Early Career HPC Achievement Awards

The NERSC High Performance Computing (HPC) Achievement Awards started in 2013 as a way to recognize extraordinary contributions from scientists who use NERSC in their research. In 2018, the awards were refocused exclusively on promising early career researchers.

Categories

Today, the NERSC Early Career HPC Achievement Awards are given in two categories, namely, Innovative Use of HPC and High Impact Scientific Achievement.

NERSC Early Career Award for Innovative Use of High Performance Computing

This award honors the innovative use of NERSC’s HPC resources. Examples include introducing HPC to a new science domain or a novel use of HPC resources. Anything that puts a fresh perspective on HPC or presents a new way to solve a problem is considered.

NERSC Early Career Award for High Impact Scientific Achievement

This award recognizes work that has had or is expected to have, an exceptional impact on scientific understanding, engineering design for scientific facilities, and/or a broad societal impact.

Eligibility

Nominations for the NERSC Early Career HPC Achievement Awards can be made by NERSC users (including self-nominations), project principal investigators (PIs), project managers, PI proxies, and Department of Energy (DOE) program managers. Nominees must be NERSC users who were students or who received their degrees within the previous five years and whose research was significantly based on work performed using the center’s facilities and services. Any combination of NERSC computational systems, storage systems, edge services, and/or HPC services qualify.

Judging

Selections are made by members of the NERSC Users’ Group Executive Committee and NERSC staff.

Awards

Recipients are awarded computing time from the NERSC Director’s Reserve, highlighted in NERSC press releases, and invited to present their work in a special seminar.

Past Recipients

High Impact Science Achievement

2022-23

Fangzhou Zhao (UC Santa Barbara) for "working on electronic, optical, and topological properties of materials, was recognized for developing a first-principles computational formalism to calculate the rate of trap-assisted Auger-Meitner (TAAM) recombination."

Bikash Kanungo (University of Michigan) for "developing a data-driven approach to improved exchange-correlation functionals in density functional theory (DFT), a method commonly used in chemical sciences, materials sciences, and other fields, via an accurate solution to the inverse DFT problem."

Kyle Bushick (University of Michigan) for "developing a novel computational methodology to calculate the Auger-Meitner recombination rates in silicon using predictive atomistic calculations, including the ability to robustly include interactions between electrons and atomic vibrations."

2021-22

Andi Gu (Havard University) for “developing and applying GIGA-Lens, a fast Bayesian inference tool used in strong gravitational lens modeling to enhance the study of dark matter.”

Chirag Jain (Georgia Institute of Technology) for “developing and applying FastANI, a computational method of measuring relatedness between two genomes.”

Bin Ouyang (UC, Berkeley and Berkeley National Laboratory) “for designing a new generation of commercialized cathode materials.”

Giulia Palermo (UC, Riverside) “for unraveling the mechanistic basis of CRISP-Cas9-mediated genome editing.”

2020

Samuel Kachuck (University of Michigan) for “improving ice sheet and Earth system models to enable accurate projections of future sea level rise.”

Abigail Polin (Caltech and Carnegie Observatories) for “providing new insight into the origin and nature of Type 1a supernova.”

David Vartanyan (UC Berkeley) for “contributions to unraveling the characteristics and mechanisms of core-collapse supernova explosions.”

2018-19 Early Career

Haoming Liang (West Virginia University) for “developing new insights, based on novel entropy-based diagnostics, into plasma simulations.”

Gareth Roberg-Clark (University of Maryland) for “advancing our understanding of the fundamental physics of thermal conduction and applying insight into the intracluster medium of galaxy clusters.”

Xie Zhang (UC, Santa Barbara) for “producing essential insights in recombination mechanisms in hybrid perovskites based on cutting-edge first-principles simulations.”

2017 

Qimin Yan, Jie Yu, Santosh K. Suram, Lan Zhou, Aniketa Shinde, Paul F. Newhouse, Wei Chen, Guo Li, Kristin A. Persson, John M. Gregoire, and Jeffrey B. Neaton (UC Berkeley, Lawrence Berkeley National Laboratory, California Institute of Technology) “for using NERSC resources to help speed the discovery of commercially viable catalysts that can be used to produce solar fuels.”

2017 Early Career

Badri Narayanan (Argonne National Laboratory) for “developing atomistic models to understand reactive interfaces of energy applications.”

2016 

Charles Koven and William Riley (Berkeley Lab’s Climate and Ecosystem Sciences Division) and David Lawrence (National Center for Atmospheric Research) for “using an Earth system model to demonstrate the atmospheric effect of emissions released from carbon sequestered in melting permafrost soil.”

