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Gordon KindlmannView profile

Associate Professor

• Biomedical Image Analysis
• Scientific Visualization
• Systems
• +5 more

Gordon Kindlmann is an Associate Professor of Computer Science at the University of Chicago, affiliated with the Systems Group research community. His work bridges computational imaging science and visualization theory, focusing on biomedical applications and machine learning integration. He leads projects in diffusion MRI analysis, surgical planning tools like SlicerDMRI, and theoretical advancements in visualization design. Research Interests: Biomedical Image Analysis Scientific Visualization Theory High Performance Computing Medical Imaging Algorithms Machine Learning Applications Recent Articles Trends: His work emphasizes cardiovascular modeling (e.g., aortic dissection prediction) and visualization validation techniques. Recent collaborations include optimizing visualization tools for scalability and accuracy in threaded data exploration. Awards: None explicitly listed in provided text. Grants/Advising: Involved in CDAC Discovery Grants (2019) and actively supports student research, though specific advisees are not listed here. His lab develops open-source tools like Diderot for tensor field visualization. Labs & Teams: Member of the Systems Group, a collaborative environment advancing systems research, programming languages, and software engineering.

Marcus HolzingerView profile

Professor

• Space Policy
• Space Situational Awareness
• Information Theory
• +4 more

Dr. Marcus Holzinger is the Joseph T. Negler Professor and Hatfield Endowed Professor in Space Policy & Law at the University of Colorado Boulder's Department of Aerospace Engineering Sciences. He leads the Colorado Center for Astrodynamics Research (CCAR) and the VADeR Laboratory, focusing on advancing space exploration through interdisciplinary research in space policy, autonomy, and space situational awareness. His work emphasizes collaboration and sustainable practices in space. Education: PhD in Aerospace Engineering Sciences, University of Colorado Boulder (2011) MS in Aeronautics & Astronautics Engineering, University of Washington (2005) BS in Aeronautics & Astronautics Engineering, University of Washington (2003) Research Interests: Space Policy & Law Space Domain Awareness Autonomy & Decision Support Systems Cislunar Space Dynamics Information Theory & Estimation Space Traffic Management Recent Research Trends: Holzinger’s work prioritizes cislunar space exploration and decentralized decision-making for space systems, with applications in orbital debris mitigation, sensor tasking, and spacecraft autonomy. His publications frequently address challenges in initial orbit determination and spacecraft maneuver detection . Awards: American Astronautical Society Fellow (2022) AIAA Associate Fellow (2018) AFOSR Young Investigator Award (2017) Advising & Labs: Holzinger mentors students in the STARLIT and VADeR Observatories. Notable advisees include Sam Fedeler (2023 PhD) and Katie Melbourne (PhD student). His labs develop technologies like astrographic mapping and sensor networks for space surveillance. Labs/Teams: CCAR and the VADeR Lab collaborate on projects funded by NASA, AFRL, and industry partners, emphasizing hardware-in-the-loop testing and space policy frameworks.

• Image Processing
• Computer Vision
• Signal Processing
• +4 more

Sos S. Agaian is a Professor affiliated with City University of New York (CUNY), USA, with a former position at the University of Texas at San Antonio's Department of Electrical and Computer Engineering. His research focuses on advanced image and signal processing techniques, including thermal imaging, medical imaging, neural networks, and computer vision applications. He has authored numerous publications in top-tier journals and conferences, contributing to fields like adversarial attack defenses, solar panel segmentation, and quantum-inspired algorithms. His work emphasizes practical solutions for image enhancement, deblurring, and segmentation, with applications in healthcare, energy systems, and cybersecurity. Research Interests: Image Processing and Computer Vision Signal Processing and Machine Learning Medical and Thermal Imaging Neural Networks and Deep Learning Quantum Computing Applications in Imaging Recent Trends in Articles: Recent work highlights advancements in quaternion-based neural networks for weather removal, lightweight networks for solar panel fault detection, and novel entropy models for thermal imaging. Collaborations span medical diagnostics, cybersecurity, and energy systems, reflecting interdisciplinary impact. Grants and Collaborations: While specific grants are not detailed, his extensive publication record suggests active research funding in areas like computer vision and quantum information processing. Collaborators include institutions globally, emphasizing translational research. Labs/Teams: Not explicitly mentioned, but his work implies involvement in imaging and machine learning research groups focused on practical solutions for real-world challenges.

