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CNLS Talks, 2024
• 2024-12-09 Dr. Andrew Salij (T-4) Optical Cavities with Apparent Circular Dichroism
• 2024-12-05 Hao Zhang (CNLS/T-4) Bound States and Resonances in the 1/3-Plateau Phase of Triangular Lattice Antiferromagnets
• 2024-12-04 Chris Taylor (Tactical Computing Lab) RISC-V HPC Terrain Familiarization
• 2024-12-03 Fabien Evrard (University of Illinois) Recent Advances in Multiscale Multiphase Flow Modeling
• 2024-12-02 Tim Linke (Lawrence Livermore National Laboratory) Multiscale Methods for Flows at Extreme Conditions
• 2024-11-25 Wonjune Choi (T-4) Nonlinear Spectroscopy as a Probe of Quantum Spin Liquids
• 2024-11-21 Alejandro Cardenas Avendano (CNLS/CCS-2) Black hole light curve autocorrelations and relativistic echoes
• 2024-11-20 Mansi Bezbaruah, Texas A&M (Texas A&M University) (Virtual Only) Shape and Eigenvalue Optimization of Microstructures Governed by Maxwell's Equations
• 2024-11-19 Anthony Gruber (Sandia National Laboratory) Data-Driven Dynamical Systems with Structural Guarantees
• 2024-11-18 Christopher Noble (University of Arizona) Non-Deterministic Multi-Fidelity Surrogates
• 2024-11-14 Paprapee Buason (T-5) Adaptive Power Flow Linearizations: Sample-Based Conservative Approximations and Second-Order Sensitivity Insights.
• 2024-11-13 Gerhard Wellein (Professor for High Performance Computing, Department for Computer Science, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU)) Performance Engineering for High Performance Computing
• 2024-11-06 Paul Laiu (Oak Ridge National Laboratory) Weak-SINDy surrogate models and their application in streaming scientific data compression
• 2024-11-05 Daniel Vigil (Sandia National Laboratory) Simulating block copolymers across length-scales: from atoms to microstructure
• 2024-11-05 Stefan Schnake (Oak Ridge National Laboratory) A micro-macro decomposition for implicit time-stepping of the BGK model
• 2024-11-04 James Kotary (University of Virginia) End-to-End Learning for Constrained Optimization
• 2024-11-04 Jessica Stockdale (Simon Fraser University) Modelling with genomic data for viral prediction and pandemic forecasting
• 2024-10-31 Charlie Young (CNLS/T-1) Dynamical systems reconstruction from sparse sensors: Attention is all you need?
• 2024-10-28 Noah Rhodes (A-1) Flexibility in Energy Transportation: Rethinking the Power Grid
• 2024-10-24 Kamal Wagle (XCP-5/CNLS) Ab initio Study of Nuclear Resonance Spectroscopy of Fentanyl Compounds
• 2024-10-21 Steve Senator, Phil Kauffman, Vivian Hafener, Jacob Frulla (HPC-ENV Group, Los Alamos National Laboratory ) Principles of Slurm
• 2024-10-15 Brian Appelbe (Imperial College London) Neutron Capture in a Plasma Environment
• 2024-10-14 Can Li (Purdue University) Applications of Machine Learning in Solving and Explaining Optimization Models
• 2024-10-10 Luke Baker (CNLS/T-5) Robust Quantum Gate Preparation in Open Environments
• 2024-10-09 David Bernal (Purdue University) Quantum-Classical Hybrid Methods: Applications in optimization, machine learning, and computational chemistry
• 2024-10-07 Ezra Karger (The Federal Reserve Bank of Chicago and The Research Director of the Forecasting Research Institute) Tradeoffs between AI Progress and Biorisk
• 2024-10-03 Patrick Cheong (CNLS) Gamma-ray bursts and kilonova emission from magnetized accretion-induced collapse of white dwarfs
• 2024-09-26 Sakib Matin (T-1) Teacher-Student Training improves accuracy and efficiency of Machine Learning Inter-atomic Potentials
• 2024-09-26 Dr. Sarah Sheldon (IBM) Near term quantum algorithms: a heuristic journey
