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Antonio PonnoView profile

Associate Professor

• Mathematical Physics
• Hamiltonian Systems
• Quantum Mechanics
• +4 more

Antonio Ponno is an Associate Professor in the Department of Mathematics at the University of Padua, specializing in Mathematical Physics. He has been in this position since November 2014, following a Researcher tenure at the same institution from 2006-2014 and a postdoctoral position at the University of Milan from 2002-2006. His academic journey includes a Master's Degree in Physics from Sapienza University of Rome (1998) and a PhD in Physics from the University of Padua (2002). Professor Ponno's research primarily focuses on Hamiltonian Systems , with particular expertise in the Fermi-Pasta-Ulam problem and related models. His work explores the connections between nonlinear dynamics, statistical mechanics, and integrable systems. He investigates how energy transfers through complex systems, the relationship between the Fermi-Pasta-Ulam model and integrable approximations like the Toda lattice, and the emergence of macroscopic behavior from microscopic dynamics. His research spans both classical and quantum mechanical systems, with applications ranging from molecular dynamics to wave phenomena. Analysis of his recent publications (2020-2024) reveals a continued strong focus on the Fermi-Pasta-Ulam problem and its connections to integrable systems. His work demonstrates sophisticated mathematical techniques applied to fundamental questions in statistical mechanics, with recent papers examining energy cascade phenomena, Burgers turbulence in lattice systems, and the thermodynamic limit of adiabatic invariants. He has also applied his expertise in nonlinear dynamics to diverse areas including epidemiological modeling during the COVID-19 pandemic. Professor Ponno maintains an active research program with consistent publications in prestigious journals including Physical Review E, Journal of Statistical Physics, and Communications in Mathematical Physics. He teaches 'Istituzioni di Fisica Matematica' for undergraduate Physics students and 'Mathematical Physics' for Master's students at the University of Padua. His courses cover dynamical systems, Hamiltonian mechanics, and mathematical methods in physics, with detailed lecture notes that reflect his research expertise. Professor Ponno collaborates extensively with researchers including Giancarlo Benettin, Marco Gallone, and Stefano Ruffo, demonstrating strong research networks in mathematical physics both within Italy and internationally.

Jason KayeView profile

Research Fellow

• Numerical Analysis
• Computational Quantum Physics
• Quantum Many-Body Problems
• +4 more

Jason Kaye serves as a Flatiron Research Fellow at the Flatiron Institute since September 2019, jointly appointed by the Center for Computational Mathematics and Center for Computational Quantum Physics. His expertise lies in developing robust numerical algorithms for computational quantum physics challenges. His academic credentials include: Ph.D. in Mathematics from New York University M.S. in Mathematics from Cambridge University B.S. in Mathematics from Brown University Dr. Kaye specializes in high-order adaptive methods and fast algorithms for compressing structured operators, with direct applications to integral/differential equations in quantum systems. His research significantly advances many-body Green’s function methods, quantum embedding frameworks, and electronic structure calculations—bridging numerical mathematics with quantum many-body problem solving. This work enables scalable simulations of complex quantum phenomena through algorithmic innovation. Embedded within both computational centers, he contributes to interdisciplinary teams advancing mathematical foundations for quantum physics simulations, leveraging the Institute's focus on high-performance computational science.

Peter FuldeView profile

Adjunct Professor

• Condensed Matter Physics
• Superconductivity
• Quantum Many-Body Systems
• +3 more

Prof. Peter Fulde was an emeritus Director and Scientific Member of the Max Planck Institute for the Physics of Complex Systems in Dresden. He held academic positions including Full Professor at Frankfurt University (1968–1971), Adjunct Professor at Technical Universities of Darmstadt (since 1973) and Dresden (since 1995), and Distinguished Professor at POSTECH, Korea (2007–2013). His research focused on condensed matter physics, superconductivity, and quantum many-body systems. Education: Studied physics at Humboldt University of Berlin, Göttingen, and Hamburg, with a doctorate from the University of Maryland (1963). He contributed to foundational work in electronic structure theory, superconductivity in thin films, and strongly correlated electron systems. Research interests included frustrated lattices, quantum phase transitions, and wavefunction-based methods for large systems. His articles explore topics like action function theory, high-field superconductivity, and spin-orbit interactions. Scientific honors include the Leibniz Medal (2006), Order of Merit of Saxony (2007), and multiple honorary professorships and citizenships in Korea. He served on committees of international scientific organizations, including the German Physical Society and the Korean Institute for Advanced Studies. His career included leadership roles at Max Planck Institutes and advisory positions for advanced research institutions in Germany and Korea. He co-founded the Max Planck Institute for Physics of Complex Systems and held presidencies in Asian-Pacific theoretical physics initiatives.

