Find Academic Supervisors

Aurelio MuttoniView profile

Academic

• Concrete Structures
• Structural Engineering
• Material Science (Concrete)
• +5 more

Aurelio Muttoni is an Honorary Professor at EPFL’s School of Architecture, Civil and Environmental Engineering (ENAC), where he led the Concrete Construction Laboratory from 2000 to 2024. He holds a diploma and doctorate in civil engineering from ETH Zurich (1982 and 1989). His teaching focuses on structural design, concrete structures, and bridge design. Research interests include concrete behavior, innovative structural design, shear forces, nonlinear analysis, bond mechanics, and ultra-high-performance concrete. He co-founded engineering consultancies Muttoni Partners and Lurati Muttoni Partner. Key awards include the Freyssinet Medal (2022), Chester Paul Siess Award (2010), and Wason Medal (2014). He co-authored the Eurocode EN 1992-1-1 (2023). Education: Diploma in Civil Engineering, ETH Zurich, 1982 Doctorate in Civil Engineering, ETH Zurich, 1989 Research Highlights: Behavior and design of concrete structures Innovative structural concepts (e.g., textile/concrete composites) Shear force analysis and punching shear Aggregate interlocking and material durability Ultra-high-performance concrete applications Professional Contributions: Advised 30+ PhD/Master’s students at EPFL Co-founded engineering firms focusing on structural design and consultancy Lead role in drafting Eurocode 2’s second generation Recent Article Trends: Focus on experimental methods (e.g., crack kinematics imaging), bond-slip mechanics, and shear failure verification in modern concrete structures. Emphasis on integrating advanced models into codes like Eurocode 2.

• Remote Sensing
• Forest Ecology
• Vegetation Indices
• +4 more

Paul is a Professor affiliated with the University of Aarhus, recognized internationally for his expertise in remote sensing and ecological modeling. He has served as an Opponent in a doctoral defense within the Faculty of Theology, though his research primarily focuses on forest dynamics, vegetation indices, and radiative transfer processes in boreal ecosystems. His work bridges remote sensing technologies with ecological applications, emphasizing leaf area index (LAI) estimation, canopy structure analysis, and albedo modeling. Research Interests: Paul specializes in remote sensing methodologies , including satellite and airborne data analysis, to study forest reflectance, canopy photon recollision probabilities, and vegetation-climate interactions. His studies often address boreal forest ecosystems in Finland and the Arctic, exploring how structural and optical properties influence Earth's energy balance and carbon cycles. Publications Trends: His articles (2005–2021) highlight advancements in LAI estimation using DSCOVR and MODIS data, the role of understory vegetation in reflectance, and the theoretical underpinnings of canopy radiation models. Recent work (2020–2021) also touches on medical topics like neonatal platelet function, suggesting interdisciplinary engagement. Paul has been actively involved in validating global Earth system data records and advancing algorithms for vegetation monitoring. His contributions have implications for climate modeling, forest management, and ecological conservation efforts.

Harmen de WeerdView profile

Assistant Professor

• Human-machine teamwork
• Multi-agent systems
• Agent-based modeling
• +3 more

Harmen de Weerd is an Assistant Professor at the Faculty of Science and Engineering, University of Groningen. He is affiliated with the Bernoulli Institute for Mathematics, Computer Science and Artificial Intelligence. His research focuses on human-machine teamwork, agent-based modeling, and higher-order reasoning. Key interests include strategic interaction among artificial systems and humans, with a focus on cooperation dynamics and decision-making under uncertainty. Research areas include multi-agent systems, theory of mind modeling, negotiation strategies, and computational linguistics. Notable work examines how artificial agents can enhance human cognitive processes through interactive training and simulation. His studies often blend AI, game theory, and cognitive science to explore complex social interactions. Publications span topics like lie detection mechanisms, predictive theory of mind models, and cross-cultural game-playing behaviors. He has contributed to agent-based simulation frameworks for bargaining dialogues and developed methodologies for estimating higher-order reasoning in human-agent systems. His work emphasizes practical applications in educational technology, behavioral change modeling, and metacognitive agent design. The Bernoulli Institute provides his primary research infrastructure, focusing on interdisciplinary computational science and AI innovation.

