Please enjoy the talks below from our 2024 session!
SAND Numbers are be listed for all SNL presentations and materials.
|
Track 1: Topics - Machine Learning Techniques and Applications |
|
Time (MST) |
Title |
Speaker |
Media/Materials |
|
9:15 am |
Keynote: Sandia AI Strategy & Roadmap |
Jen Gaudioso and Cindy Phillips (SNL) |
SAND2024-11290V
Video |
|
9:55 am |
Explainable Machine Learning Models for Predicting Oxygen Activation Energies in Perovskites and Pyrochlores |
Grace M. Lu (UIUC) |
Video |
PDF |
|
10:20 am |
Learning Algorithms for Constrained Hidden Markov Models |
Connor Mattes (SNL) |
SAND2024-10859C
Video |
|
10:50 am |
Nonparametric Sparse Learning of Dynamical Systems |
Boya Hou (UIUC) |
Video |
PDF |
|
11:10 am |
Continual Learning with Neurogenesis |
Timothy Draelos (Retired SNL) |
Video |
PDF |
|
11:35 am |
Automated Algorithms for Screening Electronic Parts for Aging using Power Spectra Analysis (PSA) Data |
Rosalie Multari (SNL) |
SAND2024-09775C
Video
SAND2024-09493C
PPTX |
|
1:00 pm |
Scoring Morphological Change in Computed Tomography Images of Pentaerythritol Tetranitrate |
Ariana Beste (SNL) |
SAND2024-10454C
Video
SAND2024-09459C
PPTX |
|
1:25 pm |
Deep learning for non-stationary bias correcting of future climate projection |
Shuang Yu (LLNL) |
Video |
PDF |
|
1:50 pm |
Evaluating Probabilistic Deep Learning Methods for Uncertainty Quantification Applied to Bias Correction of Precipitation |
Yannic Lops (LLNL) |
Video |
PDF |
|
Track 2: Topics: AI for Power Systems |
|
Time (MST) |
Title |
Speaker |
Medial/Materials |
|
9:15 am |
Keynote: Sandia AI Strategy & Roadmap |
Jen Gaudioso and Cindy Phillips (SNL) |
SAND2024-11290V Video |
|
9:55 am |
AI for Grid and Energy Overview |
Matthew Reno (SNL) |
SAND2024-11385V Video
SAND2024-10028C
PDF |
|
10:05 am |
AI for Clean Energy Integration |
Joe Azzolini (SNL) |
SAND2024-11068V Video
SAND2024-11067C
PPTX |
|
10:50 am |
AI for Grid Controls |
Miguel Jimenez Aparicio (SNL) |
SAND2024-11173V Video |
|
11:10 am |
Cyber-Physical Threat Detection in the Power Grid with LSTM-based Autoencoders |
Georgios Fragkos (SNL) |
SAND2024-09655V Video
SAND2024-05006C
PPTX |
|
11:35 am |
Reinforcement learning to support the security and resilience of power systems |
Thanh Long Vu (PNNL) |
Video |
PPTX |
|
1:00 pm |
Machine Learning and Data Considerations for Distribution System Model Calibration Tasks |
Logan Blakely (SNL) |
SAND2024-11653V Video
SAND2024-10030PE PDF |
|
1:25 pm |
AI for Grid Resilience |
Samuel T. Ojetola (SNL) |
SAND2024-10161V Video
SAND2024-09924PE PPTX |
|
1:50 pm |
Blast from the Past (2022): Hybrid Deep Reinforcement Learning For Online Distribution Power System Optimization and Control |
Nicholas Corrado (SNL) |
SAND2021-8185C Video |
|
Track 1: Topic A - Scientific Machine Learning |
|
Time (MST) |
Title |
Speaker |
Media/Materials |
|
9:10 am |
Keynote: Variograms for kriging and clustering of spatial functional data with phase variation |
Sebastian Kurtek (OSU) |
