## 2023

**Michele Pavanello (Rutgers University),** “DFT and DFT embedding: Ways to approach the mesoscopic world with ab-initio methods (without cutting corners)” and “Almost all-Python suite of software for ab-initio simulations and machine learning”

**Jane Herriman (and Don Frederick) (LLNL),** “Livermore Computing (LC) environment and leveraging LC resources - Part I. How to run and schedule jobs using SLURM on the LC Quartz cluster and Getting help with LC systems” and “Livermore Computing (LC) environment and leveraging LC resources - Part II. Getting started with Python on Quartz”

**Erik Draeger (LLNL),** “Supercomputing at the exascale and beyond: future trends and challenges”

**Talat Rahman (University of Central Florida),** “Catalytic conversion of CO2 and CO to value added products - guidelines from ab initio modeling & simulation” Parts I and II.

**Jon Belof (LLNL),** “Physical and Machine Learning Approaches toward the Control of Dynamic Material Response Far From Equilibrium”

**Aurora Pribram-Jones (UC Merced), **“Heating up Density Functional Theory” and “A Hot Mess? How Temperature, Interaction Strength, and Density Influence Electronic Structure”

**Alexander Urban (Columbia), **“Computational Materials and Process Development for a Clean-Energy Future”

**Felipe Jornada (Stanford),** “Introduction to Many-Body Perturbation Theory: Accurately Predicting Excited-State Properties of Materials from First Principles” and “Recent Developments and Applications of Many-Body Perturbation Theory Techniques to Study Excited-State Properties of Materials in Real Time”

**William Schneider (Notre Dame),** “Bridging First Principles Models to Zeolite Catalysis” and “The Catalytic Science of Making Up and Breaking Up Nitrogen”

**Ravishankar Sundararaman (Rensselaer Polytechnic Institute),** “Density-functional approximations: from electrons to classical fluids and Advancing solvation models from implicit to classical DFT methods”

## 2022

**David Richards (LLNL)**, “High Performance Computing at LLNL. Past, Present, and Future”

**Helgi Ingolfsson (LLNL)**, “MuMMI, a machine learning-driven modeling infrastructure for coupling different scales; showcased on a RAS-RAF biology application”

**Jane Herriman and Don Frederick (LLNL)**, “Livermore Computing (LC) environment and leveraging LC resources”

**Arthi Jayaraman (University of Delaware)**, “Theory, simulations, and machine learning for design and structural characterization of macromolecular materials”

**Joshua Anderson (University of Michigan)**, “Predicting the complex structures that arise from simple building blocks”

**Michael J. Janik (The Pennsylvania State University)**, “Combining experimental, density functional theory, and microkinetic modeling for catalytic mechanism determination” and “Development of electrocatalytic materials guided by computational chemistry: fuel cells and electrolysis”

**Michele Pavanello (Rutgers University)**, “DFT and DFT embedding: Ways to approach the mesoscopic world with ab-initio methods (without cutting corners)” and “The (almost) all-Python DFTpy and QM-Learn suites of software”

**Shyue Ping Ong (University of California, San Diego)**, “Mathematical Graphs as a Representation for Materials”

**Miguel A. Morales Silva (Flatiron Institute)**, “Quantum Monte Carlo methods for Ab-Initio Electronic Structure”

**Reid Van Lehn, (University of Wisconsin-Madison)**, “Classical Molecular Dynamics Simulations of Solvated Chemically Heterogeneous Interfaces” and “Combining Molecular Dynamics Simulations and Machine Learning to Screen Interfacial Properties”

## 2021

**David Richards (LLNL)**, “High Performance Computing at LLNL. Past, Present, and Future”

**Edwin Garcia (Purdue University)**, “Open Source Software for the Modeling and Simulation of Materials and Devices” and “Scaling, Coarse Graining, and Bottlenecks on the Microstructural Modeling of Lithium-Ion Batteries”

**Eberhard K.U. Gross (The Hebrew University of Jerusalem)**, “First-principles simulation of matter far from equilibrium II: Non-adiabatic dynamics from the exact factorization” and “First-principles simulation of matter far from equilibrium I: Laser-driven charge and spin dynamics from real-time TDDFT”

**Aurora Clark (Washington State University, Pacific Northwest National Laboratory)**, “Using Graphs and Topology to Identify Multidimensional Correlations in Complex Chemical Systems” and “The Mathematics of Graphs and Topology in Chemistry and Materials Science”

