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Kerstin Kleese van Dam

Director, Computational Science Initiative


Kerstin Kleese van Dam leads Brookhaven Lab's Computational Science Initiative (CSI), which leverages computational science expertise and investments across multiple programs—including the flagship facilities that attract thousands of scientific users each year— to tackle the big data challenges at the frontiers of scientific discovery. Key partners in this endeavor include north east universities like Harvard, Yale, MIT, Columbia, Cornell, Princeton, Rutgers, Stony Brook, Tufts and CMU. 

CSI formed under Kerstin’s leadership in 2015, has developed into a driving force in extreme scale data management and data analytics. It operates one of the top 5 scientific data archives in the world, in financial year 2018 it actively managed around ~150 PB of archived data and processed 690 PB of scientific data spanning nuclear physics, high energy physics, materials and chemical sciences. The operational services are complemented by leading edge research in Artificial Intelligence, Machine Learning, Computational Science, Programming Models, Compilers, Systems and Architectures. CSI’s newest endeavor is a Quantum Computing Group that focusses its research on quantum algorithms, quantum networks and the design of next generation quantum computers.

Computational Sciences Research Activities

Extreme Scale Data Management, Metadata, Provenance and Data Curation


BS and MS In Computer Science, Technical University Berlin, Germany

Professional Appointments

2015-Present Director, Computational Science Initative, Brookhaven National Laboratory, Upton, NY. Building a comprehensive research program in data driven discovery.

2010-2015 Associate Division Director & Group Leader Scientific Data Management, Pacific Northwest National Laboratory, Richland, WA. Research efforts included: 1) Development of new capabilities for in-situ analysis and interpretation of streaming data, DOE ASCR Integrated End-to-End Performance Prediction and Diagnosis for Extreme Scientific Workflows (Co-PI), DOE ASCR/BER Interoperable Design of Extreme-scale Application Software (task lead), PNNL Analysis in Motion initiative (co-lead), High Speed Data Acquisition in chemical Imaging (project lead); 2) development of data management and analysis techniques for extreme scale environments for DOE BER Climate Science for a Sustainable Energy Future and Accelerated Climate Modeling for Energy (task lead provenance), DOE BER Advanced Simulation Capability for Environmental Management (ASCEM), DOE HEP Belle II (task lead DB), Chemical Imaging Initiative (software lead – real time data analysis), Platform for Regional Integrated Modeling and Analysis (project lead), Future Power Grid (project lead – streaming feature detection); 

2009 Director Computing, Biomedical Sciences Faculty, University College London, UK

2001-2008 Group Leader, Scientific Data Management Group, Science and Technology Facilities Council, UK. Development of data management, sharing and curation infrastructures: ICAT (central data management infrastructure) for DIAMOND Light Source, ISIS Neutron Source and CLF Laser Facility, today also deployed at international facilities in Germany, France, Australia, Canada and the USA (e.g. SNS); Natural Environmental Research Council (NERC) Data Grid; Ecological DataGrid; e-Materials; e-Minerals; Integrated Systems Biology Centre; Integrative Biology; BBSRC Institutes Data Archival Service; UK Digital Curation Centre

1997-2001 Senior Research Scientist, High Performance Computing, Science and Technology Facilities Council, UK

1994-1997 Software Developer, German Climate Computing Centre (DKRZ), Germany

1989-1994 Software Developer / System Administration (HPC), INPRO, Germany

Selected Publications & Research Highlights

  1. Pouchard, L. , Baldwin, S., Elsethagen, T., Gamboa C., Jha, S., Raju, B., Stephan, E., Tang L., Kleese Van Dam, K. 2018. Use Cases of Computational Reproducibility for Scientific Workflows at Exascale. IJHPCA March 2018, arXiv:1805.00967
  2. Deelman, E., Peterka, T., Altintas, I., Carothers, C.D., Kleese van Dam, K., Moreland, K., Parashar, M., Ramakrishnan, L., Taufer, M., Vetter, J. 2017. The future of Scientific Workflows. The International Journal of High Performance Computing Applications, Vol. 32, Issue 1, p. 159-175. April 2017.
  3. Kleese van Dam, K., Stephan, E., Raju, B., Altintas, I., Elsethagen, T., Krishnamoorthy, S. 2015. Enabling Structured Exploration of Workflow Performance Variability in Extreme Scale Environments. SC15, MTAGS15 workshop, November 2015.
  4. Bethel, W., Greenwald, M., Kleese van Dam, K., Parashar, M., Wild, S.M., Wiley H.S. 2016. Management, analysis, and visualization of experimental and observational data – The convergence of data and computing. 2016 IEEE 12th International Conference on e-Science (e-Science), p. 213-222, October 2016.
  5. Kraucunas, I., L. Clarke, J. Dirks, J. Hathaway, M. Hejazi, K. Hibbard, M. Huang, C. Jin, M. Kintner-Meyer, K. Kleese van Dam, R. Leung, H.Li, R. Moss, M. Peterson, J. Rice, M. Scott, A. Thomson, N. Voisin, T. West. 2014. Investigating the nexus of climate, energy, water, and land at decision-relevant scales: the Platform for Regional Integrated Modeling and Analysis (PRIMA). Climate Change, p1-16, Springer, February 2014.
  6. Critchlow, T. and K. Kleese van Dam, Editors, 2013: Data Intensive Science. Boca Raton: Taylor and Francis, May 2013.
  7. Stephan EG, P Pinheiro da Silva, and K Kleese van Dam.  2013. Bridging the Gap between Scientific Data Producers and Consumers: A Provenance Approach. Chapter 12, p279-299, In Data Intensive Science Critchlow, Data Intensive Science. Boca Raton: Taylor and Francis, May 2013.
  8. Gorton, I., Y. Liu, C. Lansing, T. Elsethagen and K. Kleese van Dam, 2013: Build Less Code, Deliver More Science: An Experience Report on Composing Scientific Environments using Component-based and Commodity Software Platforms. Proceedings The 16th International ACM Sigsoft Symposium on Component-Based Software Engineering, June 2013.
  9. Matthews, B., Sufi, S., Flannery, D., Lerusse, L., Griffin, T., Gleaves, M., Kleese van Dam, K. 2010. Using a Core Scientific Metadata Model in Large-Scale Facilities. International Journal of Digital Curation, Vol. 5, Issue 1, p. 106-118, June 2010.