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Julian ScheuerView profile

Professor

• Geometric Analysis
• Partial Differential Equations
• Geometric Flows
• +3 more

Prof. Julian Scheuer is a Professor of Geometric Analysis at Goethe-Universität Frankfurt. He holds a PhD from the University of Heidelberg (2013) and completed his Habilitation at the University of Freiburg (2018). His research focuses on geometric evolution equations, such as mean curvature flow and inverse curvature flows, with applications to convex geometry and general relativity. He has held academic positions at Cardiff University, Columbia University, and the Universities of Freiburg and Ulm. Scheuer has organized conferences like the 41st Süddeutsches Kolloquium über Differentialgeometrie and the FRActional Curvature in FRAnkfurt workshop. Educations: PhD in Mathematics (Heidelberg, 2013), Habilitation (Freiburg, 2018) Grants: EPSRC Small Grant (2021), DFG Project on Quermassintegral Flows (2020), DFG Harnack Inequalities Project (2018) His research interests span geometric flows, curvature estimates, and geometric inequalities. Notable contributions include work on the Minkowski inequality in de Sitter space and stability results for geometric problems. He has authored over 40 peer-reviewed articles and delivered talks at institutions worldwide. Scheuer teaches advanced courses in analysis, differential geometry, and geometric inequalities at Goethe-Universität. Key Awards: Fellow of the Higher Education Academy (UK, 2022). His research is supported by grants exploring nonlocal curvature functionals and inverse curvature flows.

Ntalampekos DimitriosView profile

Assistant Professor

• Complex Analysis
• Analysis on Metric Spaces
• Complex Dynamics
• +2 more

Ntalampekos Dimitrios is an Assistant Professor at the Department of Mathematics, Aristotle University of Thessaloniki. Previously, he held positions at Stony Brook University (Assistant Professor, 2021-2024; Postdoctoral Researcher, 2018-2021). His office is located in Room 3.10, East Wing, 3rd Floor, Glass Building of the Faculty of Sciences. Ph.D. in Mathematics, University of California, Los Angeles (2018) M.A. in Mathematics, University of California, Los Angeles (2015) B.Sc. in Mathematics, Aristotle University of Thessaloniki (2013) His research focuses on Complex Analysis , Analysis on Metric Spaces , and Complex Dynamics , with emphasis on uniformization and rigidity problems in non-smooth settings, quasiconformal geometry of fractals, and applications to dynamical systems. Publications include foundational work on Sierpiński carpets, conformal uniformization of planar packings, and polyhedral approximations of metric surfaces. Recent publications explore quasiconformal characterizations of Schottky sets , smooth approximations of quasispheres , and uniformization of Gromov hyperbolic domains . His work bridges classical geometric analysis with modern non-smooth generalizations, often involving collaborations with mathematicians like Matthew Romney and Yusheng Luo.

• Transportation Engineering
• Operations Research
• Data Science
• +6 more

Nikola Markovic is an Associate Professor in the Civil & Environmental Engineering Department at the University of Utah, specializing in applications of operations research and data science to transportation problems. His research spans paratransit optimization, work zone safety, airport operations, and disaster response logistics. Dr. Markovic earned his educational qualifications in Transportation Engineering, including a BS from the University of Belgrade, and both MS and PhD degrees from the University of Maryland. His research focuses on applying advanced computational methods to solve practical transportation challenges. Key areas include optimizing paratransit services for individuals with disabilities, improving snowplow routing in Utah, enhancing work zone safety through computer vision, and developing systems for airport operations monitoring at non-towered airports. His work often involves collaboration with transportation agencies and industry partners to ensure practical applicability. Analysis of his recent publications reveals a strong trend toward integrating machine learning techniques with traditional transportation engineering problems. His work frequently employs advanced methods like generative adversarial networks, deep learning, and optimization algorithms to address complex transportation challenges across multiple domains including paratransit, work zones, airports, and disaster response. Nominated for the Early Career Teaching award (2023 and 2021) Ranked among top 15% instructors in the College of Engineering (2022) Winner of Transportation Science and Logistics Best Paper Award from INFORMS (2022) Winner of National ACRP student design competition (2021) Dr. Markovic has advised numerous graduate students through thesis research courses in transportation engineering. His grant portfolio includes significant funding from the Utah Department of Transportation, Utah Transit Authority, and National Science Foundation, supporting research in accessibility, work zone safety, and paratransit service improvement. Current projects include enhancing accessibility for individuals with limited mobility using AI and cycling data, measuring roadside feature impacts on crashes, and developing technology integration for disadvantaged communities. His laboratory work focuses on transportation data analytics, with emphasis on computer vision applications for infrastructure monitoring and optimization algorithms for transportation operations. Current team projects involve developing systems for non-towered airport monitoring, improving paratransit services through technology integration, and optimizing emergency response after seismic events.