• 2024-09-19 Agnese Marcato (EES-16/CNLS) Developing a Foundation Model for Predicting Material Failure
• 2024-09-12 Karthik Elamvazhuthi (T-5) Control of Nonlinear systems using Denoising Diffusion Models
• 2024-09-12 Emily Shinkle (LANL/CCS-3) Thermodynamic Transferability in Coarse-Grained Force Fields using Graph Neural Networks
• 2024-09-04 Alan Williams (AOT-AE) Safe Extremum Seeking with Applications to Particle Accelerators
• 2024-08-29 Megan Davis CANCELLED: Computational Screening of Transition Metal-Nitrogen-Carbon Materials as Electrocatalysts for CO2 Reduction
• 2024-08-28 Hamad El Kahza (T-5) Adaptive-Rank Implicit Time Integrator for Advection-Diffusion Transport Equations with Inhomogeneous Separable Coefficients
• 2024-08-27 Qianying Lin Model-based Deep Learning Inferential Framework for Genomic Reassortment
• 2024-08-27 Ruian Ke A graph theory and machine learning approaches for identifying rapidly expanding SARS-CoV-2 lineages using early genetic data
• 2024-08-27 Yen Ting Lin Bayesian inference for SARS-CoV-2 pandemic
• 2024-08-27 Casey Gibson Improving ML based infectious disease forecasting through mechanistic constraints
• 2024-08-27 Sara del Valle Harnessing Large-Scale Unstructured Data to Understand Public Perception
• 2024-08-27 Sayera Dhaubhadel Suicide veteran predictions using transfer learning
• 2024-08-27 Shounak Banerjee Learning Growth Curves: Algae Crops vs Harmful Algae Blooms
• 2024-08-27 Justine Moore Local Latent Space Bayesian Optimization for Drug Discovery
• 2024-08-27 Manish Bhattarai DNA Breathing Integration with Deep learning Foundational Model Advances
• 2024-08-26 Michael Wall Some Novel Applications for Molecular-Dynamics Simulations of Biomolecules
• 2024-08-26 Jason Gans A cross-validation framework for data clustering by protein sequence similarity
• 2024-08-26 Blake Hovde NLP trained on biological literature, for protein and plasmid analysis
• 2024-08-26 Bin Hu Learning the language of proteins and predicting the impact of mutations
• 2024-08-26 Sandrasegaram Gnanakaran Prediction of virus-host protein-protein interactions
• 2024-08-26 Beth Stelle AI and Human Subjects Research
• 2024-08-26 Lauren VanDervort Statistical Bias and Predictive Modeling
• 2024-08-26 Morgan Gorris Projecting the geographical distribution of mosquitoes in response to climate change
• 2024-08-26 Carrie Manore Using a hybrid approach of AI and mechanistic models to predict climate change impact on infectious diseases
• 2024-08-26 Nick Generous AI and Biological Risk
• 2024-08-22 Alessandro Gabbana (CNLS/CCS-2) Kinetic data-driven approach to turbulence subgrid modeling
• 2024-08-22 Adolfo del Campo (Professor of Physics at the University of Luxembourg) Quantum Dynamics in Krylov Space
• 2024-08-15 Joshua Leveillee (T-1/CNLS) Mixed resolution of the identity compressed exchange for electronic structure calculations in warm dense matter and hot dense plasma
• 2024-08-15 Aurelia Chenu (Associate Professor at University of Luxembourg) Dynamics of noisy quantum systems: from chaos to control
• 2024-08-15 Ali Miri, Wesley Dyk, Lac Nguyen, and Bridgid Chandler (Quantum Computing, Inc. (QCi)) Using Nonlinear Optical Phenomena in Lithium Niobate for Photonic Computing Engines
• 2024-08-13 Dr. Andreas Geist (Karlsruhe Institute of Technology (KIT)) 30+ Years of Solvent Extraction Development for Minor Actinide Separations in Europe
• 2024-08-12 Daniel Burns (Iowa State University ) Applications of Chemically Accurate Contact Response Analysis (ChACRA)
• 2024-08-12 Dr. Wade DeGottardi (Texas Tech University) Probing One-Dimensional Electron Systems with Light
