Stroke neuropathology
• +3 more

Sterling Ortega, PhD, is an Assistant Professor in the Department of Microbiology, Immunology & Genetics at the University of North Texas Health Science Center (UNTHSC), within the College of Biomedical and Translational Sciences. His research focuses on neuroimmunology, particularly the role of adaptive immunity in brain health and disease. He holds a BS in Biology from the University of Dallas, an MS in Biomedical Sciences from Barry University, and a PhD in Integrative Biology from the University of Texas Southwestern Medical Center. His postdoctoral training included studies on B-cell roles in ischemia-induced brain injury. Research Interests: Dr. Ortega investigates immune-mediated neurological dysfunction, targeting therapies to reverse conditions like multiple sclerosis (MS) and stroke. Key goals include identifying CD8+ T-cell roles in stroke neuropathology, myelin-reactive T-cells in MS recovery, and novel therapeutic applications. Techniques employed include cell culture, flow cytometry, animal models, and cerebral organoids. Projects: He has led seven sponsored projects, including studies on BCAA efficacy in stroke, cerebral organoid technology in neuroimmunology, and brain-targeting immune cells. Notable collaborations explore adaptive immunity in pediatric ECMO patients and stroke immunology. Labs/Teams: His lab integrates immunological and neuroscientific approaches to advance therapies for neuroimmune disorders. Current work emphasizes multi-organismal strategies for functional recovery post-stroke and MS.

Carmela BernardoView profile

Research Fellow

• Opinion Dynamics
• Multi-agent Systems
• Consensus Algorithms
• +3 more

Carmela Bernardo is a Research Fellow in the Department of Engineering at Università degli Studi del Sannio (UNISANNIO). Her academic work focuses on opinion dynamics, consensus algorithms, and multi-agent systems within the field of control theory. She teaches 'LEARNING FOR DYNAMICS AND CONTROL' for the Master's Degree program in Electronics Engineering for Automation and Sensing, with office hours held on Wednesdays from 10:00 to 12:00 at PalaUNISANNIO. Dr. Bernardo's research centers on mathematical modeling of social dynamics, particularly exploring the Hegselmann-Krause opinion dynamics model and bounded confidence frameworks. Her work investigates how confidence thresholds affect opinion clustering, develops mixed logical dynamical models for opinion evolution, and examines consensus achievement in systems with stubborn agents. She has made significant contributions to understanding finite-time convergence in asymmetric models and the synchronization properties of Kuramoto oscillators under bounded confidence constraints. Her publication record demonstrates a clear progression from theoretical foundations to practical applications, with recent work including comprehensive surveys that synthesize knowledge in bounded confidence opinion dynamics. The most recent publications show expansion into experimental verification of theoretical models and applications to complex real-world scenarios. Dr. Bernardo maintains an active collaboration network with researchers including Francesco Vasca, Claudio Altafini, and Trisha Srivastava. Her work appears in high-impact journals such as AUTOMATICA, IEEE TRANSACTIONS ON AUTOMATIC CONTROL, and NATURE COMMUNICATIONS, reflecting the interdisciplinary nature of her research that bridges control theory with social dynamics.

David StanfordView profile

Professor

• Queueing Theory
• Stochastic Processes
• Actuarial Science
• +4 more

David Stanford is a Professor in the Department of Statistical and Actuarial Sciences at the University of Western Ontario. He earned his Ph.D. from Carleton University in 1981. His office is located in WSC 211 and he can be contacted via phone (519-661-2111 x83612) or email. Research Focus: Dr. Stanford's research spans several interconnected domains including: Queueing Theory : Specializing in multi-server systems, priority queues, and service optimization Actuarial Science : Risk modeling, ruin theory, and insurance mathematics Healthcare Operations : Applying stochastic models to transplant systems and patient flow Environmental Modeling : Forest fire prediction using compound Poisson processes His work frequently combines theoretical stochastic processes with practical applications in healthcare and environmental systems. Publication Trends: Analysis of recent publications shows a strong focus on queueing theory applications in healthcare systems, particularly modeling patient flow and organ transplant logistics. His actuarial research emphasizes advanced ruin probability calculations and risk process modeling. Environmental applications feature stochastic approaches to natural disaster prediction.

Vidar SkogvollView profile

Senior Lecturer

• Artificial Intelligence in Education
• Computational Physics
• Topological Defects
• +4 more

Vidar Skogvoll serves as a Senior Lecturer at the Centre for Teaching and Learning in Science (KURT) within the Department of Physics at the University of Oslo's Faculty of Mathematics and Natural Sciences. His work bridges computational physics research and innovative science education methodologies, with particular focus on integrating generative artificial intelligence into academic instruction. He maintains active roles in both the Interface Dynamics in Geophysical Flows (EarthFlows) research group and the Center for Computing in Science Education (CCSE). Skogvoll's research spans computational physics (specializing in topological defects and phase field crystal modeling) and AI-enhanced education . His ComFiT library represents significant contributions to open-source scientific software, while his educational projects explore scaffolding techniques for student use of large language models. He actively develops resources through llmteaching.com and comfitlib.com , and produces educational content through dual podcast platforms focusing on science pedagogy and popular science. His publication record demonstrates consistent output in high-impact physics journals including Physical Review B, Journal of Mechanics and Physics of Solids, and Modeling and Simulation in Materials Science and Engineering. The research exhibits strong methodological continuity in computational approaches to material defects while showing recent expansion into AI applications for education. Key thematic threads include topological defect dynamics, phase field modeling, and computational methodology development. Notable recognitions include: Third place in Norwegian Physics Olympiad (2011) The King's watch awarded by Trondheim Katedralskole (2011) Skogvoll leads multiple educational initiatives including the development of AI-integrated teaching materials and maintains an active blog on AI in education with recent 2025 publications. His podcast work ( Real læring and Under kappa ) extends his science communication efforts to broader audiences. He teaches core physics courses including Mechanics, Oscillations and Waves, Thermodynamics, and Mathematical Methods in Physics, demonstrating comprehensive engagement with the department's educational mission.