**Roger Rousseau (Pacific Northwest National Laboratory)**, “Effect of Collective Dynamics and Anharmonicity on Entropy in Heterogenous Catalysis: Building the Case for Advanced Molecular Simulations” and “Understanding the role of solvent effects in the thermal and electrochemical hydrogenation of organics”

**Michael Shirts (University of Colorado Boulder)**, “Materials that wiggle: thermodynamics of organic crystals and kinetics in nanostructured separation membranes” and “Computational Chemistry and Materials Science (CCMS) Summer Institute Lecture”

**Paulette Clancy (Johns Hopkins University)**, “An introductory primer on Bayesian optimization for application to the chemical and materials sciences” and “A Bayesian Optimization Case study: Finding polymorphs in chemical systems and identifying stable versus metastable variants”

**Nongnuch Artrith (Debye Institute for Nanomaterials Science)**, “Modelling of Complex Energy Materials with Machine Learning”

**Kai Nordlund (University of Helsinki)**, “Applications of molecular dynamics to model the crystal direction dependence of sputtering, antiproton motion in solid films, and possible dark matter recoils in materials”

## 2020

**Dave Richards (LLNL)**, “High Performance Computing at LLNL. Past, Present, and Future.”

A brief overview of the history and mission of High Performance Computing at LLNL. A discussion of how LLNL is adapting to the current shift to heterogeneous computing architectures and what that architectural change means to computational scientists.

**Mikhail Dzugutov (KTH Royal Institute of Technology)**, “Particle simulations in statistical mechanics and condensed matter”

**Laura Gagliardi (University of Minnesota)**, “Modeling catalysis and excited states with electronic structure theories”

**Dion Vlachos (University of Delaware), Matteo Maestri (Politecnico di Milano), Michail Stamatakis (University College London)**, “Theory, Applications, and Tools for Multiscale Kinetic Modeling Workshop,” An online workshop on kinetic models and their integration with computational fluid dynamics (CFD).

**Ellad Tadmor (University of Minnesota)**, “Predicting Behavior from the Ground Up: Molecular and Multiscale Simulations of Materials”

**Danny Perez (Los Alamos National Laboratory)**, “Long-time simulations of materials with Accelerated Molecular Dynamics”

**Yunzhi Wang (Ohio State University)**, “Phase Field Method for Simulating Complex Microstructural Evolution at Mesoscale”

## 2019

**Dave Richards (LLNL)**, “High Performance Computing at LLNL. Past, Present, and Future.”

**Wei Cai (Stanford)**, “Methods of atomistic simulations”

**Alexander Stukowski (Technische Universität Darmstadt)**, “In-silico microscopy: Novel methods for analyzing large-scale atomistic materials simulation data”

**Julia Ling (Citrine Informatics)**, “AI Algorithms in Materials Science” and “Sequential Learning Exercise in Python using Citrination”

**Phil Stern (LLNL)**, “Electronic structure calculations”

**Sebastien Hamel (LLNL)**, “Applications of electronic structure calculations”

**Krishna Rajan (University at Buffalo)**, “Data Dimensionality in Materials Science” and “Chemical Design of Materials: Case studies”

**Noa Marom (Carnegie Mellon University)**, “Structure prediction of molecular crystals from first principles” and “Computational discovery of singlet fission and up-conversion materials”

**Becky Lindsey (LLNL)**, “Machine learning for interatomic potentials development I” and “Machine learning for interatomic potentials development II”

## 2018

**Fred Streitz (LLNL)**, “Extreme Capability Computing at LLNL”

**Christine Isborn (UC Merced)**, “Modeling Excited States of Molecules in Complex Environments with time- dependent density functional theory” and “Combining the Ensemble and Franck-Condon Approaches for Spectral Shapes of Molecules in Solution”

**Anubhav Jain (LBNL)**, “High-throughput computation and machine learning applied to materials design” and “Methods, tools, and examples: High-throughput computation and machine learning applied to materials design”

**Feliciano Giustino (University of Oxford)**, “Ab initio calculations of electron-phonon interactions: theory and applications”

**Jaime Marian (UCLA)**, “The multiscale character of materials behavior: How to build viable models across multiple length and time scale” and “Selected examples of materials simulations across the scales: Alloy evolution under highly non-equilibrium conditions and its effect on mechanical properties”

