Lab Partnering Service Discovery
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Title: HPC Application Architect
- Molecular dynamics
- Density Functional Theory Code Development
- Parallel programming (GNU parallel, MPI, OpenMP, PGAS models, etc.)
Hubertus (Huub) van Dam is a computational chemist with expertise in docking and molecular dynamics simulations. In prior work he has collaborated on improving the accuracy of docking calculations by using ab-initio molecular potentials for the electrostatic part of docking scores (DOI: 10.1063/1.2793399). He is currently supporting the National Virtual Biotechnology Laboratory (NVBL) effort to find COVID-19 drug candidates using Autodock 4.2, Dock 6 and DeepDriveMD. He also has extensive expertise in writing and supporting large parallel quantum chemistry packages. Currently, he serves as Testing and Assessment Task Lead on the Exascale Computing Project’s NWChemEx effort. NWChemEx is providing a community infrastructure for computational chemistry that takes full advantage of exascale computing technologies.
Amy Sims, Ph.D. is a Senior Research Scientist in the Chemical and Biological Signatures Division of the National Security Directorate at Pacific Northwest National Laboratory (PNNL) in Richland, WA. She earned her Ph.D. from Vanderbilt University Medical Center and worked with Professor Ralph Baric at the University of North Carolina at Chapel Hill (UNC) during her postdoctoral studies. Dr. Sims spent an additional 15 years at UNC as faculty in a continued collaboration with Dr. Baric to understand the pathogenesis of highly pathogenic human coronaviruses and to identify novel vaccination strategies and therapeutic targets. Dr. Sims has published over 50 peer-reviewed publications on antivirals that are efficacious against human coronaviruses, using reverse genetic platforms to characterize coronavirus protein functions, and how coronaviruses prevent transcription factor nuclear translocation to regulate host gene expression, and recently joined PNNL to continue a decade long collaboration on the use of computational modeling and bioinformatics approaches in analyses of kinetic ‘omics data from studies of severe acute respiratory syndrome coronavirus 2003 (SARS-CoV 2003) and Middle East respiratory syndrome coronavirus (MERS-CoV) infected samples. The overall goal of her research is to understand the detailed molecular mechanisms by which CoVs manipulate host pathways and processes to evade the innate immune response and to enhance viral replication and spread.
Michael Connolly is a Principal Scientific Engineering Associate at the Molecular Foundry at Lawrence Berkeley National Laboratory and an organic chemist with 20+ years of expertise in combinatorial and automated synthesis methods and nanomaterial discovery. His research focus is the development of combinatorial discovery technologies and new biopolymer nanomaterials. He has developed a class of bio-inspired polymer called ‘peptoids’ that have found utility in drug discovery, drug delivery, diagnostics, and materials science. Key contributions included the development of new synthetic methods, new sequencing, and characterization methods for peptoids.
Additional information available at this link.
COVID-19-related research: "Scientists Aim Gene-Targeting Breakthrough against COVID-19" (cellular delivery system/anti-viral agent)
Wah Chiu received his BA in Physics and PhD in Biophysics from the University of California, Berkeley. He is the Wallenberg-Bienenstock Professor and a professor in the Department of Bioengineering, Department of Microbiology and Immunology and the SLAC National Accelerator Laboratory at Stanford University. He is a pioneer in methodology development for electron cryo-microscopy. His work has made multiple transformational contributions in developing single particle electron cryo-microscopy as a tool for the structural determination of molecular machines at atomic resolution.
For three decades, Dr. Chiu directs a NIH funded 3DEM Resource Center. He has solved many cryo-EM structures including viruses, chaperonins, membrane proteins, ion channels, cytoskeleton protein complexes, protein-RNA complexes, DNA and RNA in collaboration with many scientists around the world. His 3DEM Resource Center continues to establish high standard testing and characterization protocols for cryoEM instrumentation and to develop new image processing and modeling algorithms for cryo-EM structure determination.
Dr. Chiu’s research, collaboration and training efforts have been recognized by his elected membership to the Academia Sinica, Taiwan (2008), and the United States National Academy of Sciences (2012), in addition to several honors including the Distinguished Science Award from the Microscopy Society of America (2014) and the Honorary Doctorate of Philosophy from the University of Helsinki, Finland (2014).
Title: Computational Scientist
- AI driven multi-omics data analysis including deep sequence analysis and multi-modal clustering
- AI driven material design using graph representation
- Causal analysis and uncertainty quantification using deep learning
- Extreme scale AI using high performance computing and streaming analysis
Shinjae Yoo has developed various fundamental AI technologies including novel machine learning algorithm design and applied them to a broad spectrum of scientific application area including medical and computational chemistry. Yoo also has been doing not only prototype demonstration but also bring such prototype into the production deployment using cloud and HPC systems. Yoo has published over 100 papers including top tier conferences and journals and is interested in social impact research.
Title: Chair, Computation and Data-Driven Discovery
- High-performance and Distributed Computing
- High-throughput and scalable infrastructure for drug discovery
- Machine learning enhanced high-performance computing
Shantenu Jha’s research interests converge at the intersection of high-performance distributed computing and computational and data-driven science. His current interests include system software, algorithms and methods to enhance the performance of HPC computations using machine learning methods. Dr. Jha leads the RADICAL-Cybertools project, a suite of middleware building blocks used to support large-scale science and engineering applications. In addition to applying these advances for drug discovery and design for COVID-19, Jha leads Brookhaven Lab’s efforts on two Exascale computing projects -- CANDLE and ExaWorks.