| • 2023-12-21 Jake Harmon (T-5/CNLS) (RESCHEDULED) Active Discretizations for Uncertainty Quantification: Method and Benchmarks |
| • 2023-12-19 (University of Illinois Urbana-Champaign - Electrical and Computer Engineering ) Trustworthy AI with Scalable Formal Verification: A Linear Bound Propagation Approach |
| • 2023-12-18 Subekshya Bidari (Columbia University) Modeling long term transmission of measles using a household- and age-structured model |
| • 2023-12-14 Samindranath Mitra (American Physical Society) (CANCELED) Your Physics Results in PRL |
| • 2023-12-14 Dr. Jason Pereira (Istituto Nazionale di Fisica Nucleare (INFN) ) (Virtual) Generalization in Quantum Machine Learning of Quantum Data |
| • 2023-12-07 Nikita Fedik (T-1/CNLS) Palette of Computational Chemistry: Research Stories about Quantum Chemistry, Active Learning and Differentiable Models |
| • 2023-12-04 Jacob Spainhour (CU Boulder) Applications of Numerical Optimization and Computational Geometry |
| • 2023-11-30 Alice Allen (T-1/CNLS) (Virtual) Improving Atomistic Simulations with Machine Learning |
| • 2023-11-16 Robert Brunato Parker (A-1/CNLS) Pre-solve reductions for nonlinear optimization |
| • 2023-11-13 Peter Hatton (MST-8, LANL) Exploiting High Performance Computing Resources to Drive Time-Parallelized Molecular Dynamics in a GPU-Dominated World |
| • 2023-11-09 Snehasish Nandy (T-4/CNLS) Third-order Hall effect in the surface states of a topological insulator (Edited) |
| • 2023-11-07 Spencer Fox (University of Georgia) Actionable modeling of outbreaks for public health |
| • 2023-11-06 Oliver Krzysik (University of Waterloo) High performance time integration for partial differential equations with strong advection |
| • 2023-11-06 Paul Rodriguez (Pontificia Universidad Catolica del Peru) Stochastic gradient descent (SGD): a unified algorithmic overview |
| • 2023-11-02 Fumika Suzuki (T-4/CNLS) Kibble-Zurek mechanism in weakly first order phase transition |
| • 2023-11-02 Bozo Vazic (EES-17) Adaptation of Generalized Continua for Shock Loading of Geomaterials |
| • 2023-11-01 Alexandre Tuel (Geolabe, LLC) Some perspectives on the use of deep learning for satellite data analysis |
| • 2023-11-01 Pablo Laguna (The University of Texas at Austin) Two Black Holes Stories from Numerical Relativity |
| • 2023-10-30 Joshua Schrier, Fordham University (Fordham University) Three Stories about Machine Learning and Materials: Solids, Liquids, and Exceptions |
| • 2023-10-26 Cody D. Schimming (T-4/CNLS) Vortex lattices in active nematic liquid crystals induced by a periodic obstacle array |
| • 2023-10-24 Alexandra Baumgart (Caltech ) Simulating detonations in a spatially-filtered framework with tabulated chemistry |
| • 2023-10-24 Rae Corrigan Grove, PhD (University of Iowa) Implicit Solvents for Molecular Applications |
| • 2023-10-19 Shane X. Coffing (CCS-2) Calibrating and optimizing operator terms via a neural Galerkin Projection on the Shallow Water Equations |
| • 2023-10-16 Jingwei Hu (University of Washington) Structure-Preserving Particle Method for the Vlasov-Landau-Maxwell Equation |
| • 2023-10-13 Madhav Marathe (University of Virginia) Computational bio-social complexity science |
| • 2023-10-12 James Brunner (B-IOME/CNLS) Inferring microbial interactions with their environment from genomic and metagenomic data |
| • 2023-10-05 Matthew Wilson (CCS-7) Magnetic Orderings in a Frustrated Ising Model for FeI2 |
