Find Academic Supervisors

• Numerical Analysis
• Quantum Theory
• Multiscale Modeling
• +4 more

Daniel Massatt is an Assistant Professor in the Mathematics Department at Louisiana State University (LSU) since August 2022. Previously, he served as a Kruskal Instructor at the University of Chicago's Statistics Department from 2018 to 2022. His research focuses on numerical analysis, quantum theory, multiscale modeling, spectral theory, topological insulators, incommensurate materials, and electronic structure. He has taught courses such as Fourier Transforms, Mathematical Models, and Numerical Linear Algebra at LSU, and probability and numerical analysis at the University of Chicago. Massatt's work emphasizes theoretical and computational studies of low-dimensional materials, particularly twisted 2D heterostructures and topological insulators. He develops mathematical frameworks to model electronic properties in systems with structural incommensurability, such as bilayer graphene. His contributions include analyzing defect states, Kubo conductivity, energy minimization, and topological invariants in such systems. He collaborates with experimentalists to bridge theory and practical applications in twistronics and correlated electron systems. His research has been published in journals like Physical Review B , Multi-scale Modeling & Simulations , and European Physical Journal B . Notable projects include modeling electronic observables in momentum space, studying convergence of planewave approximations, and exploring topologically protected transport in twisted bilayer graphene.

Shu-Guang LiView profile

Professor

• Hydrology
• Water Resources Engineering
• Groundwater Systems Modeling
• +3 more

Shu-Guang Li is a Professor in the Department of Civil and Environmental Engineering at Michigan State University's College of Engineering. His research integrates hydrology, applied mathematics, and computational sciences to advance groundwater modeling and decision-making tools. He has received funding from NSF, EPA, and other agencies, and serves as an associate editor for journals like the ASCE Journal of Hydrologic Engineering. A registered professional engineer, he is a Fellow of both the American Society of Civil Engineers and the Geological Society of America. Education: Ph.D., Water Resources and Environmental Engineering, MIT (1993) M.S., Computational Fluid Mechanics, University of Iowa (1990) M.S., Hydraulics, Chengdu University of Science and Technology (1985) B.S., Hydraulic Engineering, Chengdu University of Science and Technology (1982) Research focuses on stochastic approaches for groundwater systems, including uncertainty quantification, multiscale modeling, and GIS integration. His work bridges theoretical and applied hydrology, addressing challenges in water resources management and environmental protection. Awards highlight recognition for his contributions to engineering education and groundwater research, including the Michigan DEQ Director Team Award (2009) and Fellowship distinctions (2007). Grant activities include NSF-funded projects on stochastic modeling and environmental systems. Advising and student mentorship are integral to his role, though specific advisee names are not listed in the provided text. His research group likely contributes to interdisciplinary efforts in environmental engineering and computational hydrology.

Peidong WuView profile

Professor

• Metal forming
• Finite element analysis
• Plasticity and formability
• +6 more

Professor Peidong Wu is a faculty member in the Department of Mechanical Engineering at McMaster University, Canada. His research focuses on advanced manufacturing, materials engineering, and solid mechanics, with expertise in finite element analysis, plasticity, and biomechanics. B.Sc., Zhejiang University (1982) M.Eng., China University of Mining and Technology (1987) Ph.D., Delft University of Technology (1994) His research involves constitutive modeling of rubbers/polymers , metal deformation analysis , numerical simulation of material instabilities , and multiscale modeling of manufacturing processes . He integrates computational methods with experimental validation to study material behavior under extreme conditions. His awards include the International Magnesium Medal (2020) , NSERC Discovery Accelerator Supplement (2011) , and the International Journal of Plasticity Medal (2009) . He teaches graduate courses in finite element analysis (MECH ENG 4T03/6T03/705) and mentors students in computational mechanics and manufacturing processes.

Sharad Kumar GuptaView profile

Researcher

• Remote Sensing
• Ecological Modelling
• Environmental Informatics
• +3 more

Sharad Kumar Gupta is a Guest Scientist at the Helmholtz-Centre for Environmental Research - UFZ in Leipzig, Germany, and a Scientist at the Center for Advanced Systems Understanding (CASUS) in Görlitz. His research focuses on remote sensing , environmental informatics , and geospatial data analysis with applications in ecological modelling , UAV technology , and environmental risk assessment . Education Ph.D. in Remote Sensing (2015) - Indian Institute of Technology Mandi M.Tech in Geoinformatics (2014) - NIT Bhopal B.Tech in Computer Science (2011) - Uttar Pradesh Technical University Research Highlights Developed Drone4Tree cloud platform for UAV-based tree canopy detection Specialized in hyperspectral data scaling and agricultural stress monitoring Published extensively on environmental data integration , geophysical inversion , and urban green infrastructure Affiliations Dept. Monitoring and Exploration Technologies, UFZ Dept. Earth Systems Research, CASUS (HZDR) Key Publications address landslide susceptibility mapping , UAV-based environmental monitoring , machine learning applications in agriculture, and multi-method data integration for subsurface analysis. His work appears in journals like EGU General Assembly , Permafrost Periglacial Processes , and Environmental Earth Sciences .

