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William LionheartView profile

Professor

• Inverse Problems
• Imaging Techniques
• Medical Imaging
• +3 more

William Lionheart is a Professor of Applied Mathematics at the University of Manchester, specializing in inverse problems with applications in imaging across industry, security, medicine, and non-destructive testing. He leads research collaborations including the Henry Mosley Centre for X-ray Imaging and the Land Mine Research Centre. His work integrates theoretical, numerical, and practical methods to advance imaging technologies. Education: BSc, PhD in Applied Mathematics. Key research areas include electrical impedance tomography, X-ray imaging, and polarizability tensor-based object characterization. He has pioneered techniques for metallic object detection and medical imaging applications. Research highlights include developing algorithms for synthetic aperture radar, elastic strain reconstruction, and proton therapy verification systems. Awards include the Wolfson Research Merit Award (2015) and a 2013 recognition. He has contributed to 193+ research outputs, led 11 projects (e.g., RASTER, SEMIS Phase III), and organized conferences like the 2023 'Rich and Nonlinear Tomography' event. His work impacts airport security, land mine detection, and medical diagnostics, generating over USD215M in industrial applications.

Jose LadoView profile

Assistant Professor

• Quantum Materials
• Graphene
• Topological Superconductivity
• +5 more

Jose Lado is an Assistant Professor at the Department of Applied Physics, Aalto University. His research focuses on exotic quantum states in two-dimensional materials and twisted van der Waals systems, including topological superconductivity, quantum spin liquids, and fractionalized matter. He actively collaborates with experimental groups and leads projects like ULTRATWISTROICS and ERC-funded FQF P4 T30428 . Research Interests : Correlated quantum materials, topological superconductivity, graphene-based heterostructures, and moiré quantum matter Key Themes : Electronic correlations, symmetry-breaking states, quantum engineering of fractional particles, and spin-textured flat bands His recent publications emphasize non-Hermitian topology, Kondo lattice dynamics, and machine learning applications in many-body systems. Awards include three Early Career recognitions (2021-2023). He contributes to UN Sustainable Development Goals through quantum material innovation.

• Medical Imaging
• Biomedical Engineering
• Image Processing
• +3 more

Dr. Chas Nelson is an Affiliate Researcher at the School of Biodiversity, One Health & Veterinary Medicine, University of Glasgow. His work focuses on advanced image processing techniques applied to biomedical and biological systems. He collaborates extensively with colleagues like Boguslaw Obara and Jonathan Taylor, contributing to fields such as fluorescence microscopy, 3D biomedical imaging, and algorithmic development for medical visualization. His research interests include enhancing curvilinear structures in 2D/3D images, developing nuclei detection methods using mathematical morphology, and improving real-time image segmentation through GPU computing. Key projects involve applications in retinal imaging, zebrafish heart development, and plant cell analysis. Nelson has published widely in journals like Frontiers in Neural Circuits , Nature Communications , and Pattern Recognition , with a focus on methodologies like the multiscale top-hat tensor and bowler-hat transform. His technical expertise spans computer vision, biomedical engineering, and computational biology. He is affiliated with the Graham Kerr Building and contributes to interdisciplinary collaborations in One Health and veterinary medicine. No scientific awards or formal advising roles are explicitly listed.