• 2024-08-08 Prof. William Bricker (Department of Chemical and Biological Engineering at the University of New Mexico) DNA at the Multi-Scale: Theory and Applications
• 2024-08-08 Fumika Suzuki (T-CNLS) Probing chiral Casimir-Polder forces in a molecular matter-wave interferometer
• 2024-08-01 CNLS Summer Students (CNLS) CNLS Summer Student Talk Competition - Part 2
• 2024-07-31 Yongsoo Park (LANL EES-17 (National Security Earth Science)) Machine learning and seismic monitoring: A trilogy
• 2024-07-31 Mac Hyman (Tulane University ) Good Choices for Great Careers
• 2024-07-30 Professor Gia-Wei Chern (University of Virginia) Machine Learning Force Field Approach to Multiscale Dynamical Modeling of Correlated Electron Systems
• 2024-07-30 2024 HSC/UGS Theoretical Division Lightning Talk Student Presentations (Hybrid)
• 2024-07-29 Mashroor S. Nitol (MPA-CINT, LANL) Machine Learned spin dynamic-lattice dynamic interatomic potential for polymorphic iron
• 2024-07-29 Dr. Karen L. Butler-Purry (Texas A&M University) Enhancing Power Grid Resiliency with Microgrid Restoration
• 2024-07-25 CNLS Summer Students (CNLS) CNLS Summer Student Talk Competition - Part 1
• 2024-07-25 David Gosset (University of Waterloo) Triply efficient shadow tomography
• 2024-07-25 Cynthia Reichhardt (LANL T-1 (Physics and Chemistry of Materials)) Machine Learning for Active and Driven Matter
• 2024-07-25 Jean-Marc Leyssale (Institut des Sciences Moleculaires, Universite de Bordeaux -CNRS, Talence, France) Modeling Complex Carbon Materials: Structure & Properties
• 2024-07-24 2024 GRA Theoretical Division Lightning Talk Student Presentations
• 2024-07-24 Anne Stratman (University of Nebraska - Lincoln) Optimizing Bidding Strategies for a Wind-Battery System Using a Novel Stochastic Optimization - Deep Reinforcement Learning Method
• 2024-07-23 2024 GRA Theoretical Division Lightning Talk Student Presentations
• 2024-07-23 Hannah Sweatland (University of Florida) Safe Control Methods for Uncertain Nonlinear Dynamical Systems
• 2024-07-22 Ruian Ke (LANL T-6 (Theoretical Biology and Biophysics)) CovTransformer: A transformer model for SARS-CoV-2 lineage frequency forecasting
• 2024-07-18 Frank Barrows (T4/CNLS) Networks with memory: Training, operator techniques and kernel methods
• 2024-07-17 Michael McCann (LANL T-5 (Applied Mathematics and Plasma Physics)) Generative models for image reconstruction
• 2024-07-17 R. Loubere - Universite de Bordeaux, Bordeaux INP, CNRS, LRC Anabase, Bordeaux, France (with B. Cossart and J-P. Braeunig - CEA Cesta, Le Barp, France) Novel implicit finite volume frameworks for hypersonic steady flow problems
• 2024-07-16 Yen Ting Lin (LANL, CCS-3 (Information Sciences Group)) Generative Modeling for Sampling: Liouville Flow Importance Sampler
• 2024-07-11 Jake Harmon (T-5/CNLS) Predicting Event Times via Active Discretization
• 2024-07-11 Corey Ostrove (Sandia National Laboratory) Characterizing quasistatic noise in quantum processors
• 2024-07-11 Prof. Joel Rosenfeld (Department of Mathematics and Statistics, University of South Florida) Koopman Operator Workshop Part IV - A New Hope for Operators and Inverse Problems
• 2024-07-10 Charlie Young (LANL T-1 (Physics and Chemistry of Materials) and CNLS Postdoc) Learning dynamical systems for scientific applications
• 2024-07-09 Prof. Joel Rosenfeld (Department of Mathematics and Statistics, University of South Florida) Koopman Operator Workshop Part III - Generalizations to Control Affine and Higher Order Dynamical Systems
• 2024-07-09 Dr. Ann E. Mattsson Wills (XCP-5) DFT (and DMFT) for DFT Users
• 2024-07-08 Professor Eric R. Bittner (University of Houston) Can environmental noise enhance and sustain quantum coherence and entanglement?