Anzhong WangView profile

Professor

• Theoretical Physics
• Gravitational Wave Physics
• Quantum Cosmology
• +4 more

Dr. Anzhong Wang is a Professor of Physics at Baylor University, affiliated with the College of Arts & Sciences' Department of Physics and Astronomy. He joined Baylor in 2003, with prior academic roles at institutions in Brazil, China, and the U.S. His research focuses on classical/quantum gravity, gravitational waves, black holes, and cosmology, particularly addressing dark matter/energy and early universe dynamics. He teaches courses such as General Relativity and Quantum Mechanics. Education: Ph.D. in Physics, Ioannina University (1991) M.S. in Physics, Northeast Normal University (1986) B.S. in Physics, Shandong Normal University at Liaocheng (1983) His research explores gravitational wave cosmology, black hole physics, and quantum cosmology. He has advised numerous Ph.D. and Master’s students, and his work has been published in leading journals like Physical Review D and Nature . He collaborates globally, including with institutions in Brazil, Japan, and China. Recent publications highlight studies on loop quantum gravity effects, gravitational wave propagation, and dark matter halo interactions with black holes. His contributions bridge theoretical frameworks with observational cosmology, addressing gravitational physics at fundamental scales.

Aditya MahajanView profile

Professor

• Control Theory
• Stochastic Processes
• Reinforcement Learning
• +4 more

Aditya Mahajan is a Professor in the Department of Electrical and Computer Engineering at McGill University, Montreal, Canada. He holds affiliations with prominent research institutes including Mila (Quebec Artificial Intelligence Institute), CIM (Center for Intelligent Machines), GERAD (Group for Research in Decision Analysis), and ILLS (International Laboratory for Low Temperature Science). His research focuses on stochastic control, reinforcement learning, decentralized systems, and multi-agent decision-making. Key themes include analysis of Markov decision processes (MDPs), robust control strategies, and optimization in partially observable environments. He explores theoretical foundations of actor-critic algorithms, human-automation collaboration, and networked control systems with applications to robotics and autonomous systems. Recent work emphasizes scalable methods for complex systems, including approximation techniques for MDPs with unbounded costs, delay-resistant stochastic approximation, and policy design in POMDPs. His contributions span both algorithmic innovations and rigorous theoretical analysis, bridging gaps between control theory and modern machine learning paradigms. Major research directions include: Reinforcement learning in decentralized and partially observable settings Optimal control for human-machine teams Robustness and convergence properties of stochastic algorithms Multi-agent systems and mean-field games His articles highlight advancements in control theory, with recent attention to: Decision-making under cognitive load Convergence guarantees for Q-learning variants Structural results for restless bandits and resource allocation He participates in interdisciplinary collaborations through his affiliations, contributing to AI applications in robotics, energy systems, and networked control architectures.

• Forest Growth & Yield
• Silviculture
• Forest Inventory
• +4 more

Robert Froese is a Professor and Endowed Chair in Forest Growth & Yield at the University of Alberta's Faculty of Agricultural, Life and Environmental Sciences (Renewable Resources Department). He specializes in forest growth modeling, silviculture, and remote sensing applications. Froese holds a PhD and professional certifications (RPF, CF). His research focuses on optimizing forest management through growth/yield models, climate adaptation, and inventory techniques. Education: PhD (details unspecified). Research Interests: Froese's work addresses forest dynamics under climate change, including growth/yield prediction, regeneration patterns, and biomass estimation. He employs LiDAR and spectral analysis to improve inventory accuracy, while exploring sustainable harvest practices and their ecological impacts. Teaching: Teaches courses like Forest Measurements (REN R 215), Forest Growth & Yield (REN R 448/548), and Forestry Field Schools (REN R 702/295). Course content integrates field skills, statistical analysis, and simulation modeling. Labs/Teams: Leads the Forest Growth & Yield Lab at the University of Alberta, focusing on operationalizing growth models and climate-resilient management strategies.