**Mark Tuckerman (NYU)**, “Molecular dynamics: ‘Ersatz’ chemistry in a virtual laboratory” and “Molecular dynamics based exploration and learning of free energy landscapes of molecular crystals and oligopeptides”

**Brenda Rubenstein (Brown University)**, “Auxiliary Field Quantum Monte Carlo for Hot and Cold Electrons”

**Nandini Ananth (Cornell University)**, “Quantum Dynamics from Classical Trajectories: Path Integral and Semiclassical Methods” and “Direct Dynamic Simulations of Charge and Energy Transfer”

**Miles Stoudenmire (Flatiron Institute)**, “Introduction to Tensor Network Methods for Strongly Correlated Many-Body Systems” and “Applications of Tensor Networks: Quantum Chemistry and Machine Learning”

## 2017

**Fred Streitz (LLNL)**, “Extreme Capability Computing at LLNL”

**Kevin Leung (Sandia)**, Modeling Electrochemical Interfaces in Batteries” and “Battery Interfaces: Time, Electrostatics, and Voltages

**Davide Donadio (UC Davis)**, “Molecular dynamics: from atoms trajectories to materials properties” **and **“Thermal transport at the nanoscale and heat dissipation in liquids during pumpprobe molecular spectroscopy”

**Volker Blum (Duke University)**, “Computational Materials Science from Scratch: Density-Functional Theory, Many-Body Methods, & the Nuts and Bolts that Make Them Work” **and **“Functional Materials for Electronics and Light Harvesting - Understanding & Predictions from 1st Principles”

**Andrew Peterson (Brown University)**, “Challenges and new methods in ab initio electrochemical reactions” **and **“Developing machine-learning approaches to accelerate ab initio calculations”

**JR Schmidt (Wisconsin University)**, “Principles and practice of ab initio force field development: Applications to metal-organic frameworks and beyond” **and **“Computational heterogeneous catalysis and micro-kinetic modelling: Methods and applications”

**Maria Chan (ANL)**, “Combining first principles modeling, experimental characterization, and machine learning to understand energy materials” **and** “Examples in energy storage, photovoltaics, and catalysis”

**De-en Jiang (UC Riverside)**, “Multiscale methods in computational materials chemistry” **and** “Understanding capacitive energy storage from modeling”

**Ming Tang (Rice University)**, “Phase-field modeling of materials microstructure evolution I & II”

## 2016

**Eliot Kapit, Tulane**, Quantum Computing with Superconducting Devices-- Part I: Qubit Design and Operation" **and** "Part II: Errors, Error Correction, and Applications

**Fred Streitz, LLNL**, Extreme Capability Computing at LLNL

**Chris Van de Walle, UCSB**, Impact of point defects on efficiency of devices" **and** "Designing point defects for quantum information science

**Christopher Mundy, PNNL**, The role of an accurate description of local structure to inform our understanding of nucleation and assembly

**Francesco Paesani, UCSD**, Feel the interactions: Achieving chemical accuracy through many-body representations

**Francesco Paesani, UCSD**, Vibrational spectroscopy from many-body molecular dynamics simulations

**Andrew Taube, D.E. Shaw Research**, Anton: a computational microscope for millisecond-scale biomolecular simulation

**Andrew Taube, D.E. Shaw Research**, Developing transferable force fields for specialized hardware

**Martin Bazant, MIT**, Nonequilibrium Chemical Thermodynamics" **and** "Phase Separation Dynamics in Li-ion Batteries

**Malcolm Stocks, ORNL**, Introduction to Multiple Scattering Theory based Korringa-Kohn- Rostoker (KKR) coherent-potential-approximation (CPA) methods for disordered systems with recent applications to High Entropy Alloys

**Mal Kalos, LLNL**, Quantum Monte Carlo and the Sign Problem

**Eric Neuscamman, UC Berkeley**, Variational Monte Carlo in Electronic Structure Theory

## 2015

**Fred Streitz, LLNL**, Extreme Capability Computing at LLNL

**Sadasivan Shankar, Harvard**, Multi-level Modeling in Materials **and** Materials Design

**Ross Walker, UCSD**, The Rise of the GPU: From Quake to Simulation Workhorse **and** Lights, Computer, Action: GPU Accelerated Molecular Dynamics, from Enzyme Activation to Membrane Dynamics

