Find Academic Supervisors

Rob KusnerView profile

Professor

• Geometric analysis
• Variational problems
• Low dimensional geometry & topology
• +5 more

Robert B. Kusner is a Professor of Mathematics at the University of Massachusetts Amherst, directing the Center for Geometry, Analysis, Numerics and Graphics (GANG). His research focuses on geometric analysis, variational problems, low-dimensional topology, and mathematical visualization. He holds editorial roles at journals like Journal of Experimental Mathematics and has served on the Board of Trustees for the Association of Members of the Institute for Advanced Study. Kusner earned his Ph.D. from UC Berkeley (1988) and has held visiting positions at institutions including Stanford, Penn, and the Isaac Newton Institute. His work spans minimal surfaces, constant mean curvature surfaces, knot theory, and applications in biomathematics. He has advised students on topics ranging from geometric configurations to biomembrane modeling. Kusner’s contributions include over 150 publications and collaborations in experimental mathematics, geometric flows, and interdisciplinary research. Education: Ph.D. Mathematics, University of California, Berkeley, 1988 C.Phil. Mathematics, University of California, Berkeley, 1984 B.A. Mathematics and Physics, Haverford College, 1981 Research Interests: Geometric analysis, variational problems, minimal surfaces, Willmore energy, knot energies, biomembrane modeling, and topological configurations. Grants & Collaborations: Extensive funding for research in geometric analysis and interdisciplinary projects. Collaborations include work on the Willmore conjecture, biomembrane numerical methods, and topological colloids. Labs/Teams: Director of GANG, leading a team in experimental geometry and computational mathematics. Active in organizing workshops on geometric topology and condensed matter physics.

Vicky WardView profile

Professor

• Knowledge Mobilisation
• Policy Analysis
• Health Services Research
• +3 more

Dr. Vicky Ward is a Professor of Management at the University of St Andrews Business School, where she also serves as Director of Impact and Innovation. Her research focuses on knowledge mobilisation, examining how academic and professional knowledge is applied in policy, practice, and interprofessional collaboration. She specializes in knowledge brokering, embedded research initiatives, and parliamentary research services. She leads the RURU Network (Researching and Understanding Research Use) and chairs the UK Knowledge Mobilisation Forum. Her work spans frameworks for knowledge translation, the role of researchers in organizations, and the mobilisation of knowledge in healthcare contexts, including naturopathic practices. Ward has contributed to international studies on legislative research mechanisms and the design of collaborative research projects. Her research emphasizes practical application through frameworks like the SUFFICE framework for gathering service user experiences and principles for research coproduction. She has explored gender equality interventions in academic medicine and evaluated large-scale health research programs like the ASPIRE initiative.

Paul PaukstelisView profile

Associate Professor

• Nucleic Acid Structure
• DNA Nanotechnology
• Structural Biology
• +3 more

Paul Paukstelis is an Associate Professor in the Department of Chemistry and Biochemistry at the University of Maryland, College Park, and serves as Director of the Biochemistry Graduate Program. His research focuses on nucleic acid structure, DNA nanotechnology, and the development of novel DNA-based materials. Education: BS Biology (University of Kansas, 1997); PhD Molecular Biology (University of Texas at Austin, 2005) Postdoctoral Research: University of Texas at Austin (2005–2009) His research interests include extending DNA's structural boundaries beyond Watson-Crick pairing through x-ray crystallography and biophysical methods. Key projects involve designing pH-responsive DNA crystals, discovering new DNA motifs (e.g., C-tetrad G-quadruplexes, parallel-stranded tetraplexes), and engineering DNA crystals with embedded enzymes for biocatalytic applications. These advancements bridge biology, materials science, and engineering. His work has led to breakthroughs such as solvent-channel DNA crystals capable of size-selective macromolecule encapsulation and the first functional solid-state biocatalysts using DNA matrices. Lab activities emphasize rational design of DNA architectures for nanotechnology, with a focus on structural predictability and functional applications.