Video |
PDF |
|
9:50 am |
Physics-based and Graph-based Machine Learning Models for Surface Property Predictions |
Peter Schindler (NEU) |
Video |
PDF |
|
10:15 am |
Physics-Constrained, Structure-Preserving Machine Learning for Structural Health Assessment of As-Built, As-Deployed Structures |
David Najera-Flores (ATA Engineering, Inc.) |
Video |
PDF |
|
10:50 am |
Neural-ODE Surrogates for Fuel Degradation Processes in Nuclear Waste Repository Simulations |
Caitlin Curry (SNL) |
SAND2024-09887C Video
SAND2024-09887C
PPTX |
|
11:05 am |
Deep Neural Operators as Accurate Surrogates for Shape Optimization: Applications to Airfoils and Hypersonic Waveriders |
Michael Penwarden (SNL) |
SAND2024-10888C Video
SAND2024-10889C
PDF |
|
11:30 am |
Interpretable machine learning for molecular and materials modeling |
Susan Atlas (UNM) |
Video |
|
1:00 pm |
A novel ensemble approach to uncertainty quantification in operator learning |
Ravi G. Patel (SNL) |
SAND2024-10280V Video
SAND2024-09373C
PPTX |
|
1:20 pm |
Unsupervised physics-informed disentanglement of multimodal data |
Elise Walker (SNL) |
SAND2024-09787V Video
SAND2024-09688C
PPTX |
|
1:40 pm |
Neural ODE Hypernetwork Surrogates for Agent-Based Disease Models |
Wyatt Bridgman (SNL) |
SAND2022-9310C Video
SAND2022-9310C
PPTX |
|
2:05 pm |
Machine Learning Surrogate Modeling using Deep Operator Networks for Fuel Degradation Processes in Nuclear Waste Repository Simulations |
Calvin Madsen (SNL) |
SAND2024-10022V Video
SAND2024-09945PE
PPTX |
|
Track 1: Topic B - Computer Vision |
|
2:40 pm |
Leveraging Contrastive Loss for Interpreting Unlabeled Data from Additive Manufacturing |
Anthony Garland (SNL) |
SAND2024-10787C Video
SAND2024-10348C
PDF |
|
3:00 pm |
Characterization of Ion-Induced Damage: Application of Convolutional Neural Networks |
Pranav Rane (Georgia Tech) |
Video |
PPTX |
|
3:20 pm |
Neural-guidance by the Human Ventral Visual Stream Improves Neural Network Robustness |
Zhenan Shao (UIUC) |
Video |
PDF |
|
3:40 pm |
Practical steps to publishing with EAS (Equitably Accessible Science) |
Amelia Henriksen (SNL) |
SAND2024-11878V Video |
|
Track 2: Session A Topic- Reinforcement Learning |
|
Time (MST) |
Title |
Speaker |
Media/Materials |
|
9:10 am |
Keynote: Variograms for kriging and clustering of spatial functional data with phase variation |
Sebastian Kurtek (OSU) |
Video |
PDF |
|
9:50 am |
Blast from the Past (2022): Shortest Path Navigation using Reinforcement Learning |
Tyson Bailey (SNL) |
SAND2022-9967V Video |
|
10:15 am |
An Artificial Intelligent Bot that Hacks Simulated Cyber-Physical Networks in the Power Grid |
Georgios Fragkos (SNL) |
SAND2024-10338V
Video
SAND2024-10121C
PPTX |
|
10:50 am |
Assured Neuro-Symbolic Learning-based Control Subject to Timed Temporal Logic Constraints |
Kyriakos G. Vamvoudakis (GeorgiaTech) |
Video |
PPTX |
|
11:30 am |
Machine/reinforcement learning to teach coordinated wind turbine controllers how to reduce wake losses |
Ken Brown (SNL) |