• Mathematical Physics
• General Relativity
• Black Hole Solutions
• +4 more

Hari Kunduri is an Associate Professor in the Department of Mathematics and Statistics at McMaster University. His research focuses on mathematical physics, particularly general relativity and Riemannian geometry in asymptotically flat/hyperbolic manifolds, with emphasis on higher-dimensional black hole solutions to Einstein's equations. He holds a PhD from the University of Cambridge (2007) and a BSc from the University of Toronto (2001). His research areas include algebraic/differential geometry and mathematical physics, with contributions to topics like Penrose inequalities, near-horizon geometries, and supersymmetric solutions in AdS spacetimes. His work bridges theoretical physics (string theory, gauge/gravity correspondence) and pure mathematics. Selected recent publications (2021-2025) explore topics such as black hole thermodynamics, gravitational solitons, and geometric rigidity theorems. He teaches courses like Relativity, Analytical Mechanics, and Mathematical Physics at both undergraduate and graduate levels. Kunduri has collaborated widely, with over 137 publications since 2003, and his work is cited in Wikipedia and Mendeley. He actively participates in conferences like the Marcel Grossmann Meetings and maintains an extensive co-author network in gravitational physics communities.

Hai WangView profile

Professor

• High-Speed Propulsion
• Combustion Chemistry
• Renewable Energy Conversion
• +5 more

Hai Wang is a Professor of Mechanical Engineering at Stanford University with a distinguished career in combustion science, high-speed propulsion, and renewable energy conversion. His research spans combustion chemistry of conventional and renewable fuels, detonation dynamics, quantum-chemistry guided battery materials design, and transport theories in nanoparticle systems. Education : Ph.D. in Fuel Science from Pennsylvania State University (1992), M.S. in Chemical Engineering from Michigan Technological University (1986), B.Eng. in Polymer Materials from East China University of Science and Technology (1984). He has authored seminal works on soot formation in flames, catalytic oxidation of methane, and laminar flame speed modeling. His recent publications address interdisciplinary challenges such as eco-anxiety and advanced data plane verification. Notable administrative roles include co-founding Hestia Tec, LLC (2010-2014) and serving as President of the Combustion Institute (2024-present). Wang’s work has been recognized with the Humboldt Senior Research Award (2019), Mercator Fellow (2019), and multiple fellowships. He mentors doctoral and master’s students and leads research initiatives like the Combustion Energy Frontier Research Center (2010-2014).

Gabriel PaternainView profile

Professor

• Differential Geometry
• Analysis
• Dynamical Systems
• +2 more

Gabriel Paternain is a Professor of Mathematics at the Faculty of Mathematics , University of Cambridge. His research focuses on Differential Geometry , Analysis , and Dynamical Systems , with particular emphasis on Geometric Inverse Problems and Geodesic Ray Transforms . Research Areas: Differential Geometry Dynamical Systems Geometric Inverse Problems Integral Geometry Partial Differential Equations Mathematical Physics Recent Work: Non-Abelian X-ray transforms Anosov surface rigidity Twistor space analysis Yang-Mills inverse problems Stochastic Bayesian inversion

Xiangwen ZhangView profile

Professor

• Geometric Analysis
• Partial Differential Equations
• Differential Geometry
• +3 more

Xiangwen Zhang is a Professor in the Department of Mathematics at the University of California, Irvine. His research focuses on geometric analysis and partial differential equations, particularly exploring geometric flows, complex geometry, and mathematical physics. He has contributed to the study of Hessian equations, Strominger systems, and string theory-related geometric structures. Dr. Zhang’s work bridges differential geometry and nonlinear PDEs, with significant contributions to the understanding of curvature flows, conformally balanced metrics, and geometric inequalities. His research often involves advanced techniques from complex geometry and geometric analysis, addressing questions in both pure and applied mathematical contexts. His academic activities include teaching courses like Math 2D (Multivariable Calculus) and maintaining active participation in seminars such as the Analysis Seminar and Differential Geometry Seminar. He collaborates widely, evidenced by co-authorships with researchers like T. Fei, D.H. Phong, and S. Picard. His research has been published in leading journals such as the Journal of Differential Geometry and Inventiones Mathematicae. Zhang’s expertise also extends to geometric inequalities and spacetime geometry, as seen in his work on Minkowski formulae and Alexandrov theorems. His research program reflects a deep engagement with the interplay between geometry, analysis, and theoretical physics.

