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Greis Julieth Kim ReyesView profile

Assistant Professor

• Computational Materials Science
• Density Functional Theory
• Machine Learning in Materials Science
• +5 more

Dr. Greis Julieth Kim Reyes serves as Assistant Professor of Physics in the Department of Physics and Astronomy at SUNY New Paltz, where she conducts computational research on semiconductor materials and defects. Her work bridges theoretical physics and practical materials design for energy applications. Her educational journey includes a Ph.D. in Physics from University at Buffalo (2024), Master's in Physics from Universidad Nacional de Colombia (2014), and Bachelor's in Physics-Education from Universidad Distrital Francisco José de Caldas (2010). This international background informs her interdisciplinary approach to materials science. Dr. Reyes specializes in computational exploration of intermediate band semiconductors, defect engineering, and magnetic materials using density functional theory (DFT) and machine learning. Her research reveals how atomic-scale defects create novel electronic properties, particularly in 2D materials like C 3 N/C 3 B bilayers and perovskite oxides. She employs iterative Kohn-Sham methods to simulate electronic behavior and optical responses, with recent work focusing on excitonic effects for solar energy applications. Analysis of her 15 most recent publications shows consistent emphasis on computational discovery of materials with tailored optical and electronic properties. Key trends include defect-enabled photocatalysis, interlayer exciton engineering in van der Waals heterostructures, and Jahn-Teller effects in doped semiconductors - all targeting next-generation energy technologies. Her scholarly recognition includes: Bahethi Scholarship (SUNY Buffalo, 2022) Silvestro Scholarship (SUNY Buffalo, 2022) Marshall Plan Foundation grant (Johannes Keppler Universität, 2018) As an educator, Dr. Reyes develops interactive quantum mechanics curricula using Mathematica simulations, as evidenced by her GitHub repository. She teaches General Physics and Quantum Physics courses while integrating computational tools to build student intuition for quantum materials. Though specific research students aren't listed, her teaching philosophy emphasizes critical thinking through problem-solving sessions and real-world applications. Her computational laboratory work focuses on first-principles simulations of materials, with active development of educational resources for quantum mechanics instruction. Current projects explore machine learning pipelines for materials discovery and defect-property relationships in emerging semiconductor systems.

• Materials Science
• Computational Chemistry
• Density Functional Theory
• +3 more

Michael Herbst is an Assistant Professor (tenure-track) at EPFL, holding a joint appointment in the School of Basic Sciences (SB) and the School of Engineering (STI). He leads the Mathematics for Materials Modelling (MatMat) research group, focusing on error control in atomistic simulations, density-functional theory (DFT), and interdisciplinary computational methods. His work bridges mathematics, materials science, and computer science, emphasizing robust algorithms and Julia-based software development. Herbst holds a PhD from Heidelberg University and has held postdoctoral positions at RWTH Aachen and Inria Paris. He is a core member of the MARVEL and CESMIX research centers. Education: 2018: Dr. rer. nat. (magna cum laude), Heidelberg University 2009–2013: BA and MSci (1st class) in Natural Sciences, University of Cambridge 2008–2009: Studies in Mathematics/Physics, TU Kaiserslautern Research Interests : Herbst's research centers on developing reliable computational methods for materials modeling, including error estimation in DFT, black-box SCF algorithms, and Julia-based tools like the Density-Functional Toolkit (DFTK). His work addresses challenges in high-throughput simulations, numerical stability, and interdisciplinary collaboration across mathematics, physics, and computer science. Grants & Projects : MARVEL Center for Computational Design (EPFL) CESMIX Center for Extreme-Scale Simulations (MIT) EMC² Project (Sorbonne/Inria/École des Ponts) Awards : HGS MathComp PostDoc Fellowship (2018–2021) DAAD Travel Funding (2018) Exploratory Research Space Fund (RWTH Aachen, 2022) Labs & Teams : Head of the MatMat group at EPFL, focusing on error-controlled simulations and open-source software development.