Titus NeupertView profile

Professor

• Condensed Matter Physics
• Quantum Materials
• Topological Insulators
• +5 more

Prof. Titus Neupert is a Professor of Condensed Matter Theory at the University of Zurich's Faculty of Science. He leads the research group on quantum materials with topological properties, focusing on topological insulators, superconductors, and machine learning applications in physics. He holds roles as Director of the Digital Society Initiative and Co-director of the Graduate Campus. His work is funded by an ERC Starting Grant and has earned awards like the Klung-Wilhelmy Science Award (2019). Education: PhD in Physics (ETH Zurich & Paul Scherrer Institute, 2013) Postdoc at Princeton University (2013–2016) MSc in Physics (University of Zurich, 2009) BSc in Physics (Dresden University of Technology, 2007) Research Interests: Quantum materials with topological properties, including exotic semiconductors, magnets, and superconductors. His group combines theoretical approaches like numerical simulations and machine learning to study topological phases and their experimental realizations. Key Contributions: Discovery of topological charge density waves in kagome metals Development of variational methods for quantum many-body problems Exploration of non-Hermitian topology and strain engineering in quantum materials Awards & Grants: ERC Starting Grant, Clarivate Highly Cited Researcher (2020–2024), Klung-Wilhelmy Science Award, and Swiss Physical Society Dissertation Prize. Advising & Teams: PhD advisees: Bastien Lapierre, Nikita Astrakhantsev, Martina Soldini, and others Postdocs: Maurizio Storni, Attila Szabó, and international collaborators Labs: Research Group for Condensed Matter Theory at UZH

Simon Elias SchraderView profile

Research Fellow

• Quantum Mechanics
• Numerical Methods
• Many-body Systems
• +4 more

Simon Elias Schrader is a Research Fellow and PhD candidate in the Department of Chemistry at the University of Oslo, affiliated with the Faculty of Mathematics and Natural Sciences. His research focuses on quantum mechanics, numerical methods for many-body systems, and applications in quantum computing and machine learning. He holds a Master’s degree in Computational Science: Chemistry from the University of Oslo, where he authored a thesis on Eigenvector Continuation in quantum chemistry. Education: Master’s in Computational Science: Chemistry, University of Oslo (Thesis: Eigenvector Continuation in Quantum Chemistry) Research Interests: Schrader’s work spans numerical solutions to the time-dependent Schrödinger equation, optimization techniques, and the integration of machine learning into quantum dynamics. He actively explores quantum computing frameworks and coupled cluster theory, aiming to advance computational methodologies in theoretical chemistry. Teaching: He has served as a teaching assistant for courses including KJM1101, KJM2601, KJM3310/KJM4310, KJM5600, and KJM5631 since 2022. Awards: 2022: Prize for the best Master’s thesis at the Department of Chemistry, University of Oslo Labs/Groups: Member of the Theoretical Chemistry research group at the Department of Chemistry.

Maurits W. HaverkortView profile

Professor

• Condensed Matter Physics
• Quantum Many-Body Systems
• X-ray Spectroscopy
• +4 more

Maurits W. Haverkort is a Professor at the Institute for Theoretical Physics of Heidelberg University, Germany. His research focuses on correlated electron systems, developing numerical methods such as the Quanty software package for quantum many-body simulations. He leads a group exploring spectroscopic techniques (XAS, RIXS) and dynamical properties of complex materials, with applications to transition metal compounds, topological insulators, and actinides. His work bridges theory and experiment, emphasizing predictive modeling of electronic, magnetic, and optical properties. Education details include postdoctoral research under Prof. Bernhard Keimer at the Max Planck Institute for Solid State Research. He has taught advanced courses on condensed matter theory and computational methods at Heidelberg University. Collaborations involve global institutions like the University of Saskatchewan and the SLAC National Accelerator Laboratory. Key research directions include: (1) Development of Quanty for solving many-body problems via second quantization; (2) Spectroscopic tools for bond covalency and 5f-electron counting in actinides; (3) Neutrino mass determination via electron capture studies in Ho-163; (4) Exploring spin-orbit coupling effects in topological materials. His group has pioneered femtometer-precision vibrational metrology and ultrafast laser-controlled quantum dynamics. Funding includes leadership roles in DFG Research Units FOR 2202 (ECHo experiment), FOR 1346 (LDA+DMFT methods), and EU projects like MetroMMC. His team manages computational resources on Heidelberg's bwForCluster, emphasizing high-performance computing for correlated systems.

