2016 SDSC Summer Institute


Ilkay Altintas, Ph.D.
Chief Data Science Officer and Lab Director, Scientific Workflow Automation Technologies
Expertise: Scientific Workflows, Provenance, Distributed Computing, Observatory Systems
Ilkay Altintas, Ph.D. is the Director for the Scientific Workflow Automation Technologies Lab at the San Diego Supercomputer Center (SDSC), UC San Diego where she also is the Deputy Coordinator for Research. Since joining SDSC in 2001, she has worked on different aspects of scientific workflows as a principal investigator and in other leadership roles across a wide range of cross-disciplinary NSF, DOE and Moore Foundation projects. She is a co-initiator of and an active contributor to the open-source Kepler Scientific Workflow System, and the co-author of publications related to eScience at the intersection of scientific workflows, provenance, distributed computing, bioinformatics, observatory systems, conceptual data querying, and software modeling. Ilkay Altintas received her Ph.D. degree from the University of Amsterdam in the Netherlands with an emphasis on provenance of workflow-driven collaborative science and she is currently an assistant research scientist at UC San Diego.

Amit Chourasia
Senior Visualization Scientist
Amit Chourasia leads the Visualization Services group at the San Diego Supercomputer Center (SDSC). His work is focused on research, development and application of software tools and techniques for visualization. Key portion of his work is to find ways to represent data in a visual form that is clear, succinct and accurate - a challenging yet very exciting endeavor.

Pietro Cicotti, Ph.D.
Senior Computational Scientist
Expertise: Architecture; runtime systems; performance tools, analysis, optimization, and modeling
Dr. Cicotti is a senior computational scientist at SDSC. His research deals with aspects of emerging technology and novel system architecture. His work includes the development of runtime systems to hide communication, improve locality, and increase energy efficiency. He developed software tools for capturing and analyzing data movement, and is currently investigating the use of this information for managing data in NUMA, heterogeneous, and non-volatile memory hierarchies. Current optimization work also includes IO and hierarchical storage systems. Finally, he collaborates on scientific data analysis projects utilizing map-reduce and emerging programming models.

Andreas Goetz, Ph.D.
Co-Director, CUDA Teaching Center, Co-Principal Investigator, Intel Parallel Computing Center
Expertise: Quantum Chemistry, Molecular Dynamics, ADF and AMBER Developer, GPU Accelerated computing

Andreas Goetz, Ph.D., is an Assistant Project Scientist and Co-Director of the CUDA Teaching Center at the San Diego Supercomputer Center (SDSC). His work combines aspects of (bio)chemistry, physics, numerical mathematics, software development and high performance computing. He is a contributing author to the ADF quantum chemistry software and the AMBER software package for biomolecular simulations, both widely used in academic and industrial research. Andreas collaborates on a variety of research projects in molecular simulation, computational enzymology and drug design, most prominently as principal investigator with the National Renewable Energy Laboratory. Andreas also enjoys training the next generation of scientists in software development and numerical simulation methods via lectures, workshops and supervision of interns. Prior to joining SDSC in 2009 Andreas performed postdoctoral research in quantum chemistry at the VU University in Amsterdam and obtained his undergraduate and Ph.D. degrees in chemistry with specialization on theoretical chemistry from the University of Erlangen in Germany.

Mai H Nguyen, Ph.D.
Data Scientist
Mai Nguyen has extensive industry and academic experience in machine learning, data mining, business intelligence, data warehousing, and software design & development. She is a researcher at the San Diego Supercomputer Center (SDSC) at the University of California, San Diego (UCSD), where she works on combining machine learning algorithms with distributed computing to process large-scale data. She has worked in many application areas, including predictive analytics, remote sensing, target recognition, among others. She has M.S. and Ph.D. degrees in Computer Science from UCSD, with focus on machine learning and artificial intelligence.

Paul Rodriguez Ph.D.
Research Analyst
Paul Rodriguez received his PhD in Cognitive Science at University of California, San Diego (UCSD) in 1999. He spent several years doing research in neural network modeling, dynamical systems simulations, time series analysis, and statistical methods for analysis and predictions in fMRI data. He has more recently worked in data mining for health care fraud identification, and optimization of data intensive network flow models.

Robert Sinkovits, Ph.D.
Interim Director for Scientific Computing Applications, SDSC
Expertise: High-performance computing, performance tuning and analysis, software parallelization, network analysis, structural biology
Robert Sinkovits, Ph.D. leads the scientific applications efforts at the San Diego Supercomputer Center. He has collaborated with researchers spanning a large number of fields including physics, chemistry, astronomy, structural biology, finance and the social sciences, always with an emphasis on making the most effective use of high end computing resources. Before returning to SDSC, he was the primary developer of the AUTO3DEM and IHRSR++ software packages used for solving the structures of icosahedral and helical macromolecular structures, respectively. He has approximately 50 journal publications, book chapters and conference proceedings. He is also an avid cyclist and mountain climber, having summited nearly 300 peaks.

Mahidhar Tatineni, Ph.D.
User Services Manager
Mahidhar Tatineni received his M.S. & Ph.D. in Aerospace Engineering from UCLA. He currently leads the User Services group at SDSC and has done many optimization and parallelization projects on the supercomputing resources including Gordon.

Rick Wagner, Ph.D. Candidate
HPC Systems Manager
Expertise: Linux Clusters, Astrophysics
Rick Wagner is the High Performance Computing Systems Manager at the San Diego Supercomputer Center, and a Ph.D. Candidate in Physics at the University of California, San Diego focusing his research on analyzing simulations of supersonic turbulence. In his managerial role, Rick has technical and operational responsibility for two of the NSF-funded Extreme Science and Engineering Discovery Environment (XSEDE) HPC clusters, Trestles and Gordon, and SDSC's Data Oasis parallel file systems. He has also worked with Argonne National Laboratory on coupling remote large-scale visualization resources to tiled display walls over dynamic circuits networks on the Department of Energy's Energy Sciences Network. Rick's other interests include promoting the sharing of astrophysical simulations through standardized metadata descriptions and access protocols, and he is currently serving as the Vice-Chair of the Theory Interest Group of the International Virtual Astronomical Observatory. His latest side project involves working with undergraduates to develop course materials on parallel programming for middle and high school students using Raspberry Pis.

Nicole Wolter
Programmer Analyst III
Nicole Wolter has over 10 years of experience in high performance computing. She has spent six years doing research in Performance Modeling and Characterization at UC San Diego. She has excellent analytical and model development skills most recently applied in the areas of medical informatics, sports analytics and large data analysis. She has conducted a number of data mining classes and lectures.

Andrea Zonca Ph.D.
HPC Applications Specialist
Expertise: Data-Intensive Computing, Data Visualization, Cosmic Microwave Background, Python Development

Andrea Zonca has a background in Cosmology, during his PhD and PostDoc he worked on analyzing Cosmic Microwave Background data from the Planck Satellite. In order to manage and analyze large datasets, he developed expertise in Supercomputing, in particular parallel computing in Python and C++. At the San Diego Supercomputer Center he helps research groups in any field of science to port their data analysis pipelines to XSEDE supercomputers. Andrea is also a certified instructor of Software Carpentry and teaches automation with bash, version control with git and programming with Python to scientists.