Nathan Nichols, ANL Nathan Nichols is an Assistant Computer Scientist in the AI/ML group at the Argonne Leadership Computing Facility. He earned his B.S. in Chemistry, Physics, and Mathematics from Hartwick College and a Ph.D. in Materials Science from the University of Vermont with a heavy focus on condensed matter theory. Nathan has made contributions to a diverse set of scientific software projects, including Path Integral Quantum Monte Carlo, Analytic Continuation via Evolutionary Computation, and High Energy Physics Event Generator software. His work primarily focuses on developing performant GPU kernels using CUDA, HIP, and SYCL. Recently, Nathan has been involved in the quantization of Large Language Models to enhance performance and reduce memory usage on target GPUs. His research and professional interests center around optimizing scientific software and AI/machine learning workloads for maximum performance.