Anastasia MolchanovaView profile

Research Fellow

• Analysis
• Functional Analysis
• Quasiconformal Analysis
• +6 more

Anastasia Molchanova is a Research Fellow at the Institute of Analysis and Scientific Computing, TU Wien, holding an Elise Richter fellowship (2023–2027). Her research focuses on nonlinear elasticity, calculus of variations, and PDEs, with applications in materials science and geometric analysis. She completed her PhD on quasiconformal analysis and has held positions at TU Wien, University of Vienna, and Novosibirsk State University. Key affiliations include the Austrian Association of Women in Mathematics (A²WiM). She has organized conferences such as the ESI Workshop on Variational and Geometrical Methods in Materials Science (2023) and co-organized the Second Austrian Day of Women in Mathematics (2022). Her teaching includes advanced courses on fractional Sobolev spaces and calculus of variations at TU Wien and University of Vienna. Research interests span functional analysis, geometric measure theory, and the analytical foundations of nonlinear elasticity. Her grants include an FWF Elise Richter grant (€404K), a REWIRE Marie Skłodowska-Curie Actions COFUND grant (€266K), and a FWF Lise Meitner grant (€159K). She has authored over 15 publications, focusing on Sobolev homeomorphisms, Lavrentiev phenomena, and variational formulations in materials science.

• Artificial Intelligence
• Explainable AI
• Case-Based Reasoning
• +4 more

Professor Nirmalie Wiratunga is a leading academic at Robert Gordon University, focusing on artificial intelligence and its applications across diverse domains. Her work bridges theoretical advancements with practical implementations in areas requiring high explainability and domain-specific adaptation. Research Pillars : Explainable AI (XAI), Case-Based Reasoning (CBR), Legal AI, Healthcare Informatics, and Machine Learning. Methodological Focus : Retrieval-Augmented Generation (RAG), domain adaptation, dialogue understanding, and systematic review automation. Recent publications highlight her contributions to neonatal pain assessment transparency, legal question answering systems (SCaLe-QA and CBR-RAG), and multi-shot explanation platforms (iSee). Her work on hallucination detection and federated learning emphasizes robustness and privacy preservation. Collaborations span biomedical, legal, and energy sectors, including mini-grid optimization for rural communities. Her research integrates context-aware systems into data-to-text generation and dual-task dialogue understanding, pushing boundaries in human-AI collaboration. Projects like Agentic CBR demonstrate practical implementations for financial decision-making with counterfactual explanations.

• Partial Differential Equations
• Nonlocal Problems
• Regularity Theory
• +3 more

Dr. Ho-Sik Lee is a researcher affiliated with the Faculty of Mathematics at Bielefeld University, specializing in partial differential equations, nonlocal problems, and regularity theory. He contributes to projects within the International Research Training Group 2235 and the Bielefeld Graduate School in Theoretical Sciences. Faculty of Mathematics, Bielefeld University Bielefeld Graduate School in Theoretical Sciences International Research Training Group 2235 His research focuses on advanced mathematical analysis of nonlinear and nonlocal equations, including degenerate weights, mixed local/nonlocal operators, and regularity estimates for problems arising in calculus of variations and applied contexts. Recent work explores the Zaremba problem, fractional p-Laplacian, kinetic Fokker-Planck equations, and double phase functionals. Analysis of his 15 most recent publications (2023–2025) reveals expertise in parabolic equations, nonlocal diffusion, Hölder continuity, gradient estimates, and weighted Sobolev spaces. These works intersect with mathematical physics, functional analysis, and applications in nonlinear dynamics.

• Photogrammetry
• 3D Modeling
• Cultural Heritage Documentation
• +3 more

Emmanuel Alby is a Lecturer in the Civil Engineering and Topography Department at the University of Strasbourg, affiliated with INSA Strasbourg. He is a Researcher in the ICUBE Research Unit's TRIO Team and a member of the PAGE team. His work focuses on integrating geomatics technologies such as photogrammetry, laser scanning, and 3D modeling for archaeological and cultural heritage documentation. Research Interests: Alby's research emphasizes digital documentation of archaeological sites, 3D modeling of heritage structures, and the development of low-cost solutions for artifact and site recording. His work bridges traditional archaeological methods with cutting-edge technologies like UAV imagery, point cloud processing, and semantic segmentation for heritage preservation. Key Contributions: Alby has pioneered methodologies for combining photogrammetry and laser scanning data to create comprehensive 3D models of sites such as the Bronze Age cave "Les Fraux" and the Monastery of Saint Hilarion in Gaza. He has also developed open-source tools for real-time 3D visualization and semantic analysis of archaeological data. Articles Trends: His publications highlight advancements in 3D reconstruction techniques, artifact identification algorithms, and the application of machine learning to architectural heritage. Recent work includes real-time smartphone-based depth mapping and long-term monitoring of excavation sites in Jordan and France. Labs/Teams: Active in ICUBE's TRIO and PAGE teams, Alby collaborates on projects involving heritage preservation, archaeological surveying, and interdisciplinary geomatics applications.