Armin IskeView profile

Professor

• Numerical Approximation
• Applied Mathematics
• Kernel Methods
• +4 more

Prof. Dr. Armin Iske is a Full Professor of Numerical Approximation at the University of Hamburg's Department of Mathematics, within the Faculty of Mathematics, Computer Science and Natural Sciences. He holds a PhD from the University of Göttingen (1994) and habilitation from TU Munich (2002). His research focuses on numerical approximation, kernel-based methods, computational fluid dynamics, and medical imaging. He has held academic positions globally, including visiting roles at ANU (Australia) and the University of Leicester (UK). Research interests include scattered data approximation, adaptive particle methods for flow simulation, and high-dimensional data analysis. He has authored 118+ publications, including works on kernel interpolation, medical imaging reconstruction, and machine learning applications. He serves on editorial boards for journals like Advances in Computational Mathematics and Sampling Theory . His contributions span interdisciplinary projects, such as SFB/TRR 181 on energy transfer in atmosphere and ocean, and collaborations in nanotechnology for brain interfaces. His work bridges theoretical mathematics with practical applications in engineering and biosciences.

• Electron Scattering from Light Nuclei
• Quark-Hadron Duality
• Spatial Economic Networks

Sabine Jeschonnek is a Professor at the Lima Campus of The Ohio State University (OSU), affiliated with the Department of Physics. She holds a Dipl. Phys. (1993) and Ph.D. in Physics (1996) from the University of Bonn, Germany. Her research focuses on electron scattering from light nuclei, quark-hadron duality, and spatial economic networks. Notable studies include investigations into nucleon response functions, relativistic effects in deuteron reactions, and neutrino-nucleus interactions. She has contributed to experiments at Jefferson Lab and CEBAF, emphasizing precision measurements of neutron form factors and the luminosity frontier in particle physics. Recent work explores tensor structures in electron scattering and final-state interactions in quasielastic regimes. Her articles span theoretical frameworks for electromagnetic currents and experimental analyses of high-momentum nuclear dynamics. Dr. Jeschonnek’s research has advanced understanding of deuteron structure, QCD nuclear physics, and relativistic corrections in nuclear reactions. She is actively involved in interpreting CLAS/Hall B data and advancing models for quark-hadron duality.

John R. de BruynView profile

Professor

• Experimental Condensed Matter Physics
• Soft Materials
• Biological Systems Physics
• +3 more

John R. de Bruyn is a Professor in the Department of Physics and Astronomy at the University of Western Ontario. His research focuses on experimental condensed matter physics, particularly soft materials, biological systems physics, and non-equilibrium dynamics. He leads the de Bruyn research group, which collaborates internationally and uses advanced rheological techniques. Current projects include studies on thixotropic suspensions, star polymers, and MR-compatible medical device materials. Key equipment includes an MCR 302 rheometer. He has supervised numerous graduate and undergraduate students, including Cameron Hopkins (Don Hay Prize winner), Grace Ge (M.Sc. in polyisoprene composites), and Nirosh Getangama. Recent grants include a $705k CFI grant for medical device testing and a Western Academic Development Fund grant for rheometry equipment. Notable collaborations include work with Simon Rogers at UIUC and Dimitris Vlassopoulos in Crete (FORTH). His group also explores interdisciplinary topics like phagocytosis mechanisms and solar eclipse physics. He has presented at conferences such as the Waterloo Soft Matter Conference and the Canadian Association of Physicists annual meeting.

Ali OzelView profile

Assistant Professor

• Fluid Mechanics
• Multi-scale Modeling
• Gas-Particle Flows
• +5 more

Dr. Ali Ozel is an Assistant Professor at Heriot-Watt University's School of Engineering & Physical Sciences, specializing in fluid-particle flows and multi-scale modeling. His work bridges academic institutions and industry collaborations, including INEOS, Princeton University, and Toulouse's Fluid Mechanics Institute. PhD in Fluid Mechanics (Toulouse, 2011) B.Sc. & M.Sc. in Aerospace Engineering (Istanbul Technical University) Research Master in Environmental & Applied Fluid Dynamics (von Karman Institute) His research focuses on: Multi-scale modeling of fluid-particle flows (micro/meso/macro) Solvent-based carbon capture technologies (Volume of Fluid simulations) Rheology of dense granular suspensions (shear thickening/thinning) Development of xFlow - Complex Flow Technologies for decarbonization Hybrid digital twins combining physics and machine learning Using data-driven approaches and advanced computational tools, Dr. Ozel formulates constitutive models for industrial applications in energy, pharmaceuticals, and manufacturing. His recent publications emphasize neural networks for fluid dynamics, particle stress modeling, and decarbonization strategies. Scientific Awards: Marie Curie Fellows Association Grant Dr. Ozel actively supervises PhD students and collaborates with international institutions on computational modeling projects. His xFlow initiative investigates clean energy integration and device optimization through rigorous multi-scale methodologies.