• 2024-07-03 Andreas Zeiser (HTW Berlin) Dynamical low-rank approximation of the Vlasov-Poisson equation with piecewise linear spatial boundary
• 2024-07-03 Daniel Belkin (University of Illinois Urbana-Champaign) Approximate t-designs in generic circuit architectures
• 2024-07-03 Weizhi Li (LANL CCS-6 (Statistical Sciences)) AI-enhanced exploration for planetary science
• 2024-07-02 Dr. Ann E. Mattsson Wills (XCP-5) DFT (and DMFT) for DFT Users
• 2024-07-02 Prof. Joel Rosenfeld (Department of Mathematics and Statistics, University of South Florida) Koopman Operator Workshop Part II - Occupation Kernels and Koopman Generators for DMD on Continuous Time Systems
• 2024-06-27 Nikita Fedik (T-1/CNLS) Challenges and Opportunities for Machine Learning Potentials in Transition Path Sampling
• 2024-06-27 Prof. Joel Rosenfeld (Department of Mathematics and Statistics, University of South Florida) Koopman Operator Workshop Part I - Kernel Perspective on Koopmanism
• 2024-06-26 Emily Castleton (LANL CCS-6 (Statistical Sciences)) Foundation Models for Nuclear Non-Proliferation
• 2024-06-26 Mike Martin -- LANL -- In person Quantum information science with Rydberg atoms: Tutorial and future directions
• 2024-06-25 Ann E. Mattsson Wills (XCP-5, LANL) DFT and DMFT for DFT users
• 2024-06-24 Fangning Zheng (LANL EES-16 (Energy and Natural Resources Security)) Deep Learning Assisted Multi-Objective Optimization of Geological CO2 Storage Performance under Geomechanical Risks
• 2024-06-24 Rolando Somma - Google - In person Quantum Simulation Algorithms
• 2024-06-21 Robert Huang - Caltech - Virtual Learning Shallow Quantum Circuits
• 2024-06-20 Alice Allen (T-1/CNLS) Improving Atomistic Simulations With Machine Learning
• 2024-06-19 Elena Reinisch and Amber Whelsky (LANL ISR-6 (Space Remote Sensing and Data Science)) Advancing the State of Sea Ice Labeling in Synthetic Aperture Radar Imagery via Polarimetric Classification
• 2024-06-19 Daniel Serino (T-5, LANL) AI for Science in T Division: Introduction to Transformers for Scientific ML
• 2024-06-18 Miles Stoudenmire - Flatiron Institute - In person Quantum Algorithms as Tensor Networks
• 2024-06-17 Dr. Adra (Tory) Carr (LANL ISR-6 (Space Remote Sensing and Data Science)) Physics-Trained Machine Learning for Rare Target Detection in Hyperspectral Imaging
• 2024-06-17 Dr. Daniel Serino (T-5, LANL) Structure-Preserving Machine Learning for Dynamical Systems
• 2024-06-14 Supanut Thanasilp - EPFL - In person Exponential concentration in quantum machine learning
• 2024-06-13 Robert Parker (A-1) Surrogate and implicit models in nonlinear optimization problems
• 2024-06-13 Dr. Rahul Somasundaram (T-2 and Syracuse University ) Machine Learning for Data-Driven Nuclear Astrophysics
• 2024-06-13 Nathan Killoran - Xanadu - In person Optimizing Quantum Computation: A Quantum Gradients Masterclass
• 2024-06-12 David Mascarenas (LANL E-1 (Mechanical & Thermal Engineering)) A Neuromorphic, Event-Based Light Field Imager for Beating 2 Sides of the Exposure Triangle in Post Processing
• 2024-06-12 Dr. Saif Kazi (LANL, T-5 (Applied Mathematics & Plasma Physics)) Nonlinear Systems Modeling and Optimization for Energy Networks and Other Applications
• 2024-06-12 Vedran Djunko - Leiden University - Virtual Provable quantum earning advantages for physics data
• 2024-06-11 James Amarel (NRC Postdoctoral Fellow, U.S. Naval Research Laboratory, Washington, D.C.) Deep Learning (DL) Enabled Detection and Localization of Damage in Metal Plates
• 2024-06-11 Christa Zoufal - IBM - In person Variational Quantum Simulation with McLachlan
• 2024-06-10 Dr. Matthias Maier (Texas A&M University ) ryujin: high-performance high-order finite element solver for hyperbolic conservation equations
• 2024-06-10 Kshitija Taywade (T-5) AI for Science in T Division: Reinforcement Learning
• 2024-06-10 David Wierichs - Xanadu - In person Using PennyLane for advanced quantum research
• 2024-06-07 Andrey Lokhov ((T-5)) Sampling with Analog Quantum Computers
• 2024-06-07 Daniel Derr (Technische Universität Darmstadt, Germany) INERTIAL QUANTUM SENSORS AT THE INTERFACE OF RELATIVITY
• 2024-06-06 William G. Unruh (University of British Columbia, Canada) ANALOG BLACK HOLES
• 2024-06-06 Patrik Schach (Technische Universität Darmstadt, Germany) QUANTUM SENSORS BASED ON TUNNELING
• 2024-06-06 Ralf Schützhold (Helmholtz-Zentrum Dresden-Rossendorf, Germany) INTERACTION OF GRAVITATIONALWAVES WITH QUANTUM MATTER
• 2024-06-06 Jonathan Oppenheim (University College London, England) A POSTQUANTUM THEORY OF CLASSICAL GRAVITY
• 2024-06-05 Roman Krems (University of British Columbia, Canada) CAN QUANTUM COMPUTING ENHANCE MACHINE LEARNING AND, IF YES, HOW?