Andreas Martin Läuchli HerzigView profile

Professor

• Quantum Many-Body Systems
• Condensed Matter Theory
• Quantum Simulators
• +2 more

Prof. Andreas Läuchli heads the Laboratory for Theoretical and Computational Physics at Paul Scherrer Institute and holds a full professorship in physics at École Polytechnique Fédérale de Lausanne (EPFL). Education: Ph.D. in Physics from ETH Zürich (2003) His research investigates emergent phenomena in strongly correlated quantum systems, spanning condensed matter physics, quantum simulators, and quantum field theories. Current efforts focus on numerical algorithm development for quantum many-body problems and nonequilibrium quantum dynamics. Collaborations bridge theoretical frameworks with experimental groups in quantum materials research. Laboratory develops advanced computational methods to identify new quantum phases and characterize spectral properties of interacting systems. Research impacts fundamental understanding of quantum magnetism, topological matter, and high-temperature superconductivity mechanisms.

David D. GamarnikView profile

Professor

• Discrete Probability
• Optimization and Algorithms
• Quantum Computing
• +3 more

David D. Gamarnik is a Professor of Operations Research at the MIT Sloan School of Management, affiliated with the Operations Research and Statistics Group. He holds a BA in Mathematics from New York University (1993) and a PhD in Operations Research from MIT (1998). Prior to joining MIT in 2005, he was a Research Staff Member at IBM T.J. Watson Research Center. His research focuses on discrete probability, optimization, quantum computing, machine learning, and stochastic processes. He serves as an Area Editor for Mathematics of Operations Research and has held editorial roles in journals such as Operations Research and Annals of Applied Probability . Education: Bachelor of Arts in Mathematics, New York University (1993) PhD in Operations Research, MIT (1998) His honors include the Erlang Prize, Best Publication Award from INFORMS’ Applied Probability Society, and recognition as a finalist for the Franz Edelman Prize. He is a Fellow of the Institute for Mathematical Statistics, Institute for Operations Research and Management Science, and the American Mathematical Society. His academic contributions span theoretical computing, algorithm design, and applications in healthcare (e.g., kidney exchange models). Recent work explores algorithmic barriers in optimization, quantum computing, and high-dimensional statistics.

• Condensed Matter Physics
• Quantum Gases
• Quantum Many-Body Systems
• +3 more

Ettore Vitali is a Professor in the Department of Physics at California State University, Fresno. He holds a Ph.D. in Physics from Università degli Studi di Milano (Italy). His research focuses on condensed matter physics, quantum gases, and computational methods, with expertise in quantum many-body systems and stochastic processes. **Education**: Ph.D., Università degli Studi di Milano, Italy. **Research Interests**: Dr. Vitali investigates superconductivity, ultracold atomic Fermi systems, and the application of quantum Monte Carlo simulations to study dynamical properties. His work addresses phenomena such as Fulde-Ferrell-Larkin-Ovchinnikov phases, metal-insulator transitions in Hubbard models, and the interplay between magnetic/charge orders in correlated electron systems. He also explores stochastic calculus and inverse problems in quantum systems. **Recent Research Trends**: His 2022–2023 work emphasizes quantum phase transitions in Hubbard models, superfluid phases in optical lattices, and computational validation of theoretical models. Notable themes include the role of spin-orbit coupling in cold atoms and the absence of superconductivity in 2D Hubbard systems. **Grants & Advising**: While advising details are unspecified, his computational focus suggests mentorship in theoretical and numerical physics projects. Collaboration opportunities may arise via his participation in initiatives like the Simons Collaboration on the Many-Electron Problem. **Labs/Teams**: He contributes to interdisciplinary efforts in quantum many-body physics, leveraging Fresno State’s computational resources and access to advanced simulation techniques.

