Accomplishments

*Title*	Description/More Information
Using LLMs to generate code using Kokkos	Chris Siefert from Sandia National Laboratories gave this talk at Sandia 2025 Machine Learning/Deep Learning Workshop August 14^th, 2025.
Transforming measurable signals to informative intrusive data for continuous monitoring of physical assets	Tian Yu Yen from Sandia National Laboratories gave this talk at Sandia 2025 Machine Learning/Deep Learning Workshop August 14^th, 2025. Description: Utilize transformer neural network architecture to convert measurable time series data into informative time series data only obtainable via an intrusive approach.
Panel Discussion on LLMs and Generative AI at Sandia	Siva Rajamanickam from Sandia National Laboratories served on this panel discussion at Sandia 2025 Machine Learning/Deep Learning Workshop August 14^th, 2025.
Banyan-ingest – Challenges of Processing Documents for LLMs	Yang Ho from Sandia National Laboratories gave this talk at Sandia 2025 Machine Learning/Deep Learning Workshop August 14^th, 2025. Description: The talk went over banyan-ingest the tool as well as highlighting document processing results.
Learning to Trust: Adaptive Multisource Multimodal Bayesian Data Fusion for Forensic Blast Analysis	Lekha Patel from Sandia National Laboratories gave this talk at the Sandia 2025 Machine Learning/Deep Learning Workshop August 13th, 2025.
Sarah Ackerman served as the Co-Chair for the Sandia 2025 Machine Learning/Deep Learning Workshop	The workshop aims to provide a platform for members of the MLDL research community to network, learn, and share their work allowing participants to gain in-depth exposure to the field of MLDL.
Chris Siefert served on the ML/DL Hackathon Organizing Committee for the Sandia 2025 Machine Learning/Deep Learning Workshop	Chris organized and provided one of the challenge problems on radioisotope identification.
Imperfect Recognition: A Study of OCR Limitations in the Context of Scientific Documents	Chinmay Sahasrabudhe, Yang Ho, Nick Winovich, and Siva Rajamanickam submitted a publication and gave talks at the IEEE International Parallel & Distributed Processing Symposium May 29th, 2025 and the Trillion Parameter Consortium meeting July 31st, 2025.
Containerization of a Machine Learning Pipeline	Dalton Cole from Sandia National Laboratories gave this talk at the Sandia 2025 Machine Learning/Deep Learning Workshop July 23rd, 2025. Description: The talk described how to containerize a machine learning pipeline using docker. The tutorial covered the creation of docker files and corresponding scripts for ML/DL data processing, model training, and model inference.
Data Flow and GenAI Research: Convergence of HPC and AI Simulations	Siva Rajamanickam from Sandia National Laboratories gave this invited talk at Oak Ridge National Laboratory July 15th, 2025.
Scaling AI for Scientific Discovery: Faster Kernels, Efficient Models, Better Physics	Chinmay Sahasrabudhe from Sandia National Laboratories gave this talk as part of our series, BANYAN Guest Seminars June 16th, 2025. Description: The talk discussed common limitations discovered in evaluations of prominent optical character recognition (OCR) tools in the context of scientific document analysis, as well as automatic evaluation of extraction output and document elements to guide banyan-ingest, a general-purpose document processing tool.
Using Open Source and Proprietary models for Parallel Code Generation	Siva Rajamanickam from Sandia National Laboratories gave this talk at the 2024 Chesapeake Large-Scale Analytics Conference.
Artificial Intelligence Safety Institute Red Teaming Exercise	A joint Sandia and Lawrence Livermore team successfully performed an artificial intelligence large language model red teaming pilot. The pilot focused on biosafety with the AI Safety Institute of the Department of Commerce, as requested in an October 2024 National Security Memo.
Patent submitted 2/7/2025	Large language models (LLMs) are prone to producing incorrect information, which makes them difficult to use for high consequence decision making. The team developed methods that use knowledge graphs to provide LLMs with trusted information and to automatically check that the answers that the LLMs produce are correct.
Computing Platform Engineering: Creating a Converged HPC & Cloud Computing Environment for the Future	Kevin Pedretti from Sandia National Laboratories gave this invited talk at the CEA NNSA Computational Science Collaboration Meeting May 5th-8th, 2025.