Liwei WangView profile

Assistant Professor

• Machine Learning
• Computational Engineering
• Data-Driven Design
• +19 more

Liwei Wang is an Assistant Professor in the Department of Mechanical Engineering at Carnegie Mellon University's College of Engineering, where he leads the Computational and Physical Intelligence Laboratory (CPhI Lab). His research integrates computational modeling, machine learning, and mechanics to design advanced materials and smart systems. Education: Ph.D., Mechanical Engineering, Shanghai Jiao Tong University (2022, Honors) B.S., Mechanical Engineering, Shanghai Jiao Tong University (2017, Honors) Liwei Wang's research interests lie at the intersection of machine learning, computational engineering, and advanced materials . He develops data-driven and physics-informed frameworks for topology optimization, metamaterials, 3D/4D printing, soft robotics, and programmable materials systems . His work emphasizes physical intelligence —designing materials that can sense, adapt, and respond to their environments. Applications span mechanical protective cloaks, flexible electronics, minimally invasive surgery, and mechanical computing . His recent publications reveal a strong trend toward multi-scale, data-efficient design of metamaterials using advanced machine learning techniques such as Gaussian processes, latent variable models, and neural networks. He focuses on scalable, differentiable, and task-aware optimization methods that enable rapid discovery and deployment of functional material systems. Scientific Awards: ASME Design Automation Dissertation Award ASME Design Automation Conference Best Paper Award Institution-level Outstanding Ph.D. Dissertation Award Dr. Wang advises a growing research group at CMU and leads the CPhI Lab, where his team develops next-generation computational tools for materials innovation. While specific grants are not listed, his research is likely supported by federal and private funding given the scope and impact of his work. His lab emphasizes interdisciplinary collaboration and translation of computational designs into physical prototypes via additive manufacturing. Laboratory & Team: The Computational and Physical Intelligence Laboratory (CPhI Lab) focuses on co-designing materials and structures with embedded intelligence, combining simulation, data science, and experimental validation to push the boundaries of what engineered materials can achieve.

Kaushik DayalView profile

Professor

• Theoretical and Computational Multiscale Methods
• Materials Science
• Mechanics of Materials
• +19 more

Kaushik Dayal is a Professor in the Department of Civil and Environmental Engineering at Carnegie Mellon University's College of Engineering. He leads the Multiscale Mechanics Research Group and is affiliated with several interdisciplinary centers including the Center for Nonlinear Analysis, the Center for the Mechanics and Engineering of Cellular Systems, the NextManufacturing Center, and the Wilton E. Scott Institute for Energy Innovation. His research bridges theoretical and computational mechanics with applications in materials science, energy, and environmental systems. Ph.D., Mechanical Engineering, California Institute of Technology (2007) M.S., Aeronautics, California Institute of Technology (2001) B.Tech., Naval Architecture, Indian Institute of Technology Madras (2000) His research focuses on theoretical and computational multiscale methods , particularly in modeling the behavior of materials across atomic to continuum scales. Key areas include non-equilibrium response , electromagnetic effects , phase-field modeling of fracture , poroelasticity , soft active materials , and data-driven inverse design . He investigates phenomena such as microstructure evolution, dislocation dynamics, surface growth, and material behavior under extreme conditions. His work integrates mechanics with chemistry, robotics, and climate resilience, often leveraging machine learning and Bayesian inference. His recent publications reveal a strong trend in computational mechanics of heterogeneous and functional materials , with emphasis on phase-field models, multiscale homogenization, and instability exploitation in soft electromechanical systems. Many studies involve collaboration with national labs and cross-departmental teams, reflecting a highly interdisciplinary approach. McGaw Graduate Fellowship in Mechanical Engineering Army Research Laboratory Journeyman Fellowship Adamson Fellowship Bushnell Doctoral Fellowship Mao Yisheng Outstanding Dissertation Award MIT Postdoctoral Fellowship for Engineering Excellence Center for Machine Learning and Health Fellowship Dowd Doctoral Fellowship Steinbrenner Doctoral Fellowship Dunlap Awardee Dayal has advised numerous PhD students, many of whom have gone on to postdoctoral positions at institutions such as Caltech, MIT, Johns Hopkins, and Los Alamos National Laboratory. His research is supported by major grants from the Department of Defense (MURI program), Air Force Research Laboratory, and other federal agencies. He actively promotes education through teaching assistant awards and participation in Rising Stars workshops. He leads the Multiscale Mechanics Research Group , a vibrant team engaged in cutting-edge research on material modeling, soft robotics, energy materials, and environmental mechanics. The group emphasizes open scientific exchange, interdisciplinary collaboration, and innovation in computational methods.