• Hydrological modeling
• Flood forecasting
• Drought monitoring
• +4 more

Robert Schweppe is a Researcher at the Department of Computational Hydrosystems , Helmholtz Centre for Environmental Research (UFZ) in Leipzig, Germany. He has held this position since 2017, following prior roles as Project Engineer at HYDRON GmbH (2014-2017) and Research Assistant at UFZ (2013). Expertise in hydrological modeling using mHM, ECLand, LARSIM Developed pyflow configuration tools and MPR software for environmental data processing Key contributor to 4DHyro project integrating Earth Observation data with hydrological models His research interests span hydrological modeling , drought forecasting , machine learning applications , and climate change impacts on water systems. His 2022 publications on parameter regionalization and floodplain modeling demonstrate methodological innovations in environmental data analysis. Notable scientific recognitions include the Deutschlandstipendium scholarship (2012-2013) and Helmholtz Field Study Fellowship (2022). He collaborates extensively with European institutions on compound environmental risks and smart monitoring technologies .

• Dynamical Systems
• Complex Systems
• Cognitive Science
• +4 more

Dr. Polemnia (Nia) Amazeen is a Professor in the Department of Psychology at Arizona State University (ASU), with cross-disciplinary affiliations including the Biosocial Complexity Initiative, Center for Social Dynamics and Complexity (CSDC), and Institute for Social Science Research. She also serves as a Senior Global Futures Scientist within ASU's Global Futures Scientists and Scholars program. Education: Ph.D. in Center for the Ecological Study of Perception and Action, University of Connecticut, 1996 Postdoctoral Training, Vrije Universiteit - Amsterdam Her research centers on identifying universal mathematical principles of dynamical similitude across diverse behavioral systems. Specializing in dynamical systems and complex systems theory, she develops analytical frameworks for real-time detection of behavioral transitions and anomalies using multiscale data streams (neural, physiological, kinematic, communication). Her work bridges cognitive science, human factors, and artificial intelligence to decode complex human behavior through interdisciplinary lenses including kinesiology and psychology. Analysis of her 15 most recent publications (2002-2024) reveals consistent application of nonlinear dynamics to coordination phenomena across scales—from neural signatures in team cognition to motor-respiratory synchronization. Key trends include fractal/multifractal analysis of behavioral data, pink noise effects on state transitions, and computational modeling of memory foraging. Her work increasingly integrates real-time analytics for human-autonomy teaming applications. Scientific Awards: HFES Jerome H. Ely Award for Best Paper in Human Factors Amazeen has chaired or served on Ph.D. dissertation committees for 14 students including J. G. Holden, J. E. Butner, and A. Likens. Her research is funded by major federal agencies including NSF, ARL, DARPA, ONR, and USAMRMC, supporting investigations into team coordination dynamics and human-system interactions. She leads the Dynamics of Perception, Action, and Cognition (DPAC) research group, which develops analytical dashboards for translating complex behavioral data into actionable insights for military personnel, educators, and scientists through cross-disciplinary collaboration.

• Biomedical Engineering
• Complex Medical Engineering
• Networked Systems
• +14 more

Dr. Shahab Abdulla serves as an Associate Professor at the University of Southern Queensland within the College of English Language, specializing in pathway programs for international students transitioning to tertiary education. His academic role bridges mathematics, engineering, and language preparation through foundational courses including Linear Systems and Control, Mathematical Methods, and General Science. His academic qualifications include: BSc from University of Technology, Baghdad MSc from University of Technology, Baghdad PhD from University of Southern Queensland Dr. Abdulla's research spans Biomedical Engineering , Complex Medical Systems , and Networked Control , with pioneering work in Deep Learning for environmental forecasting and medical diagnostics. His AI research encompasses Neural Networks, Reinforcement Learning, and graph-based models applied to climate impact assessment and resource management, reflecting a commitment to solving interdisciplinary global challenges through computational innovation. Analysis of his 15 most recent publications reveals consistent application of decomposition techniques (wavelet, Fourier, curvelet) integrated with deep learning architectures across domains including ocean energy forecasting, medical imaging, and social network analysis. This demonstrates a methodological signature of combining signal processing with AI to extract patterns from complex temporal and spatial data. Though specific awards aren't detailed, his leadership is evidenced by chairing IEEE conferences and international committee service. He has supervised over 14 higher-degree research students while leading the Advanced Data Analytics Modelling Research Simulation Group, generating 55+ Q1 journal publications with 1000+ recent citations and 30+ global seminars. The Advanced Data Analytics Modelling Research Simulation Group under his direction develops AI-driven solutions for environmental monitoring, medical diagnostics, and engineering systems, maintaining active collaborations across the Middle East, US, Japan, Europe, China, and Canada.