Zhen LiView profile

Assistant Professor

• Multiscale/Multiphysics modeling
• Soft matter and Smart materials
• Biophysics and Collective dynamics
• +7 more

Dr. Zhen Li is an Assistant Professor in the Department of Mechanical Engineering at Clemson University's College of Engineering, Computing and Applied Sciences. He joined Clemson in August 2019 after serving as a research associate professor at Brown University and a postdoctoral research associate at University of California, Merced. Education: Ph.D. in Fluid Mechanics, Shanghai University, 2012 MS in Fluid Mechanics, Shanghai University, 2008 BS in Engineering Mechanics, Wuhan University, 2005 Dr. Li's research focuses on multiscale modeling of soft matter, complex fluids, biophysics, and collective dynamics using both bottom-up (coarse-grained molecular modeling) and top-down (from continuum descriptions to fluctuating hydrodynamics) approaches, along with high-performance computing. His work spans mathematical theory for coarse-graining and model reduction, statistical methods and machine-learning approaches applied to multiscale modeling, memory effects in complex fluids, and concurrent coupling of heterogeneous solvers for scale-bridging. Analysis of Dr. Li's recent publications reveals a strong trend toward integrating machine learning with traditional computational methods, particularly neural operators for multiscale problems. His work spans diverse applications from bubble dynamics and blood flow to materials science and bioprinting, demonstrating the versatility of his computational approaches across multiple disciplines in engineering and physics. Awards and Recognition: CECAS Dean's Professor Award (2024) Award of Excellence - Junior Faculty (2021-2022) Best Research Poster Award at SC19 (2019) 2nd Place Award of Best Poster Presentation at DOE/EFRC AIM for Composites meeting (2024) Dr. Li actively mentors PhD students including Miles Lu, Ryan Wan, Haizhou Wen, and Ali Mohammadi, who have published significant research in computational mechanics. His research is supported by multiple grants including an NSF Elements grant as PI for 'SciMem: Enabling High Performance Multi-Scale Simulation on Big Memory Platforms', an NSF CDS&E grant as co-PI for 'HAM3R: Heterogeneous Automated Management of Multiscale Methods and Resources', a DOE/EFRC grant as Thrust lead co-PI for 'AIM for Composites', and a NASA EPSCoR grant as Science-PI. Dr. Li leads the MuthComp (Multiscale theory and Computation) research group, which focuses on developing interfaces between Engineering, Applied Mathematics, Physics-based Machine Learning, and High Performance Scientific Computing. The group has active collaborations with institutions including Idaho National Laboratory, University of Tokyo, and Brown University, and has developed open-source software including USERMESO for GPU-accelerated DPD simulations.

Yoram AlhassidView profile

Professor

• Theoretical Nuclear Physics
• Many-Body Quantum Systems
• Nuclear Many-Body Problem
• +15 more

Yoram Alhassid is the Frederick Phineas Rose Professor of Physics in the Department of Physics at Yale University, where he leads a research group focused on theoretical nuclear and many-body physics. His work bridges nuclear physics, mesoscopic systems, and ultracold atomic gases, using advanced computational methods such as quantum Monte Carlo and the configuration-interaction shell model. His research interests include the nuclear many-body problem, femtoscience and nanoscience (nuclei, quantum dots, nanoparticles), and cold atomic Fermi gases. He has developed and applied the shell model Monte Carlo (SMMC) method to study statistical and collective properties of nuclei, such as level densities, deformation, and pairing correlations. He has extended these methods to study cold Fermi gases, particularly in the unitary regime, where he has investigated pseudogap phenomena, heat capacity, and pairing gaps. The recent publications highlight a strong focus on nuclear level densities, γ-ray strength functions, deformation effects, and quantum Monte Carlo methodologies. There is a clear trend toward microscopic, ab initio calculations of nuclear and many-body properties, with increasing attention to odd-mass and deformed nuclei, as well as the interplay between pairing and collective phenomena. Scientific Awards: Frederick Phineas Rose Professor of Physics Alhassid advises students and postdoctoral researchers, as evidenced by numerous co-authored publications. His group has developed advanced computational tools and codes (e.g., HF-SHELL) for finite-temperature mean-field and shell model calculations. The research is supported by high-performance computing and has implications for nuclear astrophysics, radioactive beam facilities, and quantum simulation with cold atoms. His lab focuses on theoretical and computational modeling of finite-size quantum many-body systems, with close collaborations across nuclear theory, condensed matter, and atomic physics. The group emphasizes method development, benchmarking against mean-field theories, and extracting model-independent signatures of physical phenomena such as deformation and pairing.

