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.
Charles Macal applies computational modeling and simulation tools to complex systems to solve problems in a variety of fields, including energy and national security.
He is the chief scientist for the Argonne Resilient Infrastructure Initiative, and is a principal investigator for the development of the widely used Repast agent-based modeling toolkit.
He has Appointments at the University of Chicago Computation Institute and the Northwestern-Argonne Institute for Science and Engineering. He is adjunct professor at the University of Chicago, where he teaches a course on Complex Adaptive Systems for Threat Management and Emergency Preparedness.
He is a registered professional engineer in the State of Illinois and holds software copyrights for two systems: ELIST (Enhanced Logistics Intra-theater Support Tool) and EMCAS (Electricity Market Complex Adaptive System).
- B.S. Purdue University, 1974
- M.S., Purdue University, 1975
- Ph.D., Northwestern University, 1989
Awards, Honors and Memberships
- Association for Computing Machinery, Transactions on Modeling and Computer Simulation, Area Editor for Agent-based Modeling
- Society for Computer Simulation International, Simulation Journal, Associate Editor
Thomas Schenkel is a physicist and senior scientist at Lawrence Berkeley National Laboratory, where he is the interim Director of the Accelerator Technology and Applied Physics Division (http://atap.lbl.gov/). Thomas received his Ph.D. in physics from the Goethe University in Frankfurt. Following time as a postdoc at Lawrence Livermore National Laboratory, he joined Berkeley Lab. His research interests include novel accelerator concepts, materials far from equilibrium, exploration of fusion processes, and spin qubit architectures. Thomas also teaches a graduate course on particle accelerators at UC Berkeley.
Thomas worked on variations of time-of-flight mass spectrometry to characterize the environment of bio-molecules as a postdoc. This theme has now come up in the current Covid-19 crisis with new ideas for mass spectrometry and imaging of viruses in droplets.
COVID-19-related research: "Laser, Biosciences Researchers Combine Efforts to Study Viruses in Droplets"
Areas of expertise: accelerators, fusion, lasers, quantum, spin qubits
Haruko Wainwright received her MS in nuclear engineering (2006), MA in statistics (2010), and PhD in nuclear engineering (2010) at University of California, Berkeley. Her initial research interest was to investigate the environmental impact of nuclear waste and nuclear weapon productions. Her PhD dissertation focused on Bayesian geostatistical inverse modeling for subsurface characterization at the uranium-contaminated DOE Hanford site. Since then, she has broadened her research interest to various environmental problems, including Arctic ecosystem responses to climate change, groundwater contamination, and deep-subsurface CO2 storage. In addition to working in many interdisciplinary projects, she is a deputy lead of the site application thrust in the Advanced Simulation Capability for Environmental Management project, leading the site application at the Savannah River Site F-Area. She is also on the leadership team of Institute for Resilient Communities, which aims to prepare communities for radiological and other disasters through research, education and outreach activities.
For more information: https://eesa.lbl.gov/profiles/haruko-murakami-wainwright/
COVID-19-related research: "Using Machine Learning to Estimate COVID-19âs Seasonal Cycle"
Ben Brown is a statistical scientist in the Environmental Genomics and Systems Biology division within Berkeley Labâs Biosciences Area. He specializes in the development of novel machine algorithms, usually for the biological and environmental sciences at Berkeley Lab. His group develops âthird-waveâ learning algorithms that combine the interpretability and reliability of classical statistics with the predictive performance of deep learning. They specialize in designing learning paradigms for complex, high-dimensional systems that enable accurate uncertainty quantification, model discovery, feature selection, and inference. Dr. Brown's expertise include statistics, machine learning, deep learning, and artificial intelligence.
COVID-19-related research: "Using Machine Learning to Estimate COVID-19's Seasonal Cycle". Other principal investigators include: Eoin Brodie, Nicola Falco, Dan Feldman, Zhao Hao, Chaincy Kuo, Joshua Ladau, and Haruko Wainwright.
Dr. Robert O’Brien is an internationally recognized Principal Nuclear Scientist/Engineer who has focused his career on the development of advanced materials and energy systems in addition to the manufacturing processes to produce materials for harsh environments Dr. O’Brien received a PhD in the nuclear engineering and physics of radioisotope and nuclear power / propulsion systems for space exploration from the University of Leicester in the United Kingdom. Under his PhD research project, Dr. O’Brien proposed the use of americium-based radioisotope thermoelectric generators (RTGs) and developed Spark Plasma Sintering (SPS) Electric Field Assisted Sintering Techniques (EFAST) for the encapsulation of nuclear materials for both RTGs and nuclear reactor fuels. Dr. O’Brien also received a Masters degree in Physics with Space Science and technology from the University of Leicester. Dr. O’Brien’s research and programmatic management experience in advanced manufacturing of harsh environment materials, space systems and instrumentation design/development, defense systems, nuclear fuel performance, nuclear instrumentation, nuclear safety, irradiation testing, radioisotope source design, and nuclear power system design and development.
Dr. O’Brien currently serves as the Director of Advanced Manufacturing for the Department of Energy’s Idaho National Laboratory (INL). Under this role, Dr O’Brien’s leadership extends across all of the Directorates of the laboratory; Energy & Environment Science & Technology, Nuclear Science & Technology, National & Homeland Security, Materials & Fuels Complex, Advanced Test Reactor, and Industry Engagement.