• Non-destructive Testing
• X-ray physics
• Physical modelling and simulation
• +7 more

Philipp Schütz is a Professor at the Lucerne School of Engineering and Architecture (HSLU), part of the Lucerne University of Applied Sciences and Arts. He holds dual appointments in the Institute of Mechanical Engineering and Energy Technology (IME) where he leads the CC Thermal Energy Storage research group, and the Institute of Natural and Social Sciences (ING). His office is located in Room E300/E311 at Technikumstrasse 21, 6048 Horw, Switzerland. Dr. Schütz earned his Physics degree from ETH Zürich with specialization in theoretical physics and optics. He completed his PhD in 2009 at the University of Zürich's Biochemical Institute, focusing on computer-aided modeling of spectroscopy experiments and pattern recognition in biochemical networks. From 2010-2014, he worked as a researcher at Empa in Dübendorf developing non-destructive testing methods before joining HSLU in September 2014 as a Physics lecturer. He completed a Certificate of Advanced Studies in Higher Education Didactics in 2015 and the 'Exzellenz in der Lehre' program in 2019. Professor Schütz's research spans Non-destructive Testing with emphasis on X-ray computed tomography , Energy System Modeling , and Computational Physics . His work on phase change materials and thermal energy storage has led to significant advancements in understanding calcium chloride hexahydrate solidification and salt hydrate behavior. He combines experimental work with sophisticated computational modeling, including Monte Carlo simulations and high-performance computing approaches. His expertise in algorithm development for large image datasets has applications across energy systems, materials science, and archaeological conservation. His publication record shows a clear evolution from fundamental physics toward applied engineering solutions, with recent work (2023-2025) increasingly focused on practical thermal energy storage applications for residential and district heating systems. The integration of X-ray computed tomography with energy system modeling represents his unique interdisciplinary approach. Professor Schütz actively leads numerous research initiatives including SWEET PATHFNDR, SWEET DeCarbCH TES, WindCoEconomy, and INTERSTORES. He teaches Mathematics & Physics for Engineering students and Time Series Analysis in the Master of Science in Applied Information and Data Science program. His research group operates advanced X-ray computed tomography facilities for studying material properties, energy storage systems, and conservation methods for archaeological materials, bridging theoretical physics with practical engineering applications in the energy sector.

• Bioengineering
• Biomedical Engineering
• Computational Biomechanics
• +7 more

Clark Meyer is a Senior Lecturer in the Department of Bioengineering at the University of Texas at Dallas, within the Erik Jonsson School of Engineering and Computer Science. He holds a PhD and BS in Biomedical Engineering from Texas A&M University, completed in 2009 and 2002 respectively. His research spans computational bioengineering with a focus on cardiovascular biomechanics, tissue engineering, and oncological applications. Key interests include finite element modeling of atherosclerotic arteries, in silico tissue engineering, dental biomechanics, and RNA-targeting therapies for solitary fibrous tumors. He also explores 3D printing for surgical training in cleft lip and palate cases. Recent publications (2017–2024) demonstrate a strong emphasis on integrating clinical data with computational models to predict biological responses, improve medical devices, and develop targeted gene therapies. His work bridges engineering principles with clinical applications in cardiology, oncology, and maxillofacial surgery. While no formal awards or fellowships are listed, his scholarly output reflects sustained contributions to translational bioengineering. He has not been noted as advising any students in the available data. Clark Meyer is actively involved in teaching and research at UTD, with no indication of part-time status, retirement, or former staff designation. His work contributes significantly to instructional and applied bioengineering programs.