| • 2023-10-04 Mathias Oster (RWTH AACHEN) Block Sparse Tensor Trains for Polynomials |
| • 2023-09-28 Martin Larocca (T-4/CNLS) Geometric Quantum Machine Learning |
| • 2023-09-25 Jian-Xin Zhu (LANL T-4) The Quick Rise and Fall of LK-99 as a Room-Temperature Superconductor |
| • 2023-09-21 Parikshit Pareek (T-5) Closed-form Power Flow Learning: Putting Intuition into Gaussian Process [Edited] |
| • 2023-09-14 Abhijith Jayakumar (T-5/CNLS) Graphical model learning with applications to analogue quantum computers. |
| • 2023-09-14 Charlie Young (LANL, T-1) Theory-informed approaches for computational modeling of soft matter |
| • 2023-09-14 Dr. Jake Buzhardt Controlled density transport in nonlinear systems with applications in Stokes flows and uncertain control systems |
| • 2023-09-11 DR. HIMANSHU SINGH, PHD PROVABLE CONVERGENCE PHENOMENA IN DYNAMICAL SYSTEMS |
| • 2023-09-07 Michael Saccone (T-4/CNLS) Complex field-reversal dynamics in nanomagnetic systems |
| • 2023-09-07 Jesse Bloom (Professor Fred Hutchinson Cancer Research Center; Investigator Howard Hughes Medical Institute) Using deep mutational scanning to interpret and forecast viral evolution |
| • 2023-09-05 Mario Ortega, Duc Truong and Boian Alexandrov Tensor Networks for Solving Realistic Time-independent Boltzmann Neutron Transport Equation |
| • 2023-08-31 Weitang Liu (CCS-7) Toward Human-Like Models |
| • 2023-08-29 Steve Fitzgerald (Department of Applied Mathematics, University of Leeds, UK) Path integral formulation of stochastic processes: non-equilibrium reaction pathways, hyperdynamics, and enhanced sampling |
| • 2023-08-28 Christoph Junghans CNLS - Meet a Scientist |
| • 2023-08-24 Alessandro Gabbana (Eindhoven University of Technology, The Netherlands) Physics constrained neural networks for learning a lattice Boltzmann collisional operator |
| • 2023-08-17 Saif Kazi (T-5/CNLS) Stochastic Finite Volume Method for Uncertainty Management in Energy Grid Networks |
| • 2023-08-14 Nathan Debardeleben (HPC-DES, LANL) A Selection of AI/ML Interests of the ASC Program |
| • 2023-08-10 Jacob Helwig (EES-17 / Department of Computer Science & Engineering, Texas A&M University) Applied Machine Learning Summer School Student Seminar: Towards High-Fidelity Data-Driven Solutions of the Helmholtz Equation for Full Waveform Inversion |
| • 2023-08-10 Carlos Mora Perez (T-1/CNLS) Unleashing HIP-NN on Chiral Mysteries: A Machine Learning Odyssey in Chirality and Spectral Predictions |
| • 2023-08-10 Siddharth Mansingh (CCS-3/CNLS) Are energy-based models trained with equilibrium propagation robust learners? |
| • 2023-08-10 Sayanton Dibbo (A-4/CNLS) Robust Audio Classification Using Multi-layer Neural Networks with Lateral Competition |
| • 2023-08-10 Agnese Marcato (EES-16/CNLS) Improving Sensor Placement for Enhanced Field Reconstruction: A Machine Learning Differentiable Workflow |
| • 2023-08-10 Sundaramoorthy Santhoshkumar (T-CNLS) Theoretical Study on f and d orbital participation in actinide materials through topotactic Li-insertion |
| • 2023-08-10 Michael Clark (T-4/CNLS) Unveiling the Potential: Unleashing the Power of Purcell Enhancement at Telecom Wavelengths |
| • 2023-08-10 Adam Stanier (Los Alamos National Laboratory -- T-5) Magnetic Reconnection: An explosive plasma phenomenon throughout the universe |