Title: Assistant Computational Scientist
- Scientific literature processing to rapidly find protein-protein interaction candidates
- AI-based platform to accelerate discovery of novel drug compounds
- Querying and filtering interface for users to efficiently scan tens of thousands of sources
Since joining Brookhaven National Laboratory in 2018, Carlos X. Soto has been an active member of the Machine Learning Group, where he has contributed extensively toward large-scale scientific data extraction from published literature using natural language processing (NLP) techniques applied to areas such as functional genomics, drug discovery, and government reports. His contributions to machine learning for the integration of biological genomics data helped prompt an ongoing partnership with Oak Ridge National Laboratory to use NLP techniques to accelerate COVID-19 drug discovery. In 2019, Soto was part of the Brookhaven team awarded one of only two Nuclear Threat Initiative (NTI) Nuclear Security Index Challenge grants. The work, Towards a Predictive Nuclear Security Threat Model, aims to create a predictive model by integrating NTI Index data into machine learning and sentiment analysis. Presently, his work on COVID-related projects focuses on providing domain scientists with powerful new computational tools to identify patterns and insights in large volumes of documents, in particular relating to potential drug compound candidates.
Mike's research interests are in mathematical modeling of environmental systems and quality, uncertainty analysis, value-of-information decision analysis, water-energy integrated assessment, and sensor-data fusion. Mike has a PhD in Civil and Environmental Engineering and an MS degree in Engineering and Public Policy from Carnegie Mellon University. He also has MS and BS degrees in Mechanical Engineering from UCLA. Mike is a California-licensed Professional Engineer (Civil), and has worked at an environmental engineering firm where he conducted environmental health risk assessments. He is Leader of the Sustainable Energy Systems Group and former Leader of the Airflow and Pollutant Transport Group (Indoor Environment Dept.). Mike has been at LBNL since 1998.
COVID-19-related research: "New Research Launched on Airborne Virus Transmission in Buildings"
Rick Stevens is Argonne’s Associate Laboratory Director for Computing, Environment and Life Sciences.
Stevens has been at Argonne since 1982, and has served as director of the Mathematics and Computer Science Division and also as Acting Associate Laboratory Director for Physical, Biological and Computing Sciences. He is currently leader of Argonne’s Exascale Computing Initiative, and a Professor of Computer Science at the University of Chicago Physical Sciences Collegiate Division. From 2000-2004, Stevens served as Director of the National Science Foundation’s TeraGrid Project and from 1997-2001 as Chief Architect for the National Computational Science Alliance.
Stevens is interested in the development of innovative tools and techniques that enable computational scientists to solve important large-scale problems effectively on advanced scientific computers. Specifically, his research focuses on three principal areas: advanced collaboration and visualization environments, high-performance computer architectures (including Grids) and computational problems in the life sciences. In addition to his research work, Stevens teaches courses on computer architecture, collaboration technology, virtual reality, parallel computing and computational science.
Dr. Robert Rallo is a scientist in the Advanced Computing, Mathematics, and Data Division at the Pacific Northwest National Laboratory.
Prior to joining PNNL, he was an Associate Professor in Computer Science and Artificial Intelligence and Director of the Advanced Technology Innovation Center (ATIC) at the Universitat Rovira i Virgili in Catalonia. Dr. Rallo served as chair for the Modeling WG in the EU NanoSafety Cluster (2013-2016) and as the EU co-chair of the US-EU Nano-Dialogue Community of Research on Predictive Modeling and Health (2013-2015). He served also as reviewer for research organizations such as the European Research Council, Horizon2020, COST and the NWO Research Council for Earth and Life Sciences (ALW).
Dr. Rallo's research interests are in data-driven analysis and modelling of complex systems of industrial, environmental and social relevance.
Tim Klett is a Cyber Security Analyst within the Infrastructure Assurance and Analysis Division at the Idaho National Laboratory (INL). He has over 20 years of experience in working with information technology solutions for both the Department of Energy (DOE) and the Department of Homeland Security (DHS). His current work includes overseeing the design, development, and security of several mission-critical systems utilized by DHS. Tim's current research areas include critical infrastructure dependencies and interdependencies and cyber/physical impacts. Tim is currently pursuing a PhD in Computer Science from the University of Idaho, earned his M.S. degree in Computer Science from the Illinois Institute of Technology in 2004, and is a Certified Information Systems Security Professional (CISSP).
Ryan Hruska is a Senior Critical Infrastructure and Mission Assurance Research Lead within the Infrastructure Assurance and Analysis Division at the Idaho National Laboratory (INL). He has over 15 years of experience developing innovative technology solutions for the Department of Energy (DOE), Department of Homeland Security (DHS), and Department of Defense (DOD). His current research includes leading the develop of the All Hazards Analysis (AHA) Framework and Essential Function Analysis Capability (EFAC) for mission assurance modeling. His research interests include machine learning, data analysis, critical infrastructure modeling, cyber-security, remote sensing, and decision support systems. He has a M.S. in both Computer & Environmental Sciences, which includes a Geographic Information Systems Certificate, and a B.S. in Cartography from the University of Idaho. In addition, he is currently pursuing a PhD in Computer Science. Mr. Hruska is a Certified Information System Security Professional (CISSP) and current member of the IEEE Computer & Computational Intelligence Societies, Association for Computing Machinery (ACM), and has served as an adjunct professor for remote sensing in Idaho State University’s Department of Geosciences.