Xiangyi MengView profile

Assistant Professor

• Quantum Networks
• Network Science
• Quantum Information
• +11 more

Prof. Xiangyi "X" Meng is an Assistant Professor at Rensselaer Polytechnic Institute's Department of Physics, Applied Physics, and Astronomy. His academic journey includes a B.S. in microelectronics from Peking University and a Ph.D. in physics from Boston University under Prof. Eugene Stanley. He held postdoctoral positions at Northeastern University's Center for Complex Network Research with Prof. Albert-László Barabási and as a Research Associate at Northwestern University with Prof. István Kovács. RPI (2025-present): Assistant Professor Northeastern University (2021-2023): Postdoc Northwestern University (2023-2024): Research Associate His research spans quantum networks, network science, and interdisciplinary applications, with key contributions in: Quantum communication protocols Concurrence percolation theory Quantum field theory applications Computational social science Power grid resilience modeling Multi-community epidemic spreading Prof. Meng has published over 20 papers in top journals like Physical Review Letters, PNAS, and Nature Communications, focusing on quantum advantage in network connectivity, entanglement distribution, and nonlinear network dynamics. His work has been featured in Physics World and Phys.org media outlets. As an educator, he teaches Physics II and Introductory Quantum Mechanics . His team develops quantum-inspired machine learning architectures like entanglement-structured LSTM networks. Current research explores nonconvex entanglement measures and hypergraph immersion techniques for quantum network optimization.

• Machine Learning
• High-Dimensional Statistics
• Network Models
• +4 more

Yang Feng is a Professor and Ph.D. Program Director in the Department of Biostatistics at New York University's School of Global Public Health. He holds affiliate faculty positions at the Center for Data Science and PRIISM, also at NYU. He earned his Ph.D. in Operations Research from Princeton University in 2010. His research focuses on machine learning, high-dimensional statistics, network models, and their applications in healthcare and public health, including Alzheimer's disease and cancer research. His work is funded by NIH and NSF grants, notably the NSF CAREER Award. His research interests include theoretical and methodological advancements in machine learning, statistical theory, and computational methods, with applications to biomedical data analysis. He serves as an Associate Editor for major journals like JASA, JBES, and AoAS. His recognitions include ASA and IMS Fellowships and ISI election. Education: Ph.D. in Operations Research, Princeton University (2010) Dr. Feng’s grants include NSF DMS-2324489 on high-dimensional transfer learning. He collaborates on projects like federated learning theory and clinical outcome prediction in neuro-oncology. His lab develops statistical tools for omics data analysis and public health surveillance. Awards: Fellow, American Statistical Association (ASA) Fellow, Institute of Mathematical Statistics (IMS) Elected Member, International Statistical Institute (ISI) He advises research teams on statistical methodology and data science applications. His work bridges theoretical statistics with practical challenges in healthcare analytics and computational biology.

Miguel A. Morales SilvaView profile

Researcher

• Quantum Physics
• Condensed Matter Physics
• Computational Physics
• +3 more

Miguel A. Morales Silva is a Research Scientist at the Center for Computational Quantum Physics (CCQ) within the Flatiron Institute . His research focuses on developing and applying quantum Monte Carlo (QMC) methods to solve quantum many-body problems, aiming to create predictive, parameter-free first-principles techniques for strongly correlated materials and large-scale high-performance computing applications. Education : B.A. in Physics and Mathematics (2004), University of Puerto Rico at Mayaguez; Ph.D. in Physics (2009), University of Illinois at Urbana-Champaign His research spans computational quantum physics, condensed matter theory, and materials science. Key areas include: Quantum Monte Carlo methodologies Electronic structure of strongly correlated systems Phase transitions in quantum materials High-performance computing for quantum simulations Downfolding ab initio Hamiltonians His recent publications emphasize quantum Monte Carlo studies of 2D materials, electron gases, and cavity-QED systems, with software development contributions to the QMCPACK package. Notable awards include: NNSA Defense Programs Award of Excellence LLNL Early and Mid-Career Recognition Program MOSI Early Career Hispanic Scientist of the Year Presidential Early Career Award for Scientists and Engineers (PECASE)

Marion MenzelView profile

Professor

• Medical Imaging
• Magnetic Resonance Imaging (MRI)
• Quantitative MRI
• +4 more