| • 2023-08-07 Raymundo Arroyave (Texas A&M University) Accelerated Alloy Discovery and Optimization through the Batch-wise Improvement in Reduced Design Space using a Holistic Optimization Technique (BIRDSHOT) |
| • 2023-08-07 Lucas Blakeslee (Princeton University and LANL Scholar - Summer Student (XCP-4)) Numerical Analysis Seminar - Reconstruction of Planar Bodies Using Geometric Moments |
| • 2023-08-03 Aidan Nakhleh (T-CNLS) Shock Interaction Effects on the Supernova Light Curve |
| • 2023-08-03 Andre Luiz Paes de Lima (T-5/CNLS) Optimal Matter-Wave Splitting Under Experimental Inhomogeneities: an Ensemble Control Approach |
| • 2023-08-03 Aleksei Sorokin (T-6/CNLS) Probabilistic Models for PDEs with Random Coefficients |
| • 2023-08-03 Daniel Hallack (EES-16/CNLS) Mixing dynamics in 3D fracture network systems |
| • 2023-08-03 Sakshi Naik (T-5/CNLS) Variable elimination strategies for optimization problems |
| • 2023-08-03 Frank Barrows (Northwestern) Inspired by the Brain |
| • 2023-08-03 Svetlana Tokareva (T-5) An introduction to hyperbolic PDEs, applications & methods |
| • 2023-08-01 Maxim Sukharev (Arizona State University) Dynamics of Quantum Systems in Resonant Optical Nano-Cavities |
| • 2023-07-31 Dr. Stephane Zaleski Title : A journey through liquid atomisation by high speed air and gas flows, from Covid-19 to shock waves. |
| • 2023-07-27 Kelsey Alexandra Lund (T-2/CNLS) Magnetic Field Strength Effects on Nucleosynthesis in Merger Driven Outflows |
| • 2023-07-27 Riti Bahl (T-1/CNLS) Training Data Generation for Coarse Grained Molecular Dynamics |
| • 2023-07-27 Benjamin Joseph Amend (CNLS) Searching for Ancient Kilonovae in the Milky Way |
| • 2023-07-27 Yi-Tang Chen (CCS-3/CNLS) Machine Learning and Data Science for Scientific Application |
| • 2023-07-27 Andrea Liu (EES-16/CNLS) Sparse, distributed, automatic Jacobians for large-scale scientific machine learning |
| • 2023-07-27 Will Taitano (T-5) My over nine years of journey working on the Rosenbluth-Fokker-Planck Equation |
| • 2023-07-27 Xiu Yang (Lehigh University) The Adaptive Spectral Koopman Method for Scientific Computing |
| • 2023-07-26 2023 Theoretical Division Lightning Talk Student Symposium (Hybrid) |
| • 2023-07-25 2023 Theoretical Division Lightning Talk Student Symposium (Hybrid) |
| • 2023-07-24 Shrinivas Ramchandra Kulkarni (California Institute of Technology - Pasadena) The Far Ultraviolet diffuse background |
| • 2023-07-24 Ulf D. Schiller (University of Delaware) Please note - rescheduled 9-10 am - Modeling magnetically responsive particle-stabilized emulsion gels using multicomponent lattice Boltzmann methods |
| • 2023-07-20 Aaron Forde (T-1/CNLS) Molecular Chirality and Symmetry Breaking Interactions: An Overview |
| • 2023-07-19 Yuanzhao Zhang (Santa Fe Institute) Can reservoir computers learn multistable systems? |
| • 2023-07-19 Luis Chacon (T-5) A personal perspective on computational methods for fusion applications |
| • 2023-07-18 Giordano Tierra (Department of Mathematics, University of North Texas) Numerical Approximations for Phase Field Models and Other Energy Based Systems |
| • 2023-07-18 Federico Toschi (Eindhoven University of Technology) Fast and slow modes in the flow of human crowds |
| • 2023-07-17 Shawn M. Jones (CCS-3: Information Sciences) Selecting Exemplars from Document Collections |
| • 2023-07-13 Jean-Luc Guermond (XCP-2 (Visitor)) An overview of some structure preserving techniques for the approximation of nonlinear conservation equations |