**Roberto Car, Princeton**, First principles molecular dynamics

**David Trebotich, LBNL**, High Resolution Simulation of Multiscale, Multiphysics Flows in Complex Geometries

**Ying Chen, Resselaer Polytechnic Institute**, Mesoscale Polycrystalline Science: From Microstructures to Properties **and** Monte Carlo Modeling at the Mesoscale

**Yosuke Kanai, UNC Chapel Hill**, First-Principles Modeling of Electron Dynamics, 1: Real-time TD-DFT and its application to Electronic Excitation Dynamica **and** 2: Surface Hopping and its application to Hot Electron Relaxation

**Marcel Baer, PNNL**, Ab initio DFT: Thermodynamic, rates and properties **and** Bulk and interfacial solvation of monatomic and polyatomic anions/acids using DFT

**Jonathan Guyer, NIST**, Computational Kinetics **and** Phase Field Modeling

**Jianzhong Wu, UC Riverside**, Structural Thermodynamics **and** Towards molecular and materials design from first principles

## 2014

**Fred Streitz, LLNL**, Extreme Capability Computing at LLNL

**André Schleife, UIUC**, Computational Methods for Atomistic Length and Time Scales **and** Quantum Interactions: Excited Electrons and Their Real-Time Dynamics

**Daryl Chrzan, Berkeley**, Application of Periodic Supercells to the Computation of Dislocations Core Structures **and** Dislocations in Two- and Three-Dimensional Materials

**Todd Martinez, Stanford**, Modeling Excited States and Nonadiabatic Dynamics **and** Machine Learning and Stream Processors for Ab Initio Molecular Dynamics

**Vidvuds Ozolins, UCLA**, First-Principles Methods for Modeling High Temperature Behavior of Materials

**Shiwei Zhang, William & Mary**, Accurate Ab Initio Computations in Materials

**Tony Rollett, Carnegie Mellon**, Image- and FFT-based Approach for Deformation Simulation **and** Potts Model for Microstructural Evolution

**Max Berkowitz, UNC-Chapel Hill**, Atomistic Modeling of Biological Membranes and Their Interactions with Proteins and Peptides

**Francesco Pederiva, Trento, Italy**, Using quantum mechanics to describe a classical diffusion process **and** Sampling rare events in classical systems by path-integrals

## 2013

**Dr. Ulrike Meier Yang, LLNL**, High Performance Computing

**Dr. Fred Streitz, LLNL**, Opening frontiers: Extreme capability computing at LLNL

**Dr. Heather Kulik, Stanford/MIT**, The practitioner's guide to density functional theory **and** Life, the universe, everything: Efficient and accurate quantum chemistry for biological systems

**Dr. Evan Reed, Stanford**, Electromechanical properties of nanoscale materials **and** Atomistic calculations of dynamic compression of materials

**Dr. Katsuyo Thornton, University of Michigan**, Computational kinetics: Fundamentals, phase field modeling, smoothed boundary method, and applications to energy materials

**Dr. Vasily Bulatov, LLNL**, Dislocation dynamics and multiscale materials strength

**Dr. Stephen Garofalini, Rutgers**, Simulations of Molecular Behavior at Interfaces: Applications in Conversion Materials for Advanced Batteries, Intergranular Films, Nanoconfined Water, and Proton Transport

**Dr. Arthur Voter, LANL**, Accelerating molecular dynamics methods

**Dr. Boris Kozinsky, Bosch**, Ab-initio materials design for commercial applications: High-energy batteries **and** Automated screening strategies and infrastructure for materials design

## 2012

**Dr. Ulrike Meier Yang, LLNL**, High Performance Computing

**Dr. David Prendergast, Lawrence Berkeley National Lab**, Simulating Core-Level Spectroscopy from First Principles I **and** Simulating Core-Level Spectroscopy from First Principles II

**Prof. Eva Zurek, State University of New York at Buffalo**, Locating the Global and Local Minima of Clusters and Solids **and** From Metallic Hydrogen to the Anti-AIDS Drug Ritonavir: The Need for Crystal Structure Prediction