Marion Menzel is a Professor and Vice Dean at the Faculty of Electrical Engineering and Information Technology (Technische Hochschule Ingolstadt). She specializes in Biomechatronics and Sensor Data Analysis, with a focus on Medical Imaging and Magnetic Resonance Imaging (MRI). Her research emphasizes quantitative MRI techniques, including MR fingerprinting, deep learning applications in medical imaging, and hyperpolarized MRI for metabolic analysis. Education highlights include a Ph.D. (1999–2002) and Diplom-Chemiker (1994–1999) from RWTH Aachen. She has held roles at GE Healthcare, Siemens AG, and Forschungszentrum Jülich before joining THI in 2021. Her work bridges engineering and clinical practice, addressing challenges in imaging reconstruction, parameter mapping, and AI-driven diagnostics. Research interests span MRI acceleration, uncertainty quantification, and multimodal data fusion. She has pioneered methods like StoDIP and MRI2Qmap, advancing 3D imaging and compressive sensing. Her contributions to hyperpolarized 13C MRI enable non-invasive metabolic profiling in oncology and diabetes research. Key awards include recognition as an Alumna of the German Academic Scholarship Foundation. Her lab collaborates on projects like CHAIMELEON, a Pan-European initiative for AI-driven cancer management tools. Recent grants focus on improving diagnostic accuracy through AI and spatiotemporal reconstruction algorithms. Menzel’s team develops open-source frameworks for MRI analysis and actively participates in standardizing medical imaging protocols. Her work has direct clinical impact in neuro-oncology, radiology, and precision medicine.

Guangze ChenView profile

Visiting Professor

• Physics
• Material Science
• Condensed Matter Physics
• +3 more

Guangze Chen is a Visiting Faculty member in the Department of Applied Physics at Aalto University, specializing in the Correlated Quantum Materials (CQM) research group. He holds a Doctor of Technology (Tekn. toht.) in Technical Physics, awarded on August 28, 2023. Research Interests: Physics and Material Science, with 91% specialization in Physics Surface Science and Semimetals (83% Material Science focus) Van Der Waals Heterostructures and Fermion physics (66% focus) Superconductivity research (66% Material Science focus) Magnetic Field applications and Monolayers (50% focus in respective fields) Chen's research output demonstrates significant activity in quantum materials, with 15 publications spanning from 2020 to 2025. His work shows a clear trend toward increasingly sophisticated quantum material engineering, particularly in van der Waals heterostructures and topological quantum systems. His publications appear in high-impact journals including Physical Review Letters, Physical Review Research, and Advanced Materials, with several receiving notable attention from news outlets and academic platforms. Research Impact: Multiple publications picked up by news outlets (up to 11 for some works) Significant social media attention (up to 16 X/Twitter posts) Substantial academic readership (up to 29 Mendeley readers) Citations across Scopus-indexed publications Chen's research bridges theoretical quantum physics with experimental material science, focusing on exotic quantum phases and their potential applications in next-generation quantum technologies.

Sanjaye RamgoolamView profile

Professor

• String theory
• Quantum field theory
• Representation theory
• +3 more

Dr. Sanjaye Ramgoolam is a Reader in Theoretical Physics at the School of Physical and Chemical Sciences, Queen Mary University of London. His research focuses on string theory, quantum field theory, representation theory, and combinatorics, with particular emphasis on gauge-string duality (AdS/CFT correspondence) and permutation invariant matrix models. He has pioneered mathematical frameworks using representation theory and combinatorics to explore the holographic map between quantum field theories and string theory. His work also extends to applications in financial matrix models and computational linguistics via matrix statistics. Teaching roles include advanced courses such as Mathematical Techniques 4 and Advanced Quantum Field Theory. He has supervised numerous PhD students, including Costis Papageorgakis and Tom Brown, and collaborates with researchers like Andreas Brandhuber and Rodolfo Russo on grants like 'Amplitudes, Strings and Duality' funded by STFC. Recent research highlights include Gaussian permutation invariant matrix models, quantum thermodynamics in large N systems, and combinatorial topological string theories. His work bridges fundamental physics with mathematical structures, offering insights into quantum gravity and dualities. Key grants include the Royal Society-funded 'Combinatorics and algorithms for quantum states in holography' (2025-2026) and STFC's 'Amplitudes, Strings and Duality' (2023-2026). His 15 most recent articles span topics like eigenvalue systems for multi-matrix invariants, permutation symmetry in quantum thermodynamics, and Kronecker coefficients from ribbon graphs. Though no explicit awards are listed, his extensive publications and grants reflect significant contributions to theoretical physics.