Adrian FeiguinView profile

Professor

• Computational Condensed Matter Physics
• Quantum Transport
• Strongly Correlated Systems
• +4 more

Adrian Feiguin is a Professor in the Department of Physics at Northeastern University, Boston. His research focuses on computational condensed matter physics, particularly quantum mechanical systems with strong correlations. He explores topics such as quantum transport, exotic phases in cold atom systems, and topological quantum matter. His group also investigates quantum magnetism, spin-charge separation phenomena, and high-temperature superconductivity. Feiguin's work emphasizes developing advanced numerical methods like the Density Matrix Renormalization Group (DMRG) and GPU-accelerated simulations to tackle complex many-body problems. His research interests include: Time-dependent and non-equilibrium quantum dynamics Electronic and spin transport in mesoscopic systems Exotic phases in ultracold atomic gases Decoherence in quantum systems (e.g., N-V centers in diamond) Quantum magnetism in low dimensions Topological order and high-temperature superconductivity Recent work highlights advancements in ultrafast magnetism, quantum spintronics, and neural network approaches to quantum many-body systems. His publications explore novel phenomena like quasi-Fermi liquids, unconventional pairing states, and skyrmion-based spintronic devices. Feiguin has contributed to algorithmic innovations in GPU computing for atomistic spin dynamics simulations and machine learning applications in quantum physics. His research is supported through collaborations with experimental groups and computational infrastructure development. The Feiguin group is actively involved in theoretical modeling of novel materials and quantum systems, with an emphasis on bridging computational methods and experimental observations in extreme conditions (e.g., low temperatures, high magnetic fields).

• Quantum Computing
• Algorithm Design
• High Energy Physics
• +4 more

Tobias Hartung is an Associate Professor in Computer Science at Northeastern University London, affiliated with the CoMENS Faculty and the Computing and Information Systems department. He holds a PhD in Mathematics from King’s College London (2015) and a Diplom in Mathematics with a Physics minor from TU Dresden (2013). His academic positions prior to Northeastern included roles at King’s College London and the University of Bath. His research focuses on the intersection of functional analysis, mathematical physics, quantum computing, and algorithm design for high-energy physics simulations. He develops mathematical frameworks to design quantum and classical algorithms for overcoming computational bottlenecks in physics simulations, particularly lattice gauge theory and particle physics. Recent work emphasizes error mitigation in quantum computing, parametric quantum circuit expressivity, and lattice field computations using advanced numerical integration techniques. Teaching includes courses on discrete structures, algorithms, and quantum computing at Northeastern, the University of Bath, and King’s College London. His courses emphasize algorithmic foundations and mathematical rigor in computer science. Publications span quantum algorithms for particle track reconstruction, error mitigation strategies, and theoretical advancements in lattice field theory. Current research trends include applying quantum computing to solve problems in high-energy physics, optimizing quantum circuits, and addressing noise limitations in NISQ-era devices. No scientific awards are explicitly listed, but his work demonstrates significant contributions to quantum computing and mathematical physics. Grants and advising details are not provided in the source material. He is affiliated with Northeastern University London’s campus in Devon House, London.

• Quantum Physics
• Computational Physics
• Quantum Chemistry
• +3 more

Giuseppe Carleo is an Associate Professor at the École Polytechnique Fédérale de Lausanne (EPFL), affiliated with the School of Basic Sciences (SB) and the Institute of Physics (IPHYS). He leads the Numerical Quantum Sciences Lab (CQSL) and holds roles such as Co-directeur in STI-SSIQ and member of doctoral committees. His research focuses on computational quantum physics, quantum many-body systems, and machine learning applications in physics. He teaches courses like Advanced computational physics and Computational quantum physics . He supervises multiple PhD students and has contributed to over 50 publications, including studies on neural network quantum states and quantum dynamics. His work bridges theoretical physics with computational methods, addressing challenges in quantum chemistry and condensed matter systems. Education: PhD in Theory and Numerical Simulation of Condensed Matter from SISSA, Trieste (2007-2011). His research interests emphasize leveraging machine learning and numerical techniques to solve complex quantum problems. He actively contributes to the development of open-source tools like NetKet for quantum system simulations.