2016 Early Career

Nathan Howard, MIT Plasma Science and Fusion Center, for “pioneering computational work in plasma turbulence simulations.”

2015 

Berkeley Lab’s BELLA (Berkeley Lab Laser Accelerator) team for “its work using NERSC resources to design and configure the world’s most powerful compact particle accelerator.”

2015 Early Career

Ken Chen, Postdoctoral Researcher at UC Santa Cruz, for his “study of the explosion of very massive stars in multiple dimensions.”

2014 

The Planck Collaboration for “the most detailed map ever made of the Cosmic Microwave Background – the remnant radiation from the Big Bang that refined some of the fundamental parameters of cosmology and physics.”

2014 Early Career

Victor Ovchinnikov, Harvard University, for “outstanding contributions to the field of computational modeling of conformational transitions in large biological molecules.”

2013

Jeff Grossman and David Cohen-Tanugi (Massachusetts Institute of Technology) for “developing a new approach for desalinating seawater using sheets of graphene, a one-atom-thick form of the element carbon.”

2013 Early Career

Tanmoy Das, Postdoctoral Researcher at Los Alamos National Laboratory for “computational work to understand fundamental materials aspects in three different areas.”

Innovative Use of HPC

2022

Youssef Elmougy (Georgia Institute of Technology) for “introducing an innovative approach to achieve large-scale asynchronous graph processing.”

2022

Anthony Kremin (Berkeley Lab) for “developing and implementing a pioneering approach to enable data processing from the Dark Energy Spectroscopic Instrument (DESI), helping fulfill DESI's mission to construct the world’s largest 3D map of the universe and allow fundamental tests of cosmological physics.”

2020 

Miha Muskinja (Berkeley Lab) for “developing a new software infrastructure that allows researchers connected to the ATLAS particle physics experiment at CERN to use HPC systems efficiently and effectively.”

2020 Sierra Villarreal (Argonne National Laboratory) for “developing innovative workflows to enable using HPC at scale in support of the LSST Dark Energy Science Collaboration.”

2018-19

Innovative Use of HPC was combined with High Impact Awards this year.

2017 

Abhinav Bhatele, Jae-Seung Yeom, Nikhil Jain, Chris J. Kuhlman, Yarden Livnat, Keith R. Bisset, Laxmikant V. Kale, and Madhav V. Marathe (Virginia Tech University, Lawrence Livermore National Laboratory, University of Utah, University of Illinois at Urbana-Champaign) for “using NERSC resources to demonstrate unprecedented scaling for simulating infectious diseases over realistic national-scale social networks.”

2017 Early Career

Thomas Heller (Friedrich Alexander University Nuremberg) for “demonstrating that an asynchronous, massively parallel tasking runtime system (HPX) can be used to harness billions of tasks for a scalable hydrodynamics simulation of the merger of two stars.”

2016 

Scott French (UC Berkeley) for “creating a unique 3D scan of the Earth’s interior that resolved some long-standing questions about mantle plumes and volcanic hotspots using one of the first production codes to use UPC++: a new partitioned global address space programming system developed by researchers in the DEGAS group at Berkeley Lab.”

2016 Early Career

Min Si (University of Tokyo & Argonne National Laboratory) for “developing novel system software in the context of MPI-3 one-sided communication.”

2015 

SPOT Suite Team (Berkeley Lab) for “transforming the way scientists run their experiments and analyze data collected from DOE light sources.”

2015 Early Career

Taylor Barnes (California Institute of Technology) for “outstanding methodological advances that enhance our ability to harness large-scale computational resources to solve important chemical problems. ”

2014

Jean-Luc Vay (Berkeley Lab’s Accelerator and Fusion Research Division) for “developing innovative algorithms that greatly improved the use of high performance computing to advance the simulation of charged particles, beams and plasmas.”

2014 Early Career

Anubhav Jain (Berkeley Lab) for “creating innovative HPC workflow tools that enable scientific discovery in materials research.”

2013

Peter Nugent (Berkeley Lab) and the Palomar Transient Factory Team (Caltech) for “detection of transient events that leads to a greater understanding of astrophysical objects like supernovae, active galaxies and gamma-ray bursts, among a variety of other known and unknown cosmic phenomena.”

2013 Early Career

Edgar Solomonik (University of California, Berkeley) for “developing novel algorithms for massively parallel tensor contractions and applying them to quantum chemistry problems, specifically coupled-cluster theory, which is the de facto standard for important scientific applications in the thermochemistry of combustion and excited-states of systems where density-functional theory (DFT) breaks down.”

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