Hongkai ZhaoView profile

Professor

• Applied and Computational Mathematics
• Inverse Problems
• Imaging
• +4 more

Professor Hongkai Zhao is a Chancellor’s Professor and Chair of the Mathematics Department at the University of California, Irvine (UCI), with a joint appointment in Computer Science. He holds a B.S. from Peking University, M.S. from USC, and Ph.D. from UCLA, all in Mathematics. His research focuses on computational and applied mathematics, including moving interface problems, inverse problems, imaging, and Hamilton-Jacobi equations. He is renowned for developing the Fast Sweeping Method (FSM) for solving hyperbolic PDEs efficiently. Education: B.S. (Peking University, 1990), M.S. (USC, 1992), Ph.D. (UCLA, 1996). Employment: UCI faculty since 1999, Szego Assistant Professor at Stanford (1996–1999). Research interests span computational fluid dynamics (moving interfaces), inverse problems (tomography, wave propagation), and imaging (medical imaging, computer vision). Key contributions include numerical methods for surfactant-laden drops, fast algorithms for Hamilton-Jacobi equations, and 4D cone-beam CT reconstruction. Awards include the Feng Kang Prize (2007), Sloan Fellowship (2002–2004), and Chancellor’s Professorship (2016–present). He has authored over 100 publications on numerical methods, inverse problems, and PDEs. Lab affiliations: Active in interdisciplinary research at UCI, leading projects in computational mathematics and imaging science. Current work includes high-frequency wave propagation, multi-scale modeling, and geometric data analysis.

Pierre PayeurView profile

Professor

• Machine Vision
• 3D Sensing and Modeling
• Human Motion Capture
• +4 more

Pierre Payeur is a Professor in the School of Electrical Engineering and Computer Science at the University of Ottawa. He holds a PhD from Université Laval (1999) and has been a faculty member since then. He leads the SMART Research Group and co-founded the VIVA Research Laboratory. His roles include Graduate Programs Coordinator for the Ottawa-Carleton Institute for Electrical and Computer Engineering and faculty advisor for the ARISE student robotics club. Education: Ph.D. in Electrical Engineering from Université Laval (1999) Research interests focus on machine vision, 3D sensing, human motion capture, tactile sensing, robotic navigation, and computational intelligence. His work integrates industry collaboration and has been funded by major granting agencies. Recent articles explore domain adaptation in human action recognition, multi-agent robotics, and soil temperature prediction using AI. His contributions include over 150 technical papers and supervision of 70+ researchers. Awards: Best Paper Awards at IROS 2020 and ISVC 2021 Advising and grants: Over 70 supervised researchers, grants from major agencies. Active in professional roles like co-chair of IEEE TC-28 and organizer of the ROSE conference series. Labs: SMART Group and VIVA Lab, focusing on robotics, sensing, and autonomous systems.

Lilian HsiaoView profile

Associate Professor

• Biomimetic Materials
• Complex Fluids
• Soft Matter Physics
• +6 more

Lilian Hsiao is an Associate Professor & University Faculty Scholar at North Carolina State University's Department of Chemical and Biomolecular Engineering within the College of Engineering. Her research focuses on biomimetic materials, complex fluids, and soft matter, particularly exploring colloidal hydrodynamics and their biomedical applications such as cartilage mechanics and elastohydrodynamic lubrication. She leads a lab of ~12 students and collaborates with Duke and UNC-Chapel Hill researchers. Education: B.S., Chemical Engineering, University of Wisconsin-Madison (2008) Ph.D., Chemical Engineering, University of Michigan (2014) Research Interests: Her work bridges fundamental science and industrial applications, using microscopy and rheology to study materials like shaped colloids and functionalized polymers. Recent projects include developing biodegradable electronics, analyzing colloidal gel elasticity, and investigating surface oxides in liquid metals. Her interdisciplinary approach integrates materials science, physics, and mechanical engineering. Awards: 2019 Marion Milligan Mason Award for Women in the Chemical Sciences Lab & Collaborations: The Hsiao Lab focuses on creating novel soft materials with directional properties inspired by biological systems. They emphasize practical applications in healthcare, robotics, and sustainable electronics. Her CAREER grant (2021) supports elastohydrodynamic lubrication research on soft-patterned interfaces.