Stefan M. WildView profile

Adjunct Professor

• Numerical Optimization
• Machine Learning
• Scientific Computing
• +3 more

Stefan M. Wild serves as Director of the Applied Mathematics and Computational Research (AMCR) Division and Senior Scientist at Lawrence Berkeley National Laboratory, while holding an adjunct faculty position in the Industrial Engineering and Management Sciences (IEMS) department at Northwestern University's McCormick School of Engineering. He also serves as a Senior Fellow at NAISE (Northwestern Initiative for AI and Society). Dr. Wild earned his Ph.D. and M.S. in Operations Research from Cornell University (2009, 2007) and his M.S. and B.S. in Applied Mathematics from the University of Colorado, Boulder (2003, 2002). His academic journey includes an Argonne Director's Postdoctoral Fellowship (2008-2010) and the DOE Computational Science Graduate Fellowship (2005-2008). His research program focuses on developing numerical optimization and automated learning algorithms for challenging science and engineering problems at interfaces involving computer simulations, complex data, and physical experiments. Dr. Wild leads multiple community software projects including BAND, parMOO, libEnsemble, deepHyper, NUCLEI, POptUS, and surmise, with applications spanning nuclear physics, materials science, and astrophysics. His work bridges derivative-free optimization, uncertainty quantification, high-performance computing, and scientific machine learning. Dr. Wild has advised numerous postdocs who have established successful careers at national laboratories and academic institutions. His editorial responsibilities include Mathematical Programming Computation, INFORMS Journal on Computing, Data Science in Science, and SIAM Review. U.S. Department of Energy Early Career Research Award (2020) STS Forum Future Leader (2018) IDC HPC Innovation Excellence Award (2015) SIAM SIGEST Award (2014) Strategic Laboratory Leadership Program (UChicago Booth School) (2013) DOE Computational Science Graduate Fellowship (2005-2008) As AMCR Division Director, he leads a diverse team of applied mathematicians, computational scientists, and software engineers addressing some of the world's most challenging computational problems across scientific and engineering disciplines. His leadership emphasizes both technical excellence and commitment to inclusion, diversity, equity, and accountability in scientific research.

Siu Ah ChinView profile

Professor

• Nuclear Physics
• Quantum Physics
• Computational Physics
• +3 more

Professor Siu Ah Chin is a faculty member in the Department of Physics and Astronomy at Texas A&M University. He holds a B.S. from MIT (1971) and a Ph.D. from Stanford University (1975). His research focuses on nuclear and subnuclear high-density matter, quantum many-body problems, Bose-Einstein condensates, and quantum Monte Carlo algorithms. He joined Texas A&M in 1984 after roles at the University of Illinois, MIT, and as an adjunct assistant professor at UCLA. His work explores topics like rogue wave dynamics on periodic backgrounds, computational methods for quantum systems, and symplectic algorithms. Notably, he is a Fellow of the American Physical Society (2006). His recent publications address nonlinear Schrödinger equation solutions and numerical methods for particle dynamics.

Jose Antonio Carrillo De La PlataView profile

Professor

• Analysis of Partial Differential Equations
• Mathematical Biology
• Nonlinear Diffusion Equations
• +3 more

Jose Antonio Carrillo De La Plata is a Professor of the Analysis of Nonlinear Partial Differential Equations at the Mathematical Institute, University of Oxford, and a Tutorial Fellow in Applied Mathematics at The Queen’s College. He holds an ERC Advanced Grant and is a SIAM Fellow, IMA Fellow, and member of the European Academy of Sciences. His academic career spans institutions including Imperial College London, Universitat Autònoma de Barcelona, and Universidad de Granada. PhD in Mathematics, University of Granada (1996) His research focuses on partial differential equations (PDEs) with applications to mathematical biology, nonlinear diffusion, hydrodynamic models, kinetic equations, and many-body systems. He has pioneered analysis of nonlocal interaction equations, aggregation-diffusion models, and optimal transport methods. Key publication trends include nonlinear PDEs for complex particle dynamics, pattern formation, synchronization, and biological systems. His work spans theoretical analysis, numerical schemes, and applied modeling. Echegaray Medal (2022) Foreign Member of the Royal Academy of Sciences of Spain (2021) ERC Advanced Grant (2020) Wolfson Research Merit Award (2012-2017) Richard von Mises Prize (2006) SEMA Young Researcher Prize (2003) He has supervised PhD students at Imperial College London (2016 SACA Award) and collaborated on grants including the ERC Advanced Grant. His visiting roles span IPAM, MSRI, and institutions in Singapore, China, France, and the US.