• 2024-06-05 Markus Arndt (University of Vienna, Faculty of Physics) UNIVERSAL MATTER-WAVE INTERFEROMETRY ACROSS THE MASS & COMPLEXITY SCALES
• 2024-06-05 Luiz Davidovich (Federal University of Rio de Janeiro) QUANTUM SENSORS: BEYOND THE CLASSICAL LIMITS OF PRECISION
• 2024-06-04 Michael Geyer (LANL A-4 (Advanced Research in Cyber Systems)) An Introduction to the History and State of Deep Learning Methods
• 2024-06-04 Ralf Schutzhold (Helmholtz-Zentrum Dresden-Rossendorf, Germany) DYNAMICALLY ASSISTED TUNNELLING
• 2024-06-04 Wojciech H. Zurek (T) DECOHERENCE AND QUANTUM DARWINISM: FROM QUANTUM FOUNDATIONS TO CLASSICAL REALITY
• 2024-06-03 Yulia Pimonova, Postdoctoral Research Associate, CCS-3 (CCS-3) Synthon Competition for Cocrystallization Prediction: Lessons Learned
• 2024-05-30 Ojas Parekh (Sandia National Laboratories) Exponential quantum advantages by making problems harder
• 2024-05-28 Chris Wells (Auburn University) Small projective codes and equiangular lines
• 2024-05-23 Brian O'Shea (Professor at Michigan State University) Adventures in understanding diffuse magnetized astrophysical plasmas
• 2024-05-23 Martin Larocca (T-4/CNLS) Towards Scalable Quantum Machine Learning
• 2024-05-22 Jasmine Foo (Northrop) Understanding the kinetics and effects of phenotypic switching in cell populations
• 2024-05-20 Sabrina Li (LANL) Understanding energy dissipation in ultrafast optical experiments from first principles
• 2024-05-20 Sayera Dhaubhadel (T-6 (Theoretical Biology and Biophysics)) AI for Science in T-Division: Transfer learning illustrated by suicide prediction
• 2024-05-16 Brian Tran (T-5 / CNLS) Nonlinearly Partitioned Runge-Kutta Methods
• 2024-05-16 Jared Averitt (University of North Carolina Greensboro) Modeling the Dynamics of 2D Nanoscale Devices: From Classical Physics to Quantum Theory and Machine Learning Perspectives
• 2024-05-13 Luis Chacon - LANL Program Manager for DOE-SC ASCR (T-5) Joint CNLS and Institutional Computing Applications Science Seminar Series. Hyperion: A high-fidelity simulation capability for ICF hohlraum environments
• 2024-05-13 Xiaoyu (Sherry) Zhang (Purdue University) A new 3-D discrete dynamical system for turbulent flow and direct numerical simulations using GPU-accelerated volumetric lattice Boltzmann method
• 2024-05-13 Dr. Xiaoyu (Sherry) Zhang (Purdue University) A new 3-D discrete dynamical system for turbulent flow and direct numerical simulations using GPU-accelerated volumetric lattice Boltzmann method
• 2024-05-09 Abhijith Jayakumar (T-5 / CNLS) Learning while stuck: Reconstructing binary graphical models from metastable states
• 2024-05-08 Prof. Oscar Grånäs (Uppsala University, Sweden) Laser-induced magnetization dynamics from first-principles - Prospects of optical control and observability on sub 100-fs time scales
• 2024-05-06 Nathaniel Morgan (E-2) (E-2) Revolutionizing Design through Advanced Numerical Methods and Manufacturing
• 2024-05-02 Cody Schimming (CNLS / T-1) Control of Active Nematics