Omar LaghroucheView profile

Professor

• Structural Dynamics
• Vibration Analysis
• Finite Element Methods
• +5 more

Professor Omar Laghrouche is a faculty member at Heriot-Watt University's School of Energy, Geoscience, Infrastructure and Society, within the Institute for Infrastructure & Environment. He holds a PhD from École Centrale de Nantes and has been at Heriot-Watt since 2004. His research focuses on structural dynamics, vibration analysis, and efficient numerical methods for wave modelling, including soil-structure interaction and railway-induced ground vibrations. He leads projects on high-speed rail infrastructure, geotechnical testing, and thermal-mechanical effects. Education: PhD in Soil-Structure Interaction, École Centrale de Nantes, France Postdoctoral Research, Durham University Research Interests: Acoustic/Elastic Wave Modelling Railway Track Dynamics and Mitigation Finite Element Methods (FEM) Geotechnical Centrifuge Testing Recent Contributions: His work spans high-speed rail infrastructure in Indonesia, damping reduction factors in seismic engineering, and electromagnetic scattering solutions using Bernstein–Bézier elements. He has pioneered validated 3D models for slab-track systems and geosynthetic-reinforced railway substructures. Awards: 2024 Heriot-Watt PRIME Award for Innovation 2014 Society of Petroleum Engineers R&D Grand Challenges 2003 UKACM Best Postdoctoral Presentation Labs & Equipment: Manages the Railway Test Rig and True Triaxial (GeoTT) facilities, enabling full-scale testing of railway components and geotechnical materials. His work bridges experimental validation and computational modelling in infrastructure engineering.

Michael BackesView profile

Associate Professor

• Gamma-ray Astronomy
• Active Galactic Nuclei
• Data Mining
• +3 more

Prof. Michael Backes is an Associate Professor and Head of Astrophysics Research at the University of Namibia (UNAM), leading the Namibian H.E.S.S. group and founding director of the Virtual Institute for Scientific Computing and Artificial Intelligence. He holds concurrent roles as Extraordinary Associate Professor at North-West University (South Africa) and Academic Visitor at the University of Oxford (UK). His research focuses on gamma-ray astronomy of Active Galactic Nuclei (AGN), data analysis methodologies, and next-generation telescope projects like the Cherenkov Telescope Array (CTA) and Africa Millimetre Telescope (AMT). Education : MSc (Dipl.-Phys.) in Physics (2008, TU Dortmund University) PhD (Dr. rer. nat.) in Astroparticle Physics (2012, TU Dortmund University) Research Interests : Gamma-ray astronomy of AGN, multi-wavelength observations, advanced data mining techniques, and instrumentation development. He pioneered semiconductor-based camera technology for gamma-ray telescopes and contributed to major collaborations like FACT and MAGIC. Key Projects : Co-PI of AMT, Namibian-PI of H.E.S.S. observatory projects, and Co-Investigator on the ERC Synergy grant 'Blackholistic'. Active in steering committees for H.E.S.S. and IAU's Southern African Regional Office of Astronomy for Development. Recognition : Annie Maunder Medal 2024 (Royal Astronomical Society), UNAM Meritorious Award 2017, GYA membership (2018–2023), and plenary speaker at World Science Forum 2022. He also chairs the Namibia Scientific Society and drives astronomy outreach initiatives. Labs/Teams : Leads the Namibian H.E.S.S. group and collaborates internationally on major observatories. Founded the Virtual Institute for Scientific Computing and AI to integrate advanced analytics into astrophysical research.

Alexander SchaeferView profile

Researcher

• Robotics
• Autonomous Systems
• Lidar-based Localization
• +6 more

Alexander Schaefer is a researcher in the Department of Computer Science at the University of Freiburg, affiliated with the Autonomous Intelligent Systems group under Prof. Dr. Wolfram Burgard. His work focuses on robotics, particularly lidar-based localization, mapping, and sensor modeling for mobile and agricultural robots. His research interests include autonomous navigation, 3D point cloud processing, sensor fusion, and agricultural robotics. He has made significant contributions to lidar-based mapping, change detection in dynamic environments, and the development of compact and differentiable map representations using cosine transforms. The recent publications highlight a strong trend in urban and agricultural vehicle localization, robust sensor modeling, and probabilistic inference for robot navigation. His work frequently appears in top robotics conferences such as ICRA, IROS, and IEEE RA-L, often in collaboration with leading researchers in the field. Alexander Schaefer has supervised several master's theses on topics including autonomous vehicle localization, multispectral soil mapping, and symmetry-based object detection in agricultural fields. He has also been involved in teaching, notably as a supervisor for the Robot Mapping lecture. He has collaborated on research projects such as the Samsung Global Research Outreach Program and the EU project Flourish, focusing on robotic solutions for smart farming using the Bonirob platform. His work bridges academic research with real-world applications in autonomous systems.

