Lab Partnering Service Discovery

Title: HPC Application Architect

Expertise:

• Docking
• 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.

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.

Title: Assistant Computational Scientist

Expertise:

• 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.

Title: Deputy Director

Expertise:

• Optimal Design of Experiments under Uncertainty
• Machine Learning
• Computational Physics
• Statistical Physics

Prior to joining Brookhaven National Laboratory in 2017, Francis “Frank” Alexander spent nearly 20 years at Los Alamos National Laboratory, finishing his tenure as the acting division leader of the lab’s Computer, Computational, and Statistical Sciences (CCS) Division. At Los Alamos, he grew in several leadership roles, including serving as deputy leader of CCS Division’s Information Sciences Group and leader of the Information Science and Technology Institute. Alexander was introduced to the DOE national laboratory complex during his postdoctoral work with Los Alamos’ Center for Nonlinear Studies and the Institute for Scientific Computing Research at Lawrence Livermore National Laboratory. He also was a research assistant professor at Boston University’s Center for Computational Science. Alexander has led many research projects and has published more than 50 papers in peer-reviewed journals. In addition to leading Brookhaven’s artificial intelligence and machine learning strategy effort, Alexander currently serves as project director of the multi-laboratory ExaLearn Co-design Center for Exascale Machine Learning Technologies, part of the Exascale Computing Project. He also leads various projects involving optimal experimental design, including for biological systems.

Arvind Ramanathan is a computational biologist in the Data Science and Learning Division at Argonne National Laboratory and a senior scientist at the University of Chicago Consortium for Advanced Science and Engineering (CASE). His research interests are at the intersection of data science, high performance computing and biological/biomedical sciences.

His research focuses on three areas focusing on scalable statistical inference techniques: (1) for analysis and development of adaptive multi-scale molecular simulations for studying complex biological phenomena (such as how intrinsically disordered proteins self assemble, or how small molecules modulate disordered protein ensembles), (2) to integrate complex data for public health dynamics, and (3) for guiding design of CRISPR-Cas9 probes to modify microbial function(s).

He has published over 30 papers, and his work has been highlighted in the popular media, including NPR and NBC News. He obtained his Ph.D. in computational biology from Carnegie Mellon University, and was the team lead for integrative systems biology team within the Computational Science, Engineering and Division at Oak Ridge National Laboratory. More information about his group and research interests can be found at http://​ramanathanlab​.org.

Raga is a member of the technical staff at Sandia. She is a molecular, developmental and, most recently, computational biologist with a background in regulation of gene expression and cell fates in mammalian systems. Her main area of focus is characterizing, monitoring, and engineering of molecular pathways within cells to alter their phenotypic outcomes. She combines the use of bioinformatics, modeling, and machine learning with experimental biology to dissect the mechanisms by which cellular responses can be programmed, both intrinsically and by external influences.

Raga’s current projects include enhancing antimicrobial and immunomodulatory activity of mesenchymal stromal cells through CRISPR-based gene modulation, prediction of CRISPR efficiency across cell types, and generating optogenetic (light-activatable) neurons and neuron-like cells for interfacing with low-power computing devices.

She received her Bachelor of Arts in Natural Sciences (Biochemistry) from the University of Cambridge, UK, in 2004. She then went on to receive her Ph.D. in Biochemistry, Cell and Molecular Biology (laboratory of Dr. W. Lee Kraus) at Cornell University, Ithaca, NY, in 2010.

Biography

Thomas Brettin’s current work focuses on the development of projects at the intersection of genomics, artificial intelligence, and leadership scale computing as well as providing ongoing direction on existing bioinformatics at Argonne National Laboratory and the University of Chicago. Active open projects include the NIH funded Bacterial and Viral Bioinformatics Resource Center, the DOE-NIH funded Joint Design of Advanced Computing Solutions for cancer, and the DOE funded exascale computing deep learning application called CANDLE. Thomas also leads projects funded by the defense community. Thomas has been actively working towards bringing genomics based computational approaches to clinical research settings. More recently, initiating and executing projects that align with strategic goals of applying artificial intelligence more broadly to a range of scientific applications.

Over the past two decades, he has led several large genomics research activities that included laboratory and computational projects. These include associating genetic markers to human diseases, using genetic markers for fine resolution identification of microbial pathogens, sequencing pathogen genomes, and comparative analysis of genomic sequences. He also served as a full-time advisor on the Defense Threat Reduction Agency’s Transformational Medical Technologies program involving bioinformatics integration across several sites around the country to identify and characterize viral and bacterial pathogens in detect to treat scenarios.

Education

Michigan State University, M.S., 1994

Michigan State University, B.S., 1987

Synergistic Activities

Program Committee: 2018-2019 International Workshop on Data Management and Analytics for Medicine and Healthcare 

Biography

Dr. Ian Foster is the Director of Argonne’s Data Science and Learning Division, Argonne Senior Scientist and Distinguished Fellow and the Arthur Holly Compton Distinguished Service Professor of Computer Science at the University of Chicago. He was the Director of Argonne’s Computation Institute from 2006 to 2016.

Foster’s research contributions span high-performance computing, distributed systems, and data-driven discovery. He has published hundreds of scientific papers and eight books on these and other topics. Methods and software developed under his leadership underpin many large national and international cyberinfrastructures.

Foster received a BSc (Hons I) degree from the University of Canterbury, New Zealand, and a PhD from Imperial College, United Kingdom, both in computer science. His awards include the Global Information Infrastructure (GII) Next Generation award, the British Computer Society’s Lovelace Medal, R&D Magazine’s Innovator of the Year, the IEEE Tsutomu Kanai award, and honorary doctorates from the University of Canterbury, New Zealand and CINVESTAV, Mexico.

He is an elected Fellow of the American Association for the Advancement of Science, the Association for Computing Machinery, and British Computer Society.

Research Interests

• Distributed, parallel, and data-intensive computing technologies
• Innovative applications of computing technologies to scientific problems in such domains as climate change and biomedicine