• 2024-04-30 Clarice Aiello (Quantum Biology Tech (QuBiT) Lab, Los Angeles, CA) Quantum Biology: How nature harnesses quantum processes to function optimally, and how might we control such quantum processes to therapeutic and tech advantage
• 2024-04-30 Jan Janssen (Group Leader, Max Planck Institute for Sustainable Materials, Dusseldorf, Germany) Pyiron: Simulation Workflows for Data-Driven Materials Design
• 2024-04-30 Eric Anschuetz (Caltech) Arbitrary Polynomial Separations in Trainable Quantum Machine Learning
• 2024-04-30 Gordon Freedman (National Laboratory for Education Transformation (NLET), Oakland, CA) Stephen Hawking, the Popularization of Science and the STEM Pipeline
• 2024-04-29 Michael Woodward (LANL, CCS-2) Reduced Lagrangian and Mori-Zwanzig Models: Applications To Turbulent Flows
• 2024-04-29 Sebastien Thevenin (CEA, France) The memory of Rayleigh-Taylor turbulence
• 2024-04-29 Sergi Julia-Farre (PASQAL) Amorphous quantum magnets in a two-dimensional Rydberg atom array
• 2024-04-25 Saif Kazi (T5 - Applied Mathematics and Plasma Physics) How to Control Hybrid Dynamical Systems Efficiently - Discretization and Optimization
• 2024-04-24 Sam Scarpino (Northeastern University) On the Shape of Epidemics
• 2024-04-22 David Wolpert (Santa Fe Institute) Non-equilibrium statistical physics of computation and communication
• 2024-04-22 Preston Robinette (Vanderbilt University) Novel Verification Domain for Malware Classification
• 2024-04-18 Patrick Rall (IBM) The Future of Fault Tolerant Quantum Computation at IBM
• 2024-04-18 Eric Tovar (T-5 / CNLS) High-order invariant-domain preserving approximation of the compressible multi-species Euler Equations
• 2024-04-17 Gaia Tomasello (Wiley VCH, Berlin, Germany) The use of Generative Artificial Intelligence tools in scientific publishing
• 2024-04-16 Andreas Waechter (Northwestern University) A Smoothing-Based Decomposition Framework for Nonlinear Nonconvex Two-Stage Optimization Problems
• 2024-04-15 Richard Messerly (LANL, T-1 Scientist) Active learning for atomistic simulation: From the basics to state-of-the-art applications
• 2024-04-11 Syed Shah (T-4 / CNLS) Plasmonic Nano-Structures: from linear to nonlinear properties.
• 2024-04-11 Adrian Sandu (Virginia Tech) Multimethod approaches in time integration
• 2024-04-08 Cristian D. Batista (University of Tennessee) Lecture 3 of 3: Large-N approach to spin dynamics near "quantum melting points".
• 2024-04-08 Nathaniel Morgan (E-2) Revolutionizing Design through Advanced Numerical Methods and Manufacturing
• 2024-04-04 Luke Baker (T-5 / CNLS) Robust Optimal Control of Robotic and Quantum Systems
• 2024-04-03 Dr. Wolfgang E. Kerzendorf (Michigan State University) Reconstructing the physics of transients using machine learning
• 2024-04-02 Jess Riedel (NTT Research, Inc) Ehrenfest's theorem beyond the Ehrenfest time
• 2024-04-02 Brian O Shea (Michigan State University) CANCELLED - Adventures in understanding diffuse magnetized astrophysical plasmas
• 2024-04-02 Seth Blumsack (Penn State) Do Electric Compressors Threaten Power Grid Reliability?