SAND2024-11727PE Video |
|
1:00 pm |
Hardware Trojan Insertion, Detection, And Benchmarking with Reinforcement Learning |
Amin Sarihi (NMSU) |
Video |
PPTX |
|
1:40 pm |
Accelerating Thin Volume Reduction with Supervised Learning and Multi-Agent Reinforcement Learning |
Steven Owen (SNL) |
SAND2024-10538V Video
SAND2023-05160C PPTX |
|
Track 2: Session B Topic- ML for Trajectories and Pathing |
|
2:40 pm |
Analyzing the Paths of Moving Objects |
Ben Newton (SNL) |
SAND2024-10279C Video |
|
3:20 pm |
Machine Learning Application for Smart Network Traffic Prediction |
Islam Omar (NMSU) |
Video |
PPTX |
|
3:45 pm |
Machine Learning for Practical Real-Time Test Campaign Design |
Zachary McDaniel (Purdue) |
Video |
PPTX |
|
4:05 pm |
Behavioral Segmentation and Clustering of Geospatial Trajectories |
Jessica Jones (SNL) |
SAND2024-10857C Video
SAND2024-10649C
PPTX |
|
Track 1: Topic - Trusted AI |
|
Time (MST) |
Title |
Speaker |
Media/Materials |
|
9:10 am |
Keynote: You Should Give a Tutorial |
Sarah Ackerman (SNL) |
SAND2024-11426V Video
SAND2024-11279C PPTX |
|
9:50 am |
Trust Maturity Model for AI Systems |
Scott Steinmetz (SNL) |
SAND2024-10909O Video
SAND2024-09809C
PPTX |
|
11:20 am |
MADmax: Multi-Agent Trust Dynamics and Influence Maximization |
Asael H. Sorensen (SNL) |
SAND2024-10692V Video
SAND2024-10202PE
PDF |
|
11:40 am |
Zig Zag Persistence as a Measure of Topology Preservation in Temporal Link Prediction |
Marco Campos (SNL) |
SAND2024-11759C Video |
|
1:00 pm |
Keynote: Adjusting for Spatial Correlation in Machine and Deep Learning |
Matt Heaton (BYU) |
Video |
PPTX |
|
1:40 pm |
HaMLET: Human and Machine Learning Effective Teaming |
Kyra Wisniewski (SNL) |
SAND2024-10160V Video
SAND2024-09811C
PPTX |
|
2:05 pm |
Graph attention embeddings as a causal lens in temporal link prediction |
Sarah Simpson (SNL) |
SAND2024-10212C Video
SAND2024-09855C
Video |
|
2:30 pm |
Trusted AI Lightning Talks from Sandia's LDRD Research Programs |
Various Speakers (SNL):
1- David Stracuzzi |
2- Mike Smith |
3-Jeremy Wendt |
4 - John Jakeman |
5- Kyle Neal |
6- Carlos Llosa |
7- Alexander Outkin |
8- Kyra Wisniewski | |
SAND2024-11496V Video1: Defining Trusted AI
SAND2024-11468V Video2: Trustworthiness
SAND2024-11329C Video3: Distance Learning
SAND2024-11656V Video4: CERTANN
SAND2024-11076C Video5: Datadriven Closure Models
SAND2024-10879V Video6: Tensor Decompositions
SAND2024-11950C Video7: Information&PrivacyLoss
SAND2024-10849V Video8: Model Trust in AI |
|
Track 2: Topics - Tools, Processing, and Pipelines for Machine Learning |
|
Time (MST) |
Title |
Speaker |
Media/Materials |
|
9:10 am |
Keynote: You Should Give a Tutorial |
Sarah Ackerman (SNL) |
SAND2024-11426V Video
SAND2024-11279C PPTX |
|
9:50 am |
Designing Large Datasets: Data-Scarce and Stable Deep Generative Models for Turning Sparse Experiments into Big Datasets in Materials Science |
Andreas E. Robertson (SNL) |
SAND2024-09804O Video
SAND2024-09646C PPTX |
|
10:40 am |