Nicholas EdelenView profile

Assistant Professor

• Differential Geometry
• Geometric Analysis
• Geometric Measure Theory
• +2 more

Nicholas Edelen is an Assistant Professor in the Department of Mathematics at the University of Notre Dame, College of Science. His research specializes in geometric analysis and geometric measure theory, focusing on minimal surfaces, mean curvature flow, and singularity analysis. He is affiliated with the Analysis and Partial Differential Equations and Differential Geometry research groups. Education: Ph.D., Stanford University, 2016 BSc, University of Edinburgh, 2012 Research Interests: Dr. Edelen studies problems related to the regularity of minimal surfaces (mathematical models of soap films) and their behavior near singularities. His work connects differential geometry, PDEs, and geometric measure theory to analyze structural properties of singular sets in high-dimensional spaces. Publications: His recent articles predominantly explore minimal surfaces, capillary boundary conditions, and regularity theory, with frequent collaborations addressing both theoretical foundations and applied geometric analysis. Common themes include singularity formation, free boundary problems, and geometric evolution equations. Awards: NSF Fellowship He currently leads the Graduate Differential Geometry course and co-organizes the Geometry and Analysis seminar. His research is supported by NSF grant DMS-2204301. Past teaching includes undergraduate real analysis, calculus, and geometric measure theory. Dr. Edelen collaborates with international researchers and contributes to interdisciplinary teams focusing on PDE-driven geometric phenomena.

• Applied Mathematics
• Fluid Dynamics
• Biological Spatial Patterns
• +3 more

Associate Professor Benjamin Binder is affiliated with the University of Adelaide's School of Computer and Mathematical Sciences within the Faculty of Sciences, Engineering and Technology. He holds the academic rank of Associate Professor and has been with the institution since 2009. His research focuses on applied mathematics, particularly in the areas of free-surface flows and biological spatial patterns. He was awarded a PhD in Applied Mathematics from the University of East Anglia (UK) in 2005 and has held research positions at the University of Melbourne and the University of Adelaide. His work integrates numerical and analytical methods to address problems in fluid dynamics, mathematical biology, and biophysics. Education: PhD in Applied Mathematics (2005, University of East Anglia, UK). Research interests include quantifying biological spatial patterns, predicting channel bed topography in free-surface flows, and developing models for cell invasion and tissue growth. He is actively involved in supervising postgraduate research students in applied mathematics and related fields. Key research areas span fluid dynamics (e.g., free-surface flows over topography, nonlinear waves) and mathematical biology (e.g., cell migration modeling, biofilm expansion). His recent publications address topics such as Kelvin wake reduction, diffusion-limited processes, and multicellular modeling frameworks.

Mark ThachukView profile

Associate Professor

• Chemical Reaction Dynamics
• Computational Chemistry
• Gas-Phase Ion Chemistry
• +3 more