• Neuroimaging
• Functional Magnetic Resonance Imaging
• Language
• +7 more

Professor Katie McMahon is a leading academic at Queensland University of Technology (QUT), holding dual roles as Deputy Director of the Herston Imaging Research Facility and Academic Lead for Research at the School of Clinical Sciences. With a PhD from the University of Queensland, her expertise spans neuroimaging and cognitive neuroscience. Research Focus: Neurobiology of language, genetics of brain development, and neuroimaging applications in stroke, epilepsy, and pediatric language disorders (e.g., autism). Collaborations: Works with Queensland Health and philanthropic organizations on brain imaging and musculoskeletal studies. Teaching: Contributes to radiation therapy and MR-guided radiation therapy courses, emphasizing clinical sciences education. Recent Research Trends: Her work bridges neuroimaging techniques (fMRI, DTI) with cognitive deficits, exploring lexical processing, aphasia recovery, and genetic influences on brain structure. Recent studies address stroke rehabilitation, epilepsy language deficits, and fatty liver imaging protocols. Grants & Projects: Lead investigator on grants like “Predicting and Promoting Aphasia Recovery” (2016) and “Enhancing Language Learning in Ageing with Exercise” (2016). Labs/Teams: Active in the Herston Imaging Research Facility and National Imaging Facility committees.

Mikjel ThorsrudView profile

Associate Professor

• Theoretical Physics
• Cosmology
• Gravitation
• +5 more

Mikjel Thorsrud is an Associate Professor in the Department of Engineering at Høgskolen i Østfold. His research focuses on theoretical physics and cosmology, particularly gravitation, general relativity, and modified gravity. He holds a PhD in Cosmology from the University of Oslo (2014) and a Master's in theoretical physics (2010). His work explores topics like Bianchi cosmologies, anisotropic curvature, and gauge fields in cosmological models. Thorsrud has been recognized with awards for outstanding reviewing in Classical and Quantum Gravity (2018-2019) and an academic writing scholarship (2018). He contributes to research groups like N-PACT (Norwegian Particle, Astroparticle and Cosmology Theory Network) and has published extensively in journals such as Classical and Quantum Gravity and Journal of Cosmology and Astroparticle Physics .

• Homotopy Theory
• Algebraic Geometry
• Combinatorics
• +3 more

Kyle Ormsby is an Associate Professor of Mathematics and Department Chair at Reed College. His research focuses on homotopy theory, algebraic geometry, and combinatorics, with particular interests in operads, equivariant homotopy, and geometric data analysis. He teaches courses like Math 111 (Calculus), Math 201 (Linear Algebra), and Math 411 (Advanced Analysis). His work bridges abstract algebraic structures and combinatorial methods, often involving collaborations with students and researchers in homotopical combinatorics. Ormsby's research explores topics such as transfer systems, N∞ operads, and motivic homotopy theory, with applications to algebraic K-theory and geometric data analysis in neuroimaging. He has organized conferences like the 2024 Homotopical Combinatorics MRC and co-founded the Project Project lab for visualizing mathematical concepts. His publications span journals like Glasgow Mathematical Journal and Homology, Homotopy and Applications , with a focus on combinatorial and categorical approaches to homotopy theory. Ormsby mentors undergraduate research, resulting in student-authored papers such as Equivariant Linear Isometries Operads and Injectivity and Surjectivity of the Dress Map . His work emphasizes interdisciplinary connections, blending pure mathematics with computational tools and visualization.

Ning BaoView profile

Assistant Professor

• High Energy Physics
• Quantum Information Science
• Quantum Algorithms
• +4 more

Ning Bao is an Assistant Professor in the Departments of Physics and Mathematics at Northeastern University's College of Science. His research bridges high energy theory and quantum information science, focusing on topics such as holographic correspondences, quantum entanglement classification, and quantum algorithm development. He explores the interplay between quantum information principles and fundamental physics concepts like black hole thermodynamics and spacetime geometry. His work often involves cutting-edge techniques from machine learning and applied mathematics to address questions in quantum gravity and condensed matter systems. Key research interests include the information-theoretic properties of black holes, entanglement structure in holographic systems, and the application of quantum information tools to machine learning. He contributes to foundational studies in quantum error correction, entanglement wedge reconstruction, and the ER=EPR conjecture. His articles span topics from AdS/CFT correspondence to quantum cellular automata, reflecting his interdisciplinary approach to theoretical physics. Bao’s research is supported by contributions to holographic entropy inequalities, tensor network models, and the exploration of quantum algorithms through frameworks like classical shadows and reinforcement learning. His work has advanced understanding of entanglement in gauge theories, quantum complexity measures, and the interplay between geometry and quantum information in gravitational systems.

