Five Users Win NERSC Early Career Achievement Awards

Five researchers have been awarded NERSC Early Career Achievement Awards, highlighting remarkable work in high performance computing (HPC) for their particular areas of science.

Announced at the January NERSC User Group meeting, the NERSC Early-Career Achievement Awards recognize work that has had or is expected to have an exceptional impact on scientific understanding, engineering design for scientific facilities, or a broad societal impact.

Two honorees, Ronald Kouski and Vinicius Mikuni, were awarded 2024 High-Impact Scientific Achievement Awards, while three more, Kyla de Villa, Massimiliano Pasini, and Axel Huebl, were awarded 2024 NERSC Early Career Awards for Innovative Use of High Performance Computing.

2024 High-Impact Scientific Achievement Award

Ronald Kouski
Graduate Student
Iowa State University
Department of the Earth, Atmosphere, and Climate

Ronald Kouski's groundbreaking research has shed new light on the influence of African easterly waves (AEWs) on tropical cyclone (TC) genesis and landfall in the Atlantic, uncovering that TC frequency and spatial distribution significantly change in the absence of AEWs. His analysis of a 50-member ensemble of TC-permitting climate simulations revealed a 16-44% increase in landfall TC activity under AEW suppression, linked to enhanced mid-tropospheric humidity and a pronounced westward shift in TC formation in the Atlantic. Using NERSC’s Perlmutter supercomputer, Kouski ran 500 simulations, using approximately 10,000 CPU node hours and generating 300 TB of data to achieve statistically robust conclusions.

Vinicius Mikuni
NESAP Post-Doctoral Fellow
NERSC
Lawrence Berkeley National Laboratory

Vinicius Mikuni is revolutionizing the application of deep learning in particle, nuclear, and astrophysics by developing cutting-edge solutions to complex challenges, particularly in the realm of denoising or "unfolding" for differential cross-section measurements. His groundbreaking methodologies, encapsulated in the widely-used PyPI package OmniFold, have enabled unprecedented scientific insights and fostered collaborations across experimental, theoretical, and computational domains. Using NERSC's Perlmutter, Mikuni has innovated computational workflows, using GPUs to train thousands of networks for robust uncertainty quantification and introducing a foundation model that doubles training speed without compromising performance.

NERSC Early Career Awards for Innovative Use of High Performance Computing

Kyla De Villa
PhD Student
University of California, Berkeley
Department of Earth and Planetary Science

Kyla de Villa has made groundbreaking contributions to computational material science through her discovery of a new state of matter, double superionicity, using GPU-accelerated molecular dynamics simulations at NERSC. Published in Nature Communications, de Villa’s work revealed this hybrid state where hydrogen and another heavier nucleus become mobile under extreme conditions, significantly advancing our understanding of the interiors of Uranus and Neptune and their magnetic field generation. She independently performed all simulations and analyses, overcoming rigorous challenges to demonstrate the robustness and planetary relevance of her findings. Beyond her research, de Villa is a dedicated mentor, educator, and community builder, revitalizing peer mentoring programs, leading STEM outreach efforts, and organizing graduate seminars, fostering a supportive academic environment.

Massimiliano Pasini
Staff Data Scientist
Oak Ridge National Laboratory
Computational Coupled Physics Group

Massimiliano Lupo Pasini’s groundbreaking contributions to scientific machine learning, particularly through the development of HydraGNN, exemplify innovative use of high-performance computing (HPC). His work achieved unprecedented scalability, processing 154 million atomistic structures with near-linear strong scaling on systems like Perlmutter and Frontier, while addressing critical challenges in data management and energy optimization. By integrating multitask learning, uncertainty quantification, and energy-efficient hyperparameter optimization into HydraGNN, Pasini set new benchmarks in computational efficiency and accuracy for materials science applications. His leadership in using NERSC resources and fostering collaborations across national laboratories underscores his commitment to advancing HPC and delivering impactful solutions across scientific domains.

Axel Huebl
Research Scientist
Lawrence Berkeley National Laboratory
Accelerator Technology & Applied Physics Division

Axel Huebl’s groundbreaking contributions to high-performance computing (HPC) have pushed the boundaries of accelerator modeling and computational workflows, making him a highly deserving recipient of the 2024 NERSC Early Career Achievement Award. His leadership in developing GPU and machine learning methods in the WarpX and ImpactX particle-in-cell codes and the pyAMReX Python interface has not only advanced the capabilities of block-structured adaptive mesh refinement simulations, but also benefited a wide array of scientific applications. By integrating GPU-accelerated simulations with in-the-loop artificial intellingence and machine learning methods, Huebl achieved a remarkable 750x speed-up in a data-driven design workflow for future particle accelerators.  His work was recognized with the PASC24 Conference Best Paper Award. Huebl’s innovative synthesis of computational techniques exemplifies excellence in HPC and ensures future scientific productivity at an unprecedented scale.