Artificial Intelligence for Microelectronics Security and Trust |
Prabuddha Chakraborty (UMaine) |
Video |
PDF |
|
11:20 am |
Arbitrary Autoencoder Injection for Interpretability Experimentation |
Michael Xi (SNL) |
SAND2024-11205C Video |
|
11:40 am |
MatFold: cross-validation protocols to systematically evaluate OOD performance in materials discovery models |
Matthew Witman (SNL) |
SAND2024-10214C Video |
PPTX |
|
1:00 pm |
Keynote: Adjusting for Spatial Correlation in Machine and Deep Learning |
Matt Heaton (BYU) |
Video |
PPTX |
|
1:40 pm |
CrossSim: Sandia's simulator for analog AI accelerators |
Patrick Xiao (SNL) |
SAND2024-10513O Video |
|
2:05 pm |
Mixed CNN-Attention Machine Learning Model for Predicting Gene Regulatory Relationships Across Fungal Species Towards Developing Computational Methods for Defending Against Emerging Pathogenic Fungi |
Laura Weinstock (SNL) |
SAND2024-10546V Video
SAND2024-10235PE PPTX |
|
2:30 pm |
Simplifying ML Pipeline Deployment for the Scientific Community in Different Computing Environments: An Integrated Approach with Clowder, Ray and HuggingFace |
Vismayak Mohanarajan (National Center for Supercomputing Applications) |
Video |
|
|
Track 1: Trusted AI Lightning Talks from Sandia's LDRD Research Programs |
Various Speakers (SNL) |
|
|
Track 1: Topics - Generative AI and Large Language Models |
|
|
Time (MST) |
Title |
Speaker |
Media/Materials |
|
9:10 am |
Keynote: Gen AI Round Table |
Tyler Ganter, Hamilton Link, Lisa Linville, Chris Siefert, Ann Speed, and Scott Thomas Steinmetz (SNL) |
SAND2024-10850O Video |
|
9:50 am |
Automated Attribution to Identified Sources |
Robert G. Abbott (SNL) |
SAND2024-11032C Video
SAND2024-10548C PDF |
|
10:15 am |
Lessons Learned Automating Generation of Malware Metadata Signatures |
Joel Schott (SNL) |
SAND2024-10422V Video
SAND2024-10421PE PDF |
|
10:45 am |
Unveiling Zero Shot Prediction for Gene Attributes Through Interpretable AI |
Avi Sahu (UNM) |
Video |
PDF |
|
11:10 am |
NOLA: Networks as Linear Combination of Low Rank Random Basis |
Hamed Pirsiavash (UC Davis) |
Video |
|
11:35 am |
Inferno: Leveraging large language models with Sandia's Atlas to augment developer understanding of Sandia's Dante Simulation Codebase |
Christopher Symonds & Catherine Appleby (SNL) |
SAND2024-10117V Video
SAND2024-09968C PDF |
|
1:00 pm |
Tadpole: Semantic Search with LLMs |
Sarah Ackerman (SNL) |
SAND2024-11919O Video
SAND2024-11919O PPTX |
|
1:40 pm |
Conditional Diffusion Models for Interlocking Metasurface Design |
Nathan Brown (SNL) |
SAND2024-10010O Video
SAND2024-09712C PPTX |
|
2:15 pm |
Synthetic Data Generation Using GenAI-Based WGAN |
Uma Balakrishnan (SNL) |
SAND2024-11770C Video |
|
Viper Lab - Open Lab Demos, Albuquerque, NM (Sandians Only) |
|
Time (MST) |
Location |
Activity |
Point of Contact |
|
11:00 am - 1:00 pm |
TA I, Bldg. 1008, Rooms 144, 154, 156 |
Demos that include a lot of hands-on experiences that blend AI and XR visit (internal page) mldl.sandia.gov for details |
Demitri Maestas (SNL) |