Mark Thachuk is an Associate Professor in the Department of Chemistry at the University of British Columbia's Faculty of Science. His research focuses on the theoretical and computational study of chemical reaction dynamics, particularly in gas-phase systems. He maintains an active research program examining collision-induced alignment of gas-phase ions and the dissociation mechanisms of protein complexes. Dr. Thachuk received his B.Sc. from Western Ontario in 1986, followed by a Ph.D. from Waterloo under F.R.W. McCourt in 1991. He completed postdoctoral work at Northwestern University with G.C. Schatz (1991-1993) and at Queen's University in Kingston with D.M. Wardlaw (1993-1996). Dr. Thachuk's primary research interests involve the study of chemical reaction dynamics using mathematical and computational techniques. His work spans two main areas: collision-induced alignment of gas-phase ions and the dissociation mechanisms of gas-phase protein complexes. In the first area, his group uses molecular dynamics simulations to model how ions develop preferred alignment when moving through gases under external fields or in molecular beam expansions. They investigate how this alignment depends on molecular parameters such as charge and mass distribution. In the second area, his research examines the unusual charge asymmetry observed in the dissociation of gas-phase protein complexes, where fragments often show uneven charge distribution rather than symmetrical splitting. His group employs molecular dynamics simulations and develops simplified models to understand these phenomena without resorting to computationally intensive atomistic simulations. Analysis of Dr. Thachuk's publication record from 2000-2010 reveals a consistent focus on gas-phase ion dynamics and protein complex dissociation. His work bridges physical chemistry, computational chemistry, and biochemistry, with particular emphasis on understanding the fundamental mechanisms behind ion mobility, alignment, and fragmentation. The research shows progression from studying simpler systems like H 2 O + and NO + drifting in noble gases to more complex protein systems, demonstrating an expanding scope of investigation while maintaining focus on the underlying physical principles. Dr. Thachuk's research program involves mentoring graduate students who work on computational projects related to gas-phase ion chemistry and protein dynamics. His group develops and applies molecular dynamics simulation techniques to address questions in physical chemistry that have implications for mass spectrometry and biomolecular analysis. While specific laboratory facilities aren't detailed in the available information, Dr. Thachuk's computational research would require access to high-performance computing resources. His work appears to be conducted primarily through simulation studies rather than experimental setups, suggesting his "lab" consists of computational infrastructure and collaborative relationships with experimental groups.

Amir VaxmanView profile

Associate Professor

• Geometry Processing
• Discrete Differential Geometry
• Directional-Field Design
• +4 more

Amir Vaxman is a Reader in Graphics, Simulation and Visual Computing at the School of Informatics, The University of Edinburgh, where he leads the Geometry Processing Group within the Institute of Perception, Action and Behaviour. Previously, he was an assistant professor at Utrecht University in the Netherlands and a postdoctoral fellow at TU Wien (Vienna) where he received the Lise-Meitner fellowship. Ph.D. in Computer Science, Technion-IIT, 2011 M.Sc. in Computer Science, Technion-IIT, 2006 B.Sc. in Computer Engineering, Technion-IIT, 2002 Dr. Vaxman's research focuses on geometry processing and discrete differential geometry , with particular interests in directional-field design, unconventional meshes, constrained shape spaces, architectural geometry, and medical applications. His work bridges theoretical mathematics with practical applications in computer graphics, visualization, and fabrication. His recent publications (2023-2025) demonstrate a strong focus on geometric modeling, neural surface reconstruction, and directional field synthesis. Key trends include the development of novel algorithms for mesh processing, integration of deep learning with geometric modeling, and applications to medical imaging and architectural design. Best Paper Award (Honorable Mention) at SIGGRAPH 2024 for "Fabric Tessellation: Realizing Freeform Surfaces by Smocking" Runner-Up Best Paper Award at Symposium on Geometry Processing (SGP) 2023 for "BPM: Blended Piecewise Möbius Maps" Software Award at Symposium on Geometry Processing 2021 for libhedra Dr. Vaxman has supervised numerous graduate students including 5 current PhD candidates and over 20 graduated students. He serves in editorial roles for ACM Transactions on Graphics and has been program co-chair for multiple major conferences including Shape and Physical Modeling (SPM) 2026. He leads the Geometry Processing Group at the University of Edinburgh, which focuses on developing cutting-edge algorithms for geometry processing, with applications ranging from computer graphics to architectural design and medical imaging.

Luca GiomiView profile

Professor

• Soft Matter Physics
• Biological Physics
• Active Matter
• +5 more

Luca Giomi is a Professor of Theoretical Physics at Leiden University , affiliated with the Leiden Institute of Physics (LION) within the Faculty of Science . He leads the Giomi Group - Soft and Bio Mechanics , focusing on understanding the interplay between geometry, topology, and mechanics in soft and biological systems. His research spans active matter, liquid crystals, and cellular mechanics. Key Research Areas : Soft Matter, Active Nematics, Topological Defects, Biophysical Modeling Methodologies : Analytical theory, numerical simulations, and experimental collaborations Giomi's work has been recognized with competitive grants including the ERC Consolidator Grant (2019) and Rubicon Grant (2023). His students include former PhD candidates Josep-Maria Armengol Collado, Dimitrios Krommydas, and Ludwig Hoffmann. The Giomi Group investigates systems ranging from biological cells to synthetic active materials, with emphasis on how geometry and topology influence mechanical behavior.