• Partial Differential Equations
• Quantum Physics
• Mathematical Physics
• +3 more

Norbert J. Mauser is a Professor of Mathematics at the University of Vienna 's Faculty of Mathematics. He serves as Director of the Wolfgang Pauli Institute and Co-Director of the Jungen Kurie at the Austrian Academy of Sciences. Mauser coordinates major EU projects like HYKE and DEASE , focusing on hyperbolic and kinetic equations, differential equations, and their applications in science and engineering. Research Interests : Mauser specializes in Partial Differential Equations (PDEs) , particularly Nonlinear Schrödinger Equations (NLS) , with applications in Quantum Physics and Computational Materials Science . His work spans mathematical modeling , numerical methods , and asymptotic analysis , addressing problems in micromagnetism , quantum correlation , and nonrelativistic limits . He explores Wigner transforms , stochastic NLS , and multi-configuration Hartree-Fock equations for quantum systems. Scientific Contributions : Grants & Projects : Principal Investigator for START Award , FWF , WWTF , and ANR-FWF projects on quantum dynamics, correlation, and nano-sensors. Collaborations : Active in international networks including CNRS Groupement de Recherche on kinetic equations and quantum physics. Publishing : Senior editor for journals like Asymptotic Analysis and Communications in Mathematical Sciences . Labs & Teams : Leads projects under Vienna Computational Materials Laboratory (ViCoM) and contributes to multi-scale modeling of nano-biosensors. His research integrates computational methods with theoretical physics, emphasizing quantum systems and nonlinear PDEs.

Gustavo ScuseriaView profile

Professor

• Computational Quantum Chemistry
• Electronic Structure Theory
• Strong Correlation
• +8 more

Gustavo Scuseria is the Robert A. Welch Professor of Chemistry, Professor of Physics and Astronomy, and Professor of Materials Science and NanoEngineering at Rice University . He is a leading figure in computational quantum chemistry , with seminal contributions to electronic structure theory , coupled cluster methods , and density functional theory (DFT) functionals like HSE and PBE0. His research spans strong correlation , symmetry-projection techniques , and quantum computing applications . Education: PhD in Physics (1983) from University of Buenos Aires Research: Pioneered linear scaling quantum methods , developed HSE functional for semiconductor band gaps, and advanced symmetry-projected wave function approaches Awards: Feynman Prize in Nanotechnology, Humboldt Research Award, Guggenheim Fellowship, and multiple Fellowships from ACS, APS, and RSC Software Contributions: Key developer of Gaussian suite and TURBOMOLE implementations His recent publications focus on symmetry-projected methods for spin systems, dualities in electron correlation , and quantum computing applications . Collaborations with institutions like Los Alamos National Laboratory and Max-Planck Institute have shaped his interdisciplinary approach. Scuseria's work remains foundational for quantum chemistry software and materials science research.

David LuitzView profile

Professor

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

David Luitz is a Professor of Theoretical Physics at Bonn University, specializing in quantum many-body systems. His research focuses on fundamental aspects of quantum dynamics, including many-body localization, quantum information spreading, and non-equilibrium thermodynamics. He develops advanced numerical methods and software tools such as the DanceQ library to tackle complex many-body problems. His work bridges theoretical physics with computational techniques, addressing topics like entanglement entropy, out-of-time-order correlators, and phase transitions in interacting quantum systems. Key research areas include the interplay between disorder and thermalization, quantum chaos, and the application of quantum Monte Carlo methods to study correlated electron systems. His contributions have advanced understanding of eigenstate thermalization, dissipative dynamics, and topological phenomena in condensed matter systems. Dr. Luitz’s publications highlight innovations in numerical algorithms for many-body systems and experimental predictions for quantum phase transitions. His work often explores the boundaries between localized and thermalizing regimes, with applications to both theoretical and computational physics.