Mark Edwin SchafferView profile

Professor

• Economics of Transition
• Applied Econometrics
• Machine Learning
• +3 more

Mark Edwin Schaffer is a Professor at Heriot-Watt University's School of Social Sciences and Edinburgh Business School. His work bridges applied econometrics and economics of transition, focusing on Central and Eastern Europe, the former Soviet Union, and China. Education AB, Magna Cum Laude in Social Studies, Harvard University (1982) MScEcon in Economics, London School of Economics (1984) MA in Economics, Stanford University (1984) PhD in Economics, London School of Economics (1990) Schaffer's research expertise spans econometric methodology, machine learning applications, and empirical analysis of transition economies. Recent work includes double/debiased machine learning in Stata, stacking regression for time-series forecasting, and fused LASSO in quantile regression. His empirical studies examine wage policies in Russian firms, institutional impacts on growth, and energy demand dynamics. Key contributions include software modules like ACTEST for autocorrelation testing and AVAR for covariance estimation. His 2025 article on model averaging and machine learning highlights his focus on methodological innovation. Earlier work (1990s-2010s) analyzes capital structure in transition firms, fiscal policy, and labor reallocation during economic crises. Schaffer's collaborations span institutions like IZA Institute of Labor Economics and Stanford University. He actively engages in invited talks on machine learning applications in economics, including gender wage gap estimation and conformal inference.

Tony DolphinView profile

Lecturer

• Coastal Geomorphology
• Estuarine Processes
• Sediment Transport
• +6 more

Tony Dolphin is an Honorary Lecturer in the School of Environmental Sciences at the University of East Anglia (UEA) and a member of the Collaborative Centre for Sustainable Use of the Seas. His work centers on coastal and estuarine processes, with a focus on sediment transport, morphodynamics, and coastal protection. His research interests include: Coastal, beach, and estuarine geomorphology Sediment transport in the coastal zone Wave and tidal dynamics Coastal erosion and protection structures Environmental monitoring using remote sensing and field instrumentation Climate change impacts on coastal systems His recent publications show a strong trend toward integrating traditional field-based coastal science with modern remote sensing and drone-based monitoring techniques, particularly in seagrass habitat mapping and post-storm impact assessment. Earlier work emphasizes physical processes such as wave-orbital dynamics, sediment suspension, and the hydrodynamics of tidal channels and intertidal flats. Notable research projects include: LEACOAST and LEACOAST2: Investigating the effects of shore-parallel breakwaters on coastal morphodynamics Blinks: Studying sandbank dynamics and beach responses Children's Corner Beach Dynamics and Shoreline Monitoring Coastal monitoring using photogrammetry and GPS/X-Band radar He has collaborated with institutions such as the Centre for Environment, Fisheries & Aquaculture Science (Cefas), Waveney District Council, and various academic partners across Europe and New Zealand. Tony Dolphin has co-authored numerous peer-reviewed articles in journals such as Journal of Coastal Research , Marine Geology , and Remote Sensing . His work is cited in both academic and policy contexts, particularly regarding storm surge impacts and sustainable coastal management.

• Geomechanics
• Geotechnics
• Soil Modeling
• +5 more

Gustav Grimstad is a Professor at the Department of Civil and Environmental Engineering at NTNU. His research focuses on advanced soil modeling, particularly in geomechanics and geotechnics, with emphasis on creep behavior of soft clays, permafrost dynamics, and landslide mechanics. He has developed influential models like the NGI-ADP model integrated into commercial software (e.g., Plaxis). His work bridges computational methods (e.g., MPM, FEA) with practical geotechnical challenges. Key research areas include hyperplastic constitutive modeling, progressive fracture in sensitive clays, and environmental applications such as carbon-negative soil reinforcement. He collaborates extensively on projects like NUNATARYUK addressing permafrost thawing impacts. His publications span over 20 years, with notable contributions to submarine landslide simulations, offshore wind foundation modeling, and frost heave phenomena. Dr. Grimstad’s expertise extends to numerical methods validation through centrifuge tests and field data, ensuring practical applicability of theoretical models. He advises on infrastructure resilience in challenging geotechnical contexts, including quick clay landslide mitigation and sustainable peat engineering.