Charbel FarhatView profile

Professor

• Computational Fluid Dynamics
• Fluid-Structure Interaction
• Structural Mechanics
• +7 more

Charbel Farhat is the Vivian Church Hoff Professor of Aircraft Structures and Professor of Aeronautics and Astronautics at Stanford University's School of Engineering. He chairs the Department of Aeronautics and Astronautics and has led significant initiatives such as the Stanford-King Abdulaziz City for Science and Technology Center. His research focuses on computational methods for multiphysics problems in aerospace engineering, including fluid-structure interaction, digital twinning, and uncertainty quantification. Farhat has authored over 650 publications and holds prestigious awards like the Vannevar Bush Faculty Fellowship and multiple honorary doctorates. Education: Ph.D. in Civil Engineering, University of California, Berkeley (1987) MS in Electrical Engineering and Computer Sciences, UC Berkeley (1986) MS in Structural Engineering, UC Berkeley (1984) MS in Applied Mechanics, Université de Paris VI (1983) Engineering Diploma, Ecole Centrale des Arts et Manufactures (1983) Research Interests: Farhat's work emphasizes advanced computational algorithms for aerospace systems, including autonomous carrier landing dynamics, hypersonic trajectory analysis, and physics-based machine learning. His group develops high-performance software for digital twinning and model reduction techniques to address complex engineering challenges. Recent efforts include supersonic parachute dynamics modeling and probabilistic learning frameworks for uncertainty quantification. Awards & Recognition: Member of National Academy of Engineering (U.S.), Royal Academy of Engineering (UK), and Lebanese Academy of Sciences Fellowships from AIAA, ASME, SIAM, and multiple computational mechanics societies Recipient of the Gordon Bell Prize, John von Neumann Medal, and Gauss-Newton Medal Advising & Grants: Farhat supervises doctoral and master's students in advanced computational methods. His research is funded by NSF, AFOSR, ONR, NASA, and industry partners like Boeing and Lockheed-Martin. He advises on national boards and editorial roles for journals like the International Journal for Numerical Methods in Engineering. Labs & Teams: Leads the Farhat Research Group (FRG) at Stanford, focusing on Simulation-Based Engineering Science. Collaborates internationally on projects like the Army High Performance Computing Research Center and the Stanford-King Abdulaziz Center.

Seungly OhView profile

Associate Professor

• Partial Differential Equations
• Nonlinear dispersive partial differential equations
• Surface water waves
• +7 more

Seungly Oh is an Associate Professor of Mathematics in the Department of Mathematical Sciences at Western New England University. Their research focuses on nonlinear dispersive partial differential equations and harmonic analysis with applications in surface water waves, optics, and quantum physics. Education: Ph.D. in Mathematics, University of Kansas Research Interests: Nonlinear dispersive equations (Benjamin-Ono, Korteweg-de Vries, Boussinesq) Harmonic analysis and multilinear operators Functional spaces (Sobolev spaces, L^p embeddings) Applications in mathematical physics Recent Article Trends: Recent work addresses nonlinear smoothing properties, well-posedness in low regularity settings, and endpoint estimates for inequalities in harmonic analysis.

Simon CrampinView profile

Senior Lecturer

• Condensed Matter Physics
• Computational Physics
• Surface Science
• +4 more

Dr. Simon Crampin is a Senior Lecturer at the University of Bath , affiliated with the Department of Physics and the Centre for Nanoscience and Nanotechnology. His work spans theoretical and computational condensed matter physics, with a focus on electronic structure at surfaces and interfaces. Education: PhD (1989) and BSc (1986) from Imperial College, London Research: Develops Green's function methods and variational embedding schemes for surface/interfacial physics, collaborates with experimentalists Projects: Modeling scanning tunneling spectroscopy, relativistic embedding theories, domain wall current flow, and electron-beam deposition Research Trends: His recent articles highlight expertise in 2D materials , quantum wells , charge density waves , and computational modeling of nanoscale phenomena. Common subfields include band structure , electron dynamics , and surface science . Scientific Awards: Royal Society Leverhulme William and Mary Fellow Collaborations: Key projects include grants from the Royal Society and EPSRC, focusing on organic molecular semiconductors , spintronic devices , and domain wall motion . Supervised 15 doctoral students over his career.