• Computational Physics
• Quantum Many-Body Systems
• Machine Learning in Physics
• +3 more

Dr. Jannes Nys is a researcher at the Professorship for Computational Physics at ETH Zürich. His work bridges computational physics and machine learning, focusing on quantum systems and many-body problems. Email: jannys@phys.ethz.ch Research Interests: His research spans computational physics, quantum many-body systems, and machine learning applications in physics. He develops neural network-based quantum states and symmetry-aware algorithms for simulating complex quantum phenomena. Quantum Many-Body Systems Neural Quantum States Ab-initio Simulations Quantum Chemistry Topological Entanglement High Energy Physics Recent Article Trends: His publications highlight the intersection of machine learning and quantum physics, including neural wavefunction optimization for non-Hermitian systems, symmetry-aware models for electron spectroscopy, and variational methods for real-time quantum dynamics. He also explores exotic hadrons in particle physics and novel quantum Monte Carlo approaches.

• Photonics
• Nonlinear Optical Physics
• Wireless Power Transfer
• +5 more

Marin Soljacic is a Professor of Physics at the Massachusetts Institute of Technology (MIT), serving as a Principal Investigator in the Research Laboratory of Electronics (RLE). He holds a B.S.E. from MIT (1996), and M.A. and Ph.D. in physics from Princeton University (1998, 2000). His career includes a Pappalardo Fellowship at MIT (2000–2003) and roles as Principal Research Scientist in RLE (2003–2005) before joining the MIT faculty in 2005. His research focuses on manipulating light through nanostructured materials, exploring phenomena like photonic crystals, metamaterials, and wireless power transfer. Key areas include nonlinear optics, plasmonics, and topological photonics. His work has led to innovations in X-ray imaging, radiative cooling, and quantum technologies. Notable achievements include the 2014 Blavatnik National Award and recognition from the Optical Society of America (2005). He leads interdisciplinary projects, blending photonics with AI, robotics, and materials science. His lab develops advanced optical systems for energy, healthcare, and computation. Recent publications highlight breakthroughs in AI-driven photonics design, quantum correlations in optical systems, and nanophotonic scintillators. His work bridges theoretical insights with practical applications, addressing global challenges in energy and healthcare.

Nikhil Chandra AdmalView profile

Assistant Professor

• Atomistic origins of continuum theories
• Interfacial mechanics
• Nanomechanics
• +6 more

Nikhil Chandra Admal is an Assistant Professor in the Department of Mechanical Science and Engineering at the University of Illinois Urbana–Champaign , where he has held this position since January 2019. His research focuses on interfacial mechanics, atomistic origins of continuum theories, and nanomechanics, with applications in 2D materials, grain boundaries, and crystal plasticity. He also held an Adjunct Assistant Professor role (2018–2019) and completed a postdoctoral fellowship at UCLA’s Materials Science and Engineering department (2014–2019). Education: Ph.D. Aerospace Engineering and Mechanics, University of Minnesota (2014) M.S. Mathematics and M.S. Aerospace Engineering, University of Minnesota (2011, 2010) B.Tech/M.Tech (Dual) Mechanical Engineering, Indian Institute of Technology Madras (2006) Research Highlights: Dr. Admal’s work bridges atomistic and continuum scales, particularly in analyzing dislocations, grain boundary mechanics, and interfacial phenomena in materials like graphene and polycrystals. His recent studies include superlubricity in bilayer graphene, stochastic models for grain evolution, and mechanics-driven surface faceting in 2D heterostructures. Awards: He received the 2023 Early Career Award and CAREER Award, along with the IDRE Postdoctoral Fellowship (2016). His work has been recognized in journal articles and conference proceedings, with over 30 peer-reviewed publications to date. Teaching & Service: Teaches courses such as TAM 210 (Statics), TAM 445 (Continuum Mechanics), and TAM 574 (Advanced Finite Element Methods). Active in organizing conferences like USACM and USNCCM, and chairs the USACM Nanotechnology Thrust Area. Holds leadership roles in professional societies including the United States Association for Computational Mechanics.