H. Metin AktulgaView profile

Associate Professor

• High Performance Computing
• Parallel Computing
• Big Data Analytics
• +3 more

H. Metin Aktulga is an Associate Professor in the Department of Computer Science and Engineering at Michigan State University's College of Engineering. His research focuses on high-performance computing, parallel algorithms, and numerical methods for large-scale scientific applications. He leads interdisciplinary projects involving collaborations with computational physicists and materials scientists to develop scalable software systems. His work includes the development of PuReMD, a reactive molecular dynamics code, and DOoC+LAF, a task-based middleware for data analytics. He explores parallel computing on emerging architectures, emphasizing energy efficiency and performance optimization. His research spans applications in molecular modeling, nuclear physics, and computational biology. Awards and grants are not explicitly listed, but his contributions are highlighted through collaborations with projects like MFDn (nuclear structure) and SHINES (electronic structure computations). He advises students in computational methods and leads efforts to automate force field optimization using machine learning and big data analytics. Labs and teams include the High-Performance Computing group at MSU, with active participation in interdisciplinary initiatives to bridge simulation and data-driven discovery in materials science and quantum systems.

• Numerical Analysis
• Applied Mathematics
• Scientific Computing
• +4 more

Virginie Ehrlacher is a Professor at CERMICS, École des Ponts ParisTech (ENPC), France. She specializes in applied mathematics with a focus on high-dimensional problems, numerical analysis, and computational modeling. Her work bridges quantum chemistry, materials science, and machine learning through innovative mathematical frameworks. Education includes: PhD in Mathematics (2012) from ENPC: Mathematical models in quantum chemistry and uncertainty quantification Habilitation (2020) from Université Paris-Dauphine: Mathematical and numerical analysis of high-dimensional and multiscale problems in materials science Research spans multiscale modeling, tensor decompositions for high-dimensional systems, cross-diffusion equations, and scientific machine learning. Her work frequently addresses challenges in quantum mechanics, materials science, and computational physics using advanced numerical techniques. Publications emphasize: Algorithms for high-dimensional PDEs and eigenvalue problems Model reduction techniques (tensor networks, reduced basis methods) Cross-diffusion systems with biological/physical applications Neural networks for scientific computing Awards and distinctions: Irène Joliot-Curie Prize (2023) Chevalier de l’Ordre National du Mérite (2025) Leadership includes: ERC Starting Grant HighLEAP (2023–2028) ERC Synergy project EMC2 (2020–2026) ANR JCJC project COMODO (2019–2023) She co-leads the EMS Topical Activity Group on Scientific Machine Learning. Affiliated with the CERMICS laboratory, she collaborates on interdisciplinary teams tackling multiscale and data-driven modeling challenges.

Anna Dall'AcquaView profile

Professor

• Partial Differential Equations
• Calculus of Variations
• Geometric Analysis
• +5 more

Prof. Dr. Anna Dall'Acqua holds a position as University Professor (Univ.-Prof.) at the Institute for Applied Analysis, Universität Ulm. Her research focuses on partial differential equations, calculus of variations, geometric analysis, and mathematical physics, with specific interests in higher-order elliptic problems, elastic curves, Willmore surfaces, and Hartree-Fock theory. She leads a research group and has supervised doctoral students including Gabriel Knöbl and Manuel Schlierf. Her work is supported by grants from the German Research Foundation (DFG) and Taiwan’s MoST. Recent research includes studies on elastic networks, Willmore flow of tori, and obstacle problems in elasticity. She teaches advanced courses such as Functional Analysis, Calculus of Variations, and Analysis series at the university. Prof. Dall'Acqua’s publications span over two decades, with contributions to journals like Calc. Var. PDEs , Journal of Differential Equations , and Analysis & PDE . Her habilitation thesis (2011) and earlier work on boundary value problems and pseudorelativistic Hartree-Fock systems highlight her interdisciplinary expertise.