| • 2023-07-12 Luis Chacon (T-5) A personal perspective on computational methods for fusion applications |
| • 2023-07-11 Jesse Chan (Rice University) An overview of high order entropy stable discontinuous Galerkin discretizations |
| • 2023-07-11 Cameron Zachereson (University of Melbourne, Australia ) Measuring and modelling equity of pandemic interventions: learning from lockdown in Australia |
| • 2023-07-10 Xianzhu Tang (LANL T-5: Applied Mathematics and Plasma Physics) How soon will fusion power be on the grid? |
| • 2023-07-10 Cameron Zachereson (University of Melbourne, Australia ) Challenges in disease transmission modelling: scales, strains, and the immune system |
| • 2023-07-06 Renai Chen (T-1/CNLS) Searching for phonon-inspired neuromorphic computation from the bottom-up: a molecular perspective |
| • 2023-07-06 Alexander Hrabski (University of Michigan) Wave Turbulence in the Numerical Kinetic Limit |
| • 2023-07-05 Hassan Hijazi (LANL T-5) Optimization and Machine Learning: Search vs Learn |
| • 2023-06-29 Abhishek Mallela (T-6/CNLS) Impacts of vaccination and SARS-CoV-2 variants Alpha and Delta on COVID-19 transmission dynamics in four metropolitan areas of the US |
| • 2023-06-26 Jimmy Fung CNLS - Meet a Scientist |
| • 2023-06-22 Hao Zhang (T-4/CNLS) CP2 Skyrmions and Skyrmion Crystals in Realistic Magnets |
| • 2023-06-19 Jonathan E. Snow (Louisiana State University) Volcanic and nonvolcanic sea floor spreading beneath the Gakkel Ridge, Arctic Ocean. |
| • 2023-06-15 Javier Estrada Santos (EES-16/CCS-3/CNLS) Generating celebrity faces from black images |
| • 2023-06-08 Sakib Matin (CNLS/T-1) Charge-aware Machine Learning Potential enables accurate simulation of liquid water |
| • 2023-06-07 Aaron Schein (University of Chicago - Dept. of Statistics and Data Science) Models of Complex Dependence Structure in Sparse Dyadic Event Data of International Relations |
| • 2023-06-06 Nick Sahinidis (H. Milton Stewart School of Industrial & Systems Engineering and School of Chemical & Biomolecular Engineering; Georgia Institute of Technology) Global optimization with integers: model-based and data-driven approaches |
| • 2023-06-05 Francesco Caravelli (T-4: Physics of Condensed Matter and Complex Systems) Complex problems might actually require real solutions |
| • 2023-06-01 Syed Shah (T-4/CNLS) Shining light on the specter of intra-material properties |
| • 2023-05-31 Mike Donlan (LANL, CEA-PA) Graphics Design tips for science folk |
| • 2023-05-26 Edward Thomas, Jr. (Physics Department, Auburn University) Exploring new regimes of low temperature plasma physics with dusty plasmas: studies from the lab to space |
| • 2023-05-26 Edward Thomas, Jr. (Physics Department, Auburn University) Exploring new regimes of low temperature plasma physics with dusty plasmas: studies from the lab to space |
| • 2023-05-25 Eric Joseph Tovar (XCP-2 / CNLS) A high-order explicit Runge-Kutta approximation technique for the Shallow Water Equations |
| • 2023-05-18 Michael Collins (Naval Research Laboratory) Elusiveness, persistence, and behaviors of the Ivory-billed Woodpecker |
| • 2023-05-18 Jake J. Harmon (T-5/CNLS) An Overview of Isotropic and Anisotropic hp Finite Elements |
| • 2023-05-17 Michael Collins (Naval Research Laboratory) Accurate and efficient solution of range-dependent wave propagation problems |