• Spoken Standard German
• Linguistics and Language Didactics
• Intercultural Communication
• +4 more

Magdalena Thien is a Professor of German at the Department of Lexicology and Pragmatic Linguistics, Faculty of Humanities, University of Białystok, Poland. She is also a visiting researcher at the Leibniz Institute for the German Language in Mannheim (2023) under a DAAD scholarship, highlighting her active engagement in international academic collaboration. Her research centers on the intersection of linguistics and language didactics, particularly focusing on spoken Standard German and its pedagogical application in German as a foreign language (DaF) contexts. She critically examines the disciplinary boundaries and methodological tensions between theoretical linguistics and language teaching, advocating for a more balanced and respectful interdisciplinary relationship. The recent publications reveal a strong thematic consistency: analyzing how linguistic research can be effectively integrated into language teaching, understanding learner perceptions of native speaker usage, and reconstructing the academic identity of language didactics. Her work often employs empirical and discourse-analytic methods, especially in digital environments like internet forums. Scientific contributions include several peer-reviewed journal articles and edited volumes that explore the dynamics between linguistic theory and classroom practice. Notable works appear in Glottodidactica , Studia Germanica Gedaniensia , and German as a Foreign Language . Visiting Researcher, Leibniz Institute for the German Language, Mannheim (2023) Editor and author in key publications on language teaching and interdisciplinary dialogue Active contributor to debates on linguistic norms and didactic methodology She has not publicly listed advisees or grants, but her editorial roles and research projects indicate leadership in her field. No laboratory or team is mentioned, but her work is deeply embedded in academic networks across Germany and Poland.

Ali NadimView profile

Professor

• Fluid Dynamics
• Mathematical Modeling
• Scientific Computing
• +4 more

Ali Nadim is a Full Professor at Claremont Graduate University's Institute of Mathematical Sciences, Department of Physical Applied Mathematics. He holds a PhD in Chemical Engineering from MIT (1986) and has held prior appointments as Assistant Professor at MIT (1986–1991), Associate Professor at Boston University (1991–2001), and dual roles at Keck Graduate Institute (bioengineering) and CGU (applied mathematics) since 2001. Education: BS Chemical Engineering (UC Davis), PhD (MIT). Affiliations: Claremont Graduate University (2001–present), Keck Graduate Institute (2001–2010), Boston University (1991–2001). His research focuses on fluid dynamics, mathematical modeling, and scientific computing, with applications in biomedical engineering (e.g., alveolar surfactant dynamics, lab-on-chip devices) and multiphase flow systems. Notable contributions include: Thin film dynamics on rotating spheres and fibers. Electrowetting-driven microfluidic mixing. Modeling p53 signaling pathways in response to DNA damage. Mathematical analysis of bubbly liquids and viscoelastic drops. He has pioneered methods for simulating blood flow in arterial systems and contributed to patents on rapid lysis devices for nucleic acid diagnostics. His work bridges applied mathematics, engineering, and biomedicine, with over 150 peer-reviewed publications and extensive grant-funded research.

Ivan Fernandez-CorbatonView profile

Researcher

• Electromagnetic radiation
• Light-matter interactions
• Symmetries and conservation laws
• +5 more

Ivan Fernandez-Corbaton is a Project Leader and Staff Scientist at the Institute of Nanotechnology, Karlsruhe Institute of Technology (KIT), where he leads research in the Theoretical Nanooptics unit. His position focuses on fundamental electromagnetic theory with applications in nanophotonics and metamaterials. His research centers on the systematic use of electromagnetic duality symmetry and its conserved quantity, electromagnetic helicity, to treat electromagnetic polarization degrees of freedom. This approach provides insights and design guidelines across diverse areas including zero backscattering, optical activity, metamaterials for transformation optics, and nanophotonic phenomena involving electromagnetic angular momentum. His work bridges theoretical physics with practical applications in chiral sensing, thermal radiation control, and light structuring technologies. Analysis of his recent publications reveals a strong focus on computational methods for electromagnetic problems, particularly the T-matrix formalism extended to polychromatic fields and complex geometries. His research increasingly integrates multi-scale approaches connecting quantum chemical simulations with classical electromagnetic modeling, especially for molecular nanomaterials and chiral structures. The work shows consistent theoretical depth with practical applications in sensing, light manipulation, and thermal radiation control. As a Staff Scientist, Fernandez-Corbaton collaborates extensively within KIT's Carsten Rockstuhl's Lab and with international partners. His research has significant implications for chiral molecule detection, photonic device design, and fundamental electromagnetic theory. He maintains active publication output with numerous preprints available on arXiv and ResearchGate, reflecting his commitment to open scientific communication.