• 2024-04-01 Cristian D. Batista (University of Tennessee) Lecture 2 of 3: Generalized classical and semi-classical dynamic of quantum spin systems
• 2024-03-28 Vidushi Sharma (T-1 / CNLS) Mixed Stochastic-Deterministic Density Functional Theory For Electronic Transport In Matter In The Extremes
• 2024-03-25 Cristian D. Batista (University of Tennessee) Lecture 1 of 3: Classical limit of quantum systems
• 2024-03-18 Moises Sudit, Ph.D. (Institute for Multisource Information Fusion | University at Buffalo) Hybrid Approaches to Solve NP-Hard Problems
• 2024-03-18 Thomas Gruber (Software & Tools Erlangen National High Performance Computing Center Friedrich-Alexander University Erlangen-Nurnberg Erlangen, Germany) Institutional Computing Science Seminar Series: Run And Analyze Code with the LIKWID Toolsuite
• 2024-03-14 Hao Zhang (T-4 / CNLS) Multipolar Skyrmion Crystals in Non-Kramers Doublet Systems
• 2024-03-13 Maria Gatu Johnson (Massachusetts Institute of Technology) Using the iFP code to interpret signatures of kinetic and multi-ion effects in MIT-led experiments
• 2024-03-12 Dr. Robert F. Lucas (Ansys Fellow and a Distinguished Engineer at Livermore Software Technology) Accelerating Graph Partitioning
• 2024-03-11 Carla Frohlich (North Carolina State University) Neutrinos, Nuclei, and Neutron stars from Core-collapse Supernovae
• 2024-03-07 Minh N. Vu (T-1) Trustworthy AI: Explain and Exploit
• 2024-03-07 Frederik Geth (GridQube) Industrial experiences in deploying Distribution State Estimation and Dynamic Operating Envelopes in Australia, and Open R&D Challenges
• 2024-02-29 Charlie Young (T-1 / CNLS) Forecasting sparse and incomplete state observations using machine learning and dynamical systems theory
• 2024-02-27 Dr. Ralf Drautz (ICAMS - Ruhr-Universitat Bochum, Germany) Graph Atomic Cluster Expansion: Accurate Representation of Atomic Interactions for the Simulation for Materials Properties
• 2024-02-26 Cecilie Glittum (University of Cambridge) Doping-induced spin liquid in a pyrochlore magnet
• 2024-02-22 Kamal Wagle (XCP-5 / CNLS) Effect of dynamical motion in ab initio studies of magnetic resonance spectroscopy
• 2024-02-21 Sungho Shin (Argonne National Laboratory) Accelerated Nonlinear Programming on GPUs: Implementing Solver and Automatic Differentiation
• 2024-02-15 Margaret Wood (A-1 / CNLS) (A-1 / CNLS) Constructing a textual profile of social media posts that gain traction in online communities
• 2024-02-14 Michael Herty Ensemble Methods for Nonlinear Nonconvex Optimization
• 2024-02-08 CNLS Postdoc Informal Meeting On AI and Research
• 2024-02-05 Joshua D. Finkelstein (T-1) Institutional Computing Science Seminar Series. Exploiting massive parallelism and hybrid architectures for ab initio simulations: Progress and Challenges
• 2024-02-01 Megan C. Davis (T-1/T-CNLS) Design of Carbonaceous Amine Materials for Direct Air Capture using Integrated High-Throughput Calculations and Machine Learning
• 2024-01-25 Joshua Leveillee (T-1/CNLS) Stochastic density functional theory - towards excited states in warm dense matter
• 2024-01-25 Prof. Mamadou Diagne (University of California San Diego) Rescheduled - Machine Learning (ML) in Service of Model-based PDE Control
• 2024-01-25 Cristiano Nisoli, T-4 (T-4) T-4 Seminar
• 2024-01-22 Georgios Tsironis (School of Engineering and Applied Sciences, Harvard University and Department of Physics, University of Crete, Greece) Machine learning applied to cardiovascular and photoacoustic microscopy data
• 2024-01-18 Melvyn Tyloo (T-4/CNLS) Forced oscillations identification from partial PMU coverage in high-voltage grids
• 2024-01-18 Prescott (Scottie) Alexander (Information Systems & Modeling (A-1) & Physics and Chemistry of Materials (T-1)) CANCELLED- Exploring the biological basis of neural computations within the early visual system
• 2024-01-17 Professor Yonatan Dubi (Ben Gurion University (Israel)) The Chirality-Induced Spin Selectivity Effect - A Puzzle and Its (Possible) Resolution
• 2024-01-16 Yonatan Dubi (Ben Gurion University - Department of Chemistry) Nano-Plasmonic Photo-Catalysis - "Hot Electrons" or just Heating?
• 2024-01-11 Vidushi Sharma (T-1/CNLS) (CANCELLED 1.11.24)Mixed Stochastic-Deterministic Density Functional Theory For Electronic Transport In Matter In The Extremes
• 2024-01-11 Prof. Marivi Fernandez-Serra (Stony Brook University) (HYBRID - Update - this is NOT CANCELLED) Machine learning in Density Functional Theory: Current milestones and challenges
• 2024-01-07 Alexander Holas (Heidelberg Institute for Theoretical Studies) Thermonuclear electron-capture supernovae - Motivating a long-overdue update to the supernova modeling pipeline for the exascale computing age

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