**Dr. Todd Weisgraber, LLNL**, An Overview of the Lattice-Boltzmann Method for Fluid Dynamics

**Dr. John Bell, Lawrence Berkeley National Lab**, Finite-Volume Methods for Fluctuating Hydrodynamics

**Prof. Kieron Burke, UC Irvine**, The ABCs of DFT I **and** The ABCs of DFT II

**Dr. Sadasivan Shankar, Intel Corp.**, Enabling Computational Materials and Chemistry Prototyping: Multi-Scale Modeling & Non-equilibrium systems I **and** Enabling Computational Materials and Chemistry Prototyping: Multi-Scale Modeling & Non-equilibrium systems II

**Prof. Jorge Kohanoff, Queen's University Belfast, Ireland**, Simplified methods for electronic structure calculations **and** A self-consistent tight-binding approach for the study of chemical reactions in heterogeneous environments

**Prof. Peter Voorhees, Northwestern University**, Computational Materials Science using Phase Field Methods I **and** Computational Materials Science using Phase Field Methods II

**Dr. Celia Reina Romo, LLNL**, Modeling and Simulation of Damage by Nucleation and Void Growth: a Multiscale Approach

## 2011

**Professor Troy van Voorhis, MIT**, What can simulations teach us about organic photovoltaics? **and** Improving density functional theory at long- and short-range

**Professor Long-Qing Chen, Pennsylvania State University**, Strain Contributions to Thermodynamics of Phase Transitions and Microstructure **and** Applications of Phase-field Method to Modeling Microstructure Evolution

**Professor Mark Asta, University of California, Berkeley**, Materials Interfaces Studied by Atomic-scale simulations I **and** Materials Interfaces Studied by Atomic-Scale Simulations II

**Dr. Jeffrey Neaton, Lawrence Berkeley National Laboratory**, Tailoring Nanoscale Interfaces for Renewable Energy Applications with Computation: DFT and Beyond

**Professor Stephen Garofalini, Rutgers University**, The Effect of the Water/Silica Interface on the Behavior of Nanoconfined Water and Proton Transport

**Dr. Janathan Dubois, Lawrence Livermore National Laboratory**, Solving Quantum Many Problems One Random Number at a Time

**Dr. Randy Hood, Lawrence Livermore National Laboratory**, Quantum Monte Carlo Studies of Electronic Structure

**Professor Andrew Rappe, University of Pennsylvania**, First-principles calculations as the cornerstone for multi-scale materials simulations **and** Using first-principles calculations to design new materials for solar energy harvesting

**Professor Giulia Galli, University of California, Davis**, Understanding and predicting materials for energy: Insight from quantum simulations I **and** Understanding and predicting materials for energy: Insight from quantum simulations II

**Professor Ting Zhu, Georgia Institute of Technology**, Revealing the Failure Mechanisms in Nanomaterial Electrodes for Lithium Ion Batteries **and** Nanomechanics of Ultra-strength Nanomaterials

**Dr. Patrick Rinke**, Towards a unified description of ground and excited state properties: the GW approach

## 2010

**Prof. Jeffrey C. Grossman, MIT**, Introduction to Electronic Structure Calculations in Materials Science: Density Functional Theory and Quantum Monte Carlo Methods **and** Applications of Electronic Structure Methods to Materials for Energy Conversion and Storage

**Dr. Eric Schwegler, Lawrence Livermore National Laboratory**, Materials Simulations for NIF

**Prof. Alain Karma, Northeastern University**, Phase-Field Modeling of Micro/Nano-structure Formation: From Turbine Blades to Nanowires I **and** Phase-Field Modeling of Micro/Nano-structure Formation: From Turbine Blades to Nanowires II

**Prof. Kaushik Bhattacharya, California Institute of Technology**, Phase transitions and microstructure in solids: General Principles **and** Phase transitions and microstructure in solids: Case Study of Liquid Crystal Elastomers

**Prof. Wei Cai, Stanford University**, Predicting Nucleation Rate by Computer Simulations I **and** Predicting Nucleation Rate by Computer Simulations II

**Prof. Chris Wolverton, Northwestern University**, Computational Discovery of Novel Hydrogen Storage Materials and Reactions **and **First-Principles Calculations and Virtual Aluminum Castings

**Prof. Oleg Prezhdo, University of Rochester**, Nonadiabatic Molecular Dynamics with Time-Domain Density Functional Theory **and** Time-domain ab initio studies of quantum dots and molecule-bulk interfaces for solar energy harvesting

**Dr. Berni Alder, Lawrence Livermore National Laboratory**, Historical Perspectives in Computational Physics