Mark A IwenView profile

Associate Professor

• Computational Harmonic Analysis
• Mathematical Data Science
• Signal Processing
• +4 more

Mark A Iwen is an Associate Professor at Michigan State University, holding dual appointments in the Department of Mathematics and the Department of Computational Mathematics, Science and Engineering (CMSE) . His research focuses on computational harmonic analysis, mathematical data science, signal processing, and algorithms for analyzing high-dimensional datasets. He has contributed to advancements in sparse Fourier transforms, compressive sensing, and sublinear-time algorithms for large-scale data. Key research themes include: Efficient algorithms for high-dimensional PDEs and spectral methods Phase retrieval and inverse problems in imaging Optimization of tensor decompositions and dimensionality reduction techniques Development of sparse approximation methods with theoretical guarantees His recent work emphasizes applications in: Sublinear-time algorithms for function approximation Terminal embeddings for manifold data Fast JL embeddings with bi-Lipschitz properties Tensor completion and low-rank approximations Notable contributions include: Development of Sparse Harmonic Transforms for functions of many variables Advancements in distributed SVD algorithms for large networks Empirical and theoretical analysis of phase retrieval techniques Efficient sparse FFT implementations (e.g., DMSFT, GFFT) Iwen collaborates on open-source code projects, including sparse FFT libraries and phase retrieval tools. His work bridges mathematical theory with practical applications in engineering and computational science.

Thomas SchlumprechtView profile

Professor

• Functional Analysis
• Banach Spaces
• Probability Theory
• +3 more

Thomas Schlumprecht is a Professor at the Department of Mathematics, Texas A&M University (College of Arts & Sciences), holding a concurrent adjunct position at the Czech Technical University, Prague. He earned his Ph.D. (1988) and Diplom (1982) from Ludwig-Maximilians-Universität, München. His research focuses on Functional Analysis, Banach spaces, Probability Theory, Convex Geometry, and Mathematics in Finance. He has held various roles at Texas A&M since 1992, including Associate Head for Graduate Studies (2001–2005) and Professor since 1999. Schlumprecht’s work includes editorial roles for the Journal of Functional Analysis and Banach Journal of Mathematical Analysis . His teaching contributions span courses like Functional Analysis and Infinite Combinatorics. Recent research emphasizes metric embeddings, operator theory, and geometric functional analysis. Education: Ph.D. in Mathematics, Ludwig-Maximilians-Universität, München (1988) Diplom (M.Sc.), Mathematics, Ludwig-Maximilians-Universität, München (1982) Research Highlights: Advances in Banach space geometry and asymptotic properties Studies on metric embeddings and coarse rigidity Investigations into operator ideals and closed ideals in Banach algebras His recent publications explore topics such as greedy algorithms, transportation cost spaces, and stochastic embeddings, reflecting a deep engagement with both theoretical and applied aspects of functional analysis.

Robijn VanhoveView profile

Research Fellow

• Theoretical Physics
• Condensed Matter Physics
• Quantum Information
• +3 more

Robijn Vanhove is a Research Fellow and Visiting Associate in the Department of Physics at the California Institute of Technology (Caltech), supported by the FWO Postdoctoral Scholar Fellowship. His research focuses on theoretical physics, particularly in topological phases of matter, conformal field theories, and quantum information science. He explores connections between topological systems and critical lattice models using advanced tools like tensor networks and quantum circuit analysis. His work bridges abstract mathematical frameworks (e.g., Galois conjugated tensor categories) with computational methods (matrix product states) to study phase transitions, critical phenomena, and quantum symmetries. Notable research includes investigations into Haagerup conformal field theories, Potts models, and symmetry-protected topological phases. He is affiliated with Caltech’s Division of Physics, Mathematics and Astronomy, and potentially collaborates with research centers like the Institute for Quantum Information and Matter (IQIM). Research Highlights: Develops novel mappings between topological phases and critical systems using tensor networks. Applies quantum circuit models to analyze gapped phase transitions. Explores nonunitary conformal field theories through lattice realizations and Cardy states. Awards: FWO Postdoctoral Scholar Fellowship (Belgian Research Foundation). Collaborations: Likely involves interdisciplinary projects with IQIM and other theoretical physics groups at Caltech, focusing on quantum computing applications and topological materials.

• Combinatorics
• Combinatorial Design
• Latin Squares
• +5 more

Ian Wanless is a Research Professor at the School of Mathematics, Monash University. He specializes in combinatorics, with a focus on Latin squares, graph theory, and matrix permanents. His work bridges theoretical mathematics and applications in information technology, such as coding and experimental design. Wanless leads collaborative projects funded by the Australian Research Council, including studies on combinatorial structures and hypergraph matchings. He has authored over 120 peer-reviewed articles, with recent work addressing quantum states, Latin square properties, and quasigroup isomorphisms. Key Awards: Australian Mathematical Society 2009 Medal Collaborations: Global partnerships with institutions in the US, Europe, and Asia His research emphasizes universal solutions to combinatorial puzzles, such as Sudoku and the four-color theorem, while prioritizing theoretical rigor over direct applications.