Edward LymanView profile

Associate Professor

• Molecular Biophysics
• Membrane Biochemistry
• Computational Modeling
• +3 more

Edward Lyman is an Associate Professor at the University of Delaware, affiliated with the College of Arts & Sciences and the Department of Chemistry and Biochemistry. His research bridges molecular-level phenomena with cellular physiology, focusing on multiscale modeling of biological systems. Education: B.S., Pennsylvania State University (1998) Ph.D., Virginia Polytechnic and State Institution (2004) Postdoctoral Associate, University of Pittsburgh Medical School (2004-2007) Postdoctoral Fellow, University of Utah (2007-2010) Research centers on Developing multiscale modeling frameworks to connect molecular and cellular scales in biomedical systems Computational lipid-protein interactions in cell membranes Virtual drug discovery targeting G-protein coupled receptors Machine learning applications in membrane protein simulations Scientific Awards Thomas E Thompson Award, Biophysical Society MSF subgroup Students & Collaborations : Mentored researchers including JD Russo, Sasiri Vargas Urbano, Alison Leonard, and Swapnil Baral. Collaborated with institutions like UCSD, MBARI, and UMD.

• Applied mathematics
• Mathematical biology
• Biomechanics
• +10 more

Chiara Giverso is an Associate Professor in the Department of Mathematical Sciences "G. L. Lagrange" (DISMA) at Politecnico di Torino, Italy, where she also serves as the Academic Advisor for the Mathematical Engineering Master’s program. Her research is centered on applied mathematics with a focus on mathematical modeling in biomedical contexts, particularly in biomechanics, tumor growth, and cell migration. University: Politecnico di Torino Department: Department of Mathematical Sciences "G. L. Lagrange" (DISMA) Academic Rank: Associate Professor Email: chiara.giverso@polito.it Her research interests include applied mathematics, mathematical biology, biomechanics, mechanobiology, cell migration, and tumor growth modeling. She applies advanced mathematical frameworks—such as poroelasticity, nonlinear mechanics, and continuum mechanics—to understand complex biological phenomena like solid tumor progression and cellular responses to mechanical cues. The recent publications (2022–2024) reflect a strong trend in modeling brain tumor growth using imaging-informed mechanical frameworks, cell orientation under mechanical stretch, and multiscale modeling of tissue perfusion and angiogenesis. These works integrate mechanics, nutrient transport, and phenotypic evolution, often employing finite element methods and non-local PDEs to simulate biological behavior. Chiara Giverso is actively involved in competitive research projects, including the ANATOMY project (2023–2026), a nationally funded PRIN initiative aimed at developing a unified mathematical framework for modeling muscular dystrophies. She supervises PhD students such as Gabriele Fioretto and Francesca Ballatore, whose thesis work focuses on brain tumor modeling and cell migration. She teaches a range of courses across engineering disciplines, including: Mathematical Models for Biomedicine (Master’s level, Mathematical Engineering) Computational Modeling for Biomedicine Laboratory (Biomedical Engineering) Linear Algebra and Geometry (Aerospace, Management, and Computer Science Engineering) Probability and Mathematical Statistics (Architecture) She is a member of the research group "Models and Methods of Mathematical Physics" at DISMA and contributes to interdisciplinary research aligned with SDG Goal 3: Good Health and Well-being.

• Condensed Matter Physics
• Theoretical Physics
• Computational Physics
• +7 more

Prof. Dr. Igor Schapiro is a faculty member at the Faculty of Physics, Technical University of Dortmund, where he leads a research group focused on the theoretical and computational description of light-induced processes in condensed matter. His work lies at the intersection of physics, chemistry, and computational science, with applications to natural systems such as solvated molecules and chromophore-protein complexes. His research interests include: Theoretical modeling of excited-state reactions Multiscale simulation methods for large systems (thousands of atoms) Development of multireference electronic structure methods Accurate description of conical intersections and electronic state degeneracies The group emphasizes both the application of advanced computational tools and the development of new methodologies to better understand critical points in photochemical processes. While no specific publications or awards are listed in the provided text, his work contributes to fundamental advances in computational condensed matter physics and photochemistry. Prof. Schapiro is supported by a secretariat, and his contact information is publicly available for academic collaboration and inquiry. Contact details: Email: igor.schapiro@tu-dortmund.de Phone: +49 (0)231 755-3537 Room: P2-02-422 Address: Department of Physics, Otto-Hahn-Str. 4, 44227 Dortmund, Germany Website: Schapiro Group