| • 2023-05-16 Lucas Hildebrand Pires da Cunha (Department of Chemical and Biomolecular Engineering, Rice University, Houston, Texas, US) Measurements on the magentic relaxation of superparamagnetic colloids in time-varying magnetic fields |
| • 2023-05-15 Prof. Eric R. Bittner (Univ. of Houston) Looking under the hood and unraveling dark processes in excitonic systems |
| • 2023-05-11 Vidushi Sharma (T-1/CNLS) Exploring Warm Dense Matter Regimes Using Density Functional Theory And Beyond |
| • 2023-05-04 David Wych (CCS-3/CNLS) Turning up the temperature: recent advances and remaining challenges in structural biology and simulation |
| • 2023-04-25 Joshua Leveillee (University of Texas at Austin) Exploring and designing finite-temperature electronic transport properties of materials with the ab initio Boltzmann transport equation |
| • 2023-04-20 Melvyn Sandy Tyloo (T-4/CNLS) Cyber and physical attacks on networked systems: the Byzantine generals problem and the energy transition |
| • 2023-04-20 Professor Cesare Tronci (University of Surrey) Energetic particle models in magnetic confinement fusion |
| • 2023-04-13 Robert Brunato Parker (A-1/CNLS) Analyzing problem formulations for reliable nonlinear optimization |
| • 2023-04-10 Alejandro Lopez-Bezanilla (Los Alamos National Laboratory (T-4)) Quantum Annealer Hardware: An Advance in Scientific Applications |
| • 2023-04-06 Antoinette Hurtado (U.S. Department of State) Careers Representing America: Life as a U.S. Diplomat |
| • 2023-04-06 Lampros Svolos (T-3) Phase-field models and advanced numerical methods for brittle and ductile fracture problems |
| • 2023-04-03 Anas Abu-Odeh (University of California, Berkeley) CANCELLED: Mean-Field Modeling of Short-Range Ordering/Clustering Kinetics Using Concentration Waves |
| • 2023-03-30 Snehasish Nandy (T-4/CNLS) Quantum Hall Effect in Weyl-Hubbard System: Interplay Between Topology and Correlations |
| • 2023-03-29 Dr. Tameem Albash (University of New Mexico ) Parallel Tempering for Ground State Approximation using Artificial Neural Networks |
| • 2023-03-27 Megan Davis (Physics and Chemistry of Materials (T-1) Group) Novel ab initio Approaches for Theoretical Vibrational Characterization of Electronically Excited States |
| • 2023-03-23 Cody Dylan Schimming (T-4/CNLS) Active nematics in geometric confinement |
| • 2023-03-23 Hao Li (Department of Chemistry, University of Houston) The Spectral Characteristics of Stochastic Processes in Many-Body Exciton Scattering |
| • 2023-03-21 Dr. Andrew King (D-Wave Systems) Quantum simulation and optimization in D-Wave quantum annealing processors |
| • 2023-03-16 Alice Allen (T-1) Learning Together: Training Interatomic Potentials to Multiple Datasets |
| • 2023-03-16 Dr. David Weld (University of California, Santa Barbra) Probing quantum dynamics with strongly driven ultracold atoms |
| • 2023-03-14 Dr. Sanjubala Sahoo (University of Connecticut) QUANTUM THEORETICAL MODELING OF ADVANCED SURFACE PROCESSES AND SMART CATALYST DESIGN |
| • 2023-03-14 Kshitija Taywade Multi-armed Bandit Algorithms for Cournot Games |
| • 2023-03-13 Stefan Sandner (Valencia U, IFIC) Kinetic equations and their applications |
| • 2023-03-13 Javier Lopez Piqueres (University of Massachusetts, Amherst) Symmetric Tensor Networks for Generative Modeling and Constrained Combinatorial Optimization |
| • 2023-03-09 Michael Douglas Saccone (T-4 / CNLS) How to get paid for your ideas - Commercialization as a postdoc |