Boris ResnikView profile

Professor

• Geodetic Monitoring
• Structural Health Assessment
• Deformation Analysis
• +3 more

Prof. Dr.-Ing. Boris Resnik is a full professor at Berlin University of Technology (BHT Berlin) in the Department of Civil Engineering and Geoinformation. Born in 1960 in Leningrad, he holds a diploma in Geodesy from the Leningrad Mining Institute (1982) and a doctorate from VNIMI (1990). His academic career spans over two decades at BHT Berlin, with prior positions at Rostock University and Brandenburg Technical University Cottbus. His research focuses on: Geodetic monitoring and deformation analysis Structural health assessment of wind turbine foundations AI and neural network applications in structural monitoring Sensor technologies (MEMS, accelerometers, inclinometers) Automated early warning systems for infrastructure He leads significant projects including the IFAF-funded WEsaFE (2014-2016) on wind turbine foundation monitoring and the DAAD Eastern Partnerships initiative (2018-2023) with Central Asian universities. Publication analysis shows a strong evolution toward AI-driven methodologies since 2019, with recent works focusing on neural networks for real-time structural monitoring, vehicle classification, and vibration analysis. His 2023-2025 publications demonstrate increasing integration of drone-based thermography and advanced sensor networks. No scientific awards are documented in the provided materials. Contact is maintained through resnik@bht-berlin.de, with office at Building D (Civil Engineering) Room D 422.

Stanley SnelsonView profile

Associate Professor

• Partial Differential Equations
• Kinetic Theory
• Dynamics of Many-Particle Systems
• +4 more

Stanley Snelson is an Associate Professor at the Department of Mathematics and Systems Engineering, College of Engineering and Science, Florida Institute of Technology. His research focuses on partial differential equations (PDEs) with applications to kinetic theory, shape optimization, and nonlinear waves. Kinetic Theory: Boltzmann and Landau equations, statistical physics, particle dynamics Shape Optimization: Minimal domains for eigenvalues, free boundary problems Nonlinear Waves: Stability of solitary waves, wave equations with nonlinear terms His recent work includes regularity theory for the Landau equation and stability analysis of variable-coefficient scalar-field equations. Supported by NSF Grant DMS-2213407, he collaborates with researchers like C. Henderson, A. Tarfulea, and E. Teixeira. Publications span top journals including Transactions of the AMS and SIAM Journal on Mathematical Analysis . Key applications of his research include modeling wave propagation, structural design optimization, and plasma dynamics. Current and former collaborations with the Simons Foundation and Oak Ridge Associated Universities highlight his contributions to mathematical physics.

Olaf PoschView profile

Professor

• Macroeconomics
• Dynamic Stochastic General Equilibrium (DSGE) Models
• Asset Pricing
• +12 more

Olaf Posch is a Professor of Economics, specializing in Methods of Economics, at the Department of Economics within the Faculty of Economics and Social Sciences at the University of Hamburg. His research integrates macroeconomic theory, econometrics, and computational methods to analyze dynamic equilibrium models, asset pricing, and policy design. Research Interests: His primary research areas include Macroeconomics, Dynamic Stochastic General Equilibrium (DSGE) models, Asset Pricing, Monetary and Fiscal Policy, Econometrics, Structural Estimation, and Continuous-Time Modeling. He investigates the implications of uncertainty, rare disasters, heterogeneous agents, and public policy on macroeconomic dynamics and financial markets. Recent Research Trends: His recent publications demonstrate a consistent focus on advancing the estimation and solution methods of macroeconomic models. He explores the role of uncertainty (e.g., Peso problems, Poisson shocks), the impact of fiscal policy and debt maturity (e.g., FTPL), and the importance of risk in model approximations. His work often bridges theoretical innovation with empirical application, using mixed-frequency data and structural estimation techniques. Scientific Grants: DFG Project No. 268475812: 'Dynamic equilibrium models' – Developing a continuous-time New Keynesian model. DFG Project No. 446166239: 'Fiscal Sustainability'. DFG Project No. 510995673: 'Fiscal policy in models with heterogeneous agents'. Advising and Grants: While specific advisees are not listed, he frequently collaborates with co-authors on research projects and working papers, indicating an active role in mentoring junior researchers. He is the principal investigator on multiple DFG-funded projects, demonstrating significant grant acquisition and research leadership. Laboratories and Research Teams: He leads a research team at the University of Hamburg, including Corinna Kienle, Réka Rátfai, and Josie Oetjen, focused on dynamic equilibrium models and macroeconomic policy analysis.