Mark IwenView profile

Professor

• Computational Harmonic Analysis
• Mathematical Data Science
• Signal Processing
• +12 more

Mark Iwen is a Full Professor with a dual appointment in the Department of Mathematics and the Department of Computational Mathematics, Science and Engineering (CMSE) at Michigan State University. His research bridges theoretical mathematics and computational science, focusing on high-dimensional data analysis, signal processing, and numerical algorithms. Research Interests: His work centers on computational harmonic analysis, mathematical data science, and algorithms for large-scale data. Key areas include sparse spectral methods, phase retrieval, tensor decomposition, compressive sensing, sublinear-time algorithms, and Johnson-Lindenstrauss embeddings. He develops provably accurate and efficient algorithms for problems in high dimensions, such as solving PDEs, function approximation, and manifold learning. Publications and Trends: His recent publications (2023–2025) emphasize sparse and low-rank tensor methods, phase retrieval, and high-dimensional PDE solvers. There is a strong focus on algorithmic efficiency, provable guarantees, and applications in imaging and data science. Many works involve collaborative efforts and include open-source code. Scientific Awards: Scholarship established in honor of Benjamin (Ben) Segal, reflecting his mentorship and academic impact Advising and Grants: He advises numerous students, including undergraduates and graduate researchers, many of whom are co-authors on publications and code repositories. While specific grants are not listed, his sustained research output and collaborative projects suggest active funding. He co-founded the One World MINDS Seminar, demonstrating leadership in the academic community. Labs and Teams: He leads a research group focused on algorithm development for high-dimensional problems, with strong ties to computational mathematics and data science. His team develops and shares code for sparse FFTs, phase retrieval, tensor methods, and PDE solvers, indicating a collaborative and open research culture.

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

Casey E. Berger is an Assistant Professor of Physics at Bates College, affiliated with the Department of Physics and Astronomy. Their research focuses on quantum many-body systems, computational physics, and theoretical frameworks addressing challenges like the sign problem in quantum simulations. Berger employs advanced methods such as complex Langevin dynamics, Monte Carlo techniques, and machine learning to explore phenomena in rotating quantum matter, lattice field theories on curved manifolds, and quantum technologies for climate science. Key research areas include the development of numerical approaches to tackle sign problems in fermionic systems, the study of virial expansions in trapped fermions, and the application of quantum computing to environmental challenges. Their work bridges theoretical physics with computational innovation, emphasizing interdisciplinary solutions to fundamental problems in quantum mechanics and statistical physics. Berger’s publications span topics from quantum counter-terms in curved spacetime to the thermodynamics of rotating matter, reflecting a commitment to advancing both foundational and applied aspects of physics. Their research contributes to the broader goals of simulating complex quantum systems and leveraging quantum technologies for societal applications.

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.