• Mathematical Logic
• Model Theory
• Definable Types
• +6 more

Pablo Jose Andujar Guerrero is an Assistant Professor in the Department of Mathematical Analysis at the Faculty of Mathematics, University of Valencia. His research lies at the intersection of mathematical logic, model theory, and topology, with a focus on definable structures in o-minimal and p-adically closed fields. His primary research interests include definable types , definable topological spaces , o-minimal structures , p-adically closed fields , and definable groups . His work explores foundational aspects of model theory, particularly in the context of ordered and valued fields, and their topological implications. He has contributed to understanding definable compactness, interpretable sets, and the structure of definable groups with definable f-generics. His recent publications (2021–2025) reflect a strong trend in model-theoretic algebra and definable topology, with articles in journals such as Annals of Pure and Applied Logic , Journal of the London Mathematical Society , and Model Theory . These works demonstrate a consistent focus on definability, compactness, and classification in both o-minimal and p-adic settings. Pablo Andujar Guerrero has collaborated with notable researchers including Margaret E. M. Thomas, Erik Walsberg, and Will Johnson. He has no listed scientific awards in the available data. His advising activity and grant history are not mentioned in the provided texts. He is affiliated with the research group in Mathematical Analysis at the University of Valencia and contributes to the broader model theory community through publications and collaborations. His work continues to advance the understanding of definability and structure in mathematical logic.

• Applied Physical Chemistry
• Colloids
• Computational Fluid Dynamics (CFD)
• +12 more

Marco Vanni is a Full Professor in the Department of Applied Science and Technology (DISAT) at the Polytechnic University of Turin, where he has been a faculty member since 1991, progressing from University Researcher to Associate Professor (2001) and Full Professor (2012). He is affiliated with the College of Chemical and Materials Engineering and teaches courses in Applied Physical Chemistry, Thermodynamics for Chemical Engineering, and Hydrogen Production Processes. He has served in leadership roles including Coordinator of the PhD Program in Chemical Engineering (2014–2018) and as Contact Person for Chemical and Sustainable Process Engineering degree programs. His research focuses on the behavior of dispersed multiphase systems, integrating computational fluid dynamics (CFD) with models of microscale phenomena such as mass transfer, surface interactions, and population balances. Key areas include nanoparticle precipitation, gas-liquid reactors, and elastomer processing, with applications in energy, pharmaceuticals, and sustainable engineering. The recent publications reveal a strong trend in multiscale modeling of multiphase systems, particularly using advanced moment methods (QMOM, CQMOM, DQMOM) coupled with CFD. His work spans from fundamental colloid dynamics to applied industrial problems, including collaborations with Eni, Pirelli, and Rockwood. The latest articles also show an expanding interest in thermal and mass transfer in wearable systems, indicating interdisciplinary outreach into textile and biomedical engineering. He has supervised multiple PhD students, including Eleonora Bianca, Antonello Raponi, Marco Ferrari, and Lorenzo Vasquez Giuliano, on topics ranging from magnesium hydroxide precipitation to food emulsions and drug delivery systems. Marco Vanni leads and participates in numerous research projects, including EU-funded initiatives like MULTIPHASE Erasmus Mundus and BATCAT, as well as commercial projects with Eni, Pirelli, and others, focusing on reactor simulation, nanoparticle production, and process optimization. He is also involved in applied research on bioreactors, tire production, and filtration technologies. He is a member of research groups such as the Multiscale Modeling for Materials Science and Process Engineering team and works within laboratories including the Center for Multiphysics Modeling of Materials and Processes and the Laboratory for Multiscale and Process Modeling at DISAT.

• Computational Chemistry
• Theoretical Physics
• Heterogeneous Catalysis
• +3 more

Katharina Doblhoff-Dier is an Assistant Professor at the Leiden Institute of Chemistry (LIC) , part of the Faculty of Science at Leiden University , Netherlands. Her research focuses on computational and theoretical studies of atomic-scale processes at metal interfaces, including heterogeneous catalysis and electrochemical processes. She employs methods ranging from electronic structure calculations to molecular dynamics and mean-field modeling to address complex interfacial phenomena. Education: PhD in Theoretical Physics, Technische Universität Wien, Vienna, Austria (2014) MSc in Geophysics, University of Vienna (2011) MSc in Technical Physics, Technische Universität Wien (2010) Teaching: Courses include Computational Chemistry and Molecular Simulations , Density Functional Theory in Practice , and Quantum Chemistry and Physics for undergraduate and graduate students. Research Interests: Katharina combines multi-scale modeling approaches to study electrochemical interfaces and catalytic reactions. Her work emphasizes understanding microscopic mechanisms through computational methods, including quantum chemistry and classical simulations. Grants and Recognition: Recipient of NWO-EW Supercomputing grants (2021 and 2023) Professional Activities: Organizer of the 2024 Lorentz workshop on Multiscale Modeling of Electrochemical Processes Member of the NWO-ENW review committee Reviewer for Nature Communications , Physical Review Letters , and others Her work bridges theoretical insights with experimental electrochemistry, contributing to advancements in energy and sustainability research.