Philippe CorbozView profile

Associate Professor

• Strongly correlated quantum many-body systems
• 2D tensor network algorithms
• Fermionic lattice models
• +5 more

Philippe Corboz is an Associate Professor in Condensed Matter Theory at the Institute for Theoretical Physics (ITFA) within the Faculty of Science at the University of Amsterdam (UvA). He is affiliated with the Delta Institute for Theoretical Physics (D-ITP), the European Tensor Network, and QuSoft. His research focuses on computational methods for simulating strongly correlated quantum many-body systems, particularly 2D tensor network algorithms like PEPS and MERA. His work addresses applications in: Fermionic lattice models (Hubbard/t-J) related to high-Tc superconductivity Frustrated spin systems (Shastry-Sutherland model, SU(N) Heisenberg models) Bosonic systems (Helium-4 films, supersolids) Corboz also investigates quantum Monte Carlo and density matrix renormalization group (DMRG) methods. He teaches the course "Advanced numerical methods in many-body physics" (6EC), emphasizing practical implementation in Python. Current group members include postdocs Qi Yang, Wout Merbis, Naushad Kamar, and PhD students Yining Zhang, Stijn Kleijweg, Emilio Cortes Estay. Former students include Juan Osorio Iregui, Ido Niesen, and Boris Ponsioen. His research is supported by the European Research Council (ERC) and the UvA Institute of Physics (IoP).

• Quantum Computing
• Topological Quantum Computation
• Tensor Networks
• +3 more

Andreas Bauer is a Research Fellow at the Department of Mechanical Engineering , Massachusetts Institute of Technology , focusing on quantum computing and topological phases of matter. His work bridges theoretical physics and computational methods, with an emphasis on fault-tolerant systems and tensor networks. Research Focus: Topological quantum computation, quantum error correction, tensor networks, and condensed matter physics. Email: andib@mit.edu

Frank VerstraeteView profile

Professor

• Quantum Physics
• Theoretical Physics
• Condensed Matter Physics
• +4 more

Frank Verstraete is the Leigh Trapnell Professor of Quantum Physics at the University of Cambridge's Department of Applied Mathematics and Theoretical Physics (DAMTP), part of the Faculty of Mathematics. He also holds a concurrent professorship in Theoretical Physics at Ghent University since 2012 and previously served as Professor of Physics at the University of Vienna (2006–2019). His research focuses on entanglement in quantum computation and interacting quantum many-body systems, developing quantum tensor network theories, computational optimization methods, and applying them to condensed matter physics, quantum field theory, atomic physics, statistical physics, and quantum computing. He leads the Centre for Quantum Information and Foundations and maintains an office in Room B0.14 at the DAMTP facility on Wilberforce Road, Cambridge. Frank Verstraete's career includes roles as a Research Scholar at Caltech (2004–2006) and Research Fellow at the Max Planck Institute for Quantum Optics (2002–2004). His work emphasizes foundational advancements in tensor network states, including matrix product states (MPS) and projected entangled-pair states (PEPS), with applications to topological phases, quantum error correction, and lattice gauge theories. Notable research contributions include studies on non-Abelian symmetries, anyonic excitations, and the interplay between entanglement structure and physical observables. Key research themes: Entanglement scaling, quantum phase transitions, topological order, and tensor network optimization Professional affiliations: DAMTP, Centre for Quantum Information and Foundations External collaborations: Ongoing work with Caltech's Institute for Quantum Information and the Max Planck Institute for Quantum Optics His scientific contributions are accessible via his personal homepage http://www.qi.damtp.cam.ac.uk/person/fv285 and through arXiv/Google Scholar. While no explicit awards are listed, his extensive publication record and leadership roles reflect a distinguished career in quantum information science. Advising activities and grant details are not detailed in the provided texts.