| • 2023-03-07 Duc Truong (CCS-3) (CCS-3) Big-Data Analytics & Machine Learning, Solving Ultra-Large Partial Differential Equations and High-Dimensional Integrals |
| • 2023-03-02 Aleksander Durumeric (Freie Universität Berlin) Neural Network Coarse-Grained Models: Noise Matters |
| • 2023-03-02 David Rosenberger (Freie Universität Berlin) Slicing and Dicing: How to coarse-grain a molecule without cutting your finger |
| • 2023-03-02 Yair Shokef (Tel Aviv University) Effective Magnetism in Mechanical Metamaterials: from Spin Glass to Spin Ice |
| • 2023-03-02 Dr. Xavier Gaona Martinez (Institute of Nuclear Waste Disposal (INE), Karlsruhe Institute of Technology (KIT)) Recent Advances on Aquatic Radionuclide Chemistry and Thermodynamics |
| • 2023-03-01 Alessandro Corbetta (Eindhoven University of Technology, the Netherlands) Machine learning turbulent cascades: inference and closure |
| • 2023-02-28 Alessandro Gabbana (Eindhoven University of Technology, the Netherlands) Fast kinetic simulator for relativistic matter |
| • 2023-02-27 Marianne Francois (T-DO) CNLS - Meet a Scientist |
| • 2023-02-23 Martin Larocca (T-4) Geometric Quantum Machine Learning |
| • 2023-02-21 Luke Baker (Arizona State University) Optimal Gas Flow in Hydrogen-Blended Natural Gas Networks |
| • 2023-02-20 CNLS Executive Committee and Postdocs (CNLS) CNLS PD's and EC Discussions |
| • 2023-02-13 Shane Coffing (CCS-2) Modeling high energy density phenomena in laser-driven experiments, current and future work |
| • 2023-02-13 S. Balachandar (University of Florida) Physics-Inspired Machine Learning for Multiphase Flow Modeling |
| • 2023-02-09 Abhijith Jayakumar (T-5) Universal framework for simultaneous tomography of quantum states and measurement noise |
| • 2023-02-07 Stathis G. Charalampidis (California Polytechnic State University San Luis Obispo) Rogue Waves in Continuous and Discrete Models |
| • 2023-02-06 Joel Rosenfeld (University of South Florida) The role of Kernel Spaces in Dynamic Mode Decompositions |
| • 2023-02-02 Jake J. Harmon (T-5) On Adaptive Uncertainty Quantification and the Stochastic Finite Volume Method |
| • 2023-02-02 John M. Finn (T-5) Tutorial on Koopman operator and reproducing kernel Hilbert spaces |
| • 2023-02-01 Yulia Pimonova (University of Utah) Computational insights into cocrystallization prediction: from 2D models to real molecules |
| • 2023-01-31 Youzuo Lin (EES-16) Physics-guided Learning-driven Computational Seismic Imaging: from Synthetic Practice to Field Application |
| • 2023-01-30 Eric Bittner (University of Houston) BLABS Seminar: How does many-body scattering contribute to the exciton/polaron dynamics in 2d semiconductors? |
| • 2023-01-26 Saif R. Kazi (T-5) On Global Convergence of Mathematical Programming with Complementarity Constraints |
| • 2023-01-19 Laura Lopes (T-1) Avoiding overfitting interatomic potentials: removing redundancies in datasets |
| • 2023-01-10 George P. Tsironis (School of Engineering and Applied Sciences, Harvard University and Department of Physics, University of Crete, Greece ) Machine learning motivated approach applied to discover dynamical phase transitions and quantum resonances |
| • 2023-01-05 Aaron Forde (T-1) Ab Initio Modeling of Charge-Transfer States at Molecular Donor-Acceptor Interfaces |
| • 2023-01-05 Dr. Aidan Thompson (Sandia National Laboratories) SNAP and Beyond: Machine Learning Interatomic Potentials in LAMMPS |
| • 2023-01-01 tester test talk |