• Quantum Computing
• Quantum Physics
• Atomic Physics
• +7 more

Servaas JJMF Kokkelmans is a full Professor at Eindhoven University of Technology (TU/e), where he leads the Coherence and Quantum Technology group within the Department of Applied Physics and Science Education. He serves as scientific director of the Center for Quantum Materials and Technology Eindhoven (QT/e), which he founded in 2018, and is a co-founder of the Eindhoven Hendrik Casimir Institute established in 2021. Kokkelmans also coordinates action line 1: Research and Innovation at Quantum Delta NL, demonstrating his national leadership in quantum technology. Professor Kokkelmans earned his MSc in Physics from TU/e in 1996 and completed his PhD on interacting atoms in clocks and condensates in 2000. Following postdoctoral research at JILA, University of Colorado (USA) and Laboratoire Kastler Brossel, ENS (France), he returned to TU/e in 2004 as an Assistant Professor, became Associate Professor in 2017, and was promoted to full Professor in 2023. His research focuses on strongly-interacting quantum gases and neutral atom quantum computing, with particular expertise in manipulating interatomic interactions. Kokkelmans' work impacts quantum materials development, quantum computing, and fundamental understanding of superfluidity. His expertise spans many-body properties of Fermi and Bose gases, ultracold collisions, Feshbach resonances, ultracold molecules, Efimov trimers, ultracold plasmas, and Rydberg atoms. Analysis of his recent publications reveals a strong progression from fundamental quantum gas studies to practical quantum computing implementations, with increasing emphasis on optical tweezer arrays, Rydberg atom systems, and hybrid quantum architectures. Professor Kokkelmans has received numerous prestigious awards: NWO Vici Award: 'From neutron star to quantum computer' (2015) NWO Vidi Award: 'Atomic gases with strong interactions' (2003) Teacher Award of Appreciation Applied Physics (2021) Visiting Scientist Fellowship JILA (2016) Eindhoven University of Technology Fund for Excellence (2010) As principal investigator of the KAT-1 project 'Rydberg Atom Quantum Computing' (2020-2028), Kokkelmans leads a major research initiative in neutral atom quantum computing. His research group has secured substantial funding from NWO and university sources, supporting numerous PhD students and postdoctoral researchers. His educational contributions include teaching 'Hybrid quantum computing,' 'Quantum Optics and Quantum Information,' and 'Ultracold quantum physics' courses. Professor Kokkelmans founded the Center for Quantum Materials and Technology Eindhoven (QT/e) as a hub for quantum research at TU/e. His Coherence and Quantum Technology group combines experimental and theoretical approaches to quantum systems, with particular strength in ultracold atomic physics. The group's work bridges fundamental quantum phenomena with practical quantum technology applications, positioning TU/e as a significant player in the global quantum computing landscape.

• Condensed Matter Physics
• Theoretical Physics
• Quantum Materials
• +7 more

Rafael Fernandes is a Professor in the Department of Physics at the University of Illinois Urbana-Champaign, where he joined in 2024 after serving as a Distinguished McKnight University Professor at the University of Minnesota (2023-2024). His academic journey includes positions as Professor (2021-2024), Associate Professor (2017-2021), and Assistant Professor (2012-2017) at the University of Minnesota, following postdoctoral appointments at Columbia University/Los Alamos National Lab (2011-2012) and Ames Laboratory/Iowa State University (2008-2011). His educational background includes: B.S. in Physics from the University of Campinas, Brazil (2003) M.Sc. in Physics from the University of Campinas, Brazil (2005) Ph.D. in Physics from the University of Campinas, Brazil (2008) Professor Fernandes is a leading condensed matter physics theorist renowned for his work on electronic nematicity and vestigial electronic order in quantum materials. His research focuses on establishing clear relationships between microscopic electron behavior and macroscopic material properties through theoretical modeling of quantum many-body systems. He investigates model quantum materials to develop frameworks applicable to broader problems in interacting quantum matter, with notable contributions to understanding nematicity in iron pnictides and its extension to vestigial phases in diverse systems. His current research interests span electronic nematicity, altermagnetism, intertwined electronic phases, unconventional charge-order in kagome materials, electron-phason coupling in moiré systems, and multi-component superconductivity. His publication record reveals a strategic evolution from foundational work on iron-based superconductors toward cutting-edge research on altermagnetism, moiré systems, and kagome metals. The articles demonstrate a consistent methodological approach combining analytical field-theory techniques with numerical quantum Monte Carlo simulations to address phase transitions, electronic order parameters, and competing electronic orders in quantum materials. His scientific achievements have been recognized with prestigious awards: Mercator Fellow, DFG, Germany (2020-present) Fellow, American Physical Society (2017) Cottrell Scholar Award (2016-2019) DOE Early Career Award (2014-2019) Professor Fernandes teaches courses including PHYS 211 - University Physics: Mechanics and maintains extensive collaborations with experimental groups utilizing scanning tunneling microscopy, angle-resolved photoemission spectroscopy, nuclear magnetic resonance, and various scattering techniques. His theoretical work bridges fundamental quantum mechanics with practical material properties, incorporating realistic crystal elastic properties into models of quantum materials. His research group at UIUC investigates the fundamental physics of quantum materials through theoretical frameworks that connect microscopic quantum behavior to observable macroscopic phenomena, with particular emphasis on developing predictive models for novel electronic phases and phase transitions.