SDSC Summer Institute Instructors

Amit Chourasia

SDSC | 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.

Andreas Goetz, Ph.D.

SDSC | Research Scientist, Principal Investigator

Andreas Goetz leads the computational chemistry efforts at SDSC, working at the intersection of (bio)chemistry, physics, and high performance and data intensive 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 with support from NSF, DOE, NIH, Intel and Nvidia. Andreas also enjoys training the next generation of scientists in software engineering and numerical simulation methods via lectures, workshops and supervision of interns. He is author of over 40 scientific publications and editor of the book 'Electronic structure calculations on GPUs'. Prior to joining SDSC in 2009 Andreas performed postdoctoral research at the VU University in Amsterdam and obtained his undergraduate and Ph.D. degrees in chemistry from the University of Erlangen in Germany.

Martin Kandes, PH.D.

SDSC | Computational and Data Science Research Specialist

Marty Kandes is a Computational and Data Science Research Specialist in the High-Performance Computing User Services Group at SDSC. He currently helps manage user support for Comet — SDSC’s largest supercomputer. Marty obtained his Ph.D. in Computational Science in 2015 from the Computational Science Research Center at San Diego State University, where his research focused on studying quantum systems in rotating frames of reference through the use of numerical simulation. He also holds an M.S. in Physics from San Diego State University and B.S. degrees in both Applied Mathematics and Physics from the University of Michigan, Ann Arbor. His current research interests include problems in Bayesian statistics, combinatorial optimization, nonlinear dynamical systems, and numerical partial differential equations.

Amit Majumdar, PH.D.

SDSC | Director for Data Enabled Scientific Computing (DESC)

Amit Majumdar leads the Data Enabled Scientific Computing division at SDSC. He has developed parallel algorithms for various kinds of HPC machines using shared memory, message passing and hybrid programming models. He and his colleagues manage the Neuroscience Gateway project which enables large scale neuronal simulations and processing of neuroscience data on supercomputers. He received his bachelor’s in electronics and telecommunication engineering from the Jadavpur Univ., Calcutta, India; master's in nuclear engineering from Idaho State Univ., Pocatello; Ph.D. degree in the interdisciplinary program of nuclear engineering and scientific computing from Univ. of Michigan.

Mai H Nguyen, Ph.D.

SDSC | Lead for Data Analytics

Mai Nguyen has extensive industry and academic experience in machine learning, data mining, business intelligence, data warehousing, and software design & development. She is a data scientist 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 remote sensing, personalized medicine, image analysis, and speech recognition. 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.

SDSC | 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.

SDSC | Director for Scientific Computing Applications

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.

Subhashini Sivagnanam

SDSC | Senior Computational and Data Science Specialist

Subhashini Sivagnanam works for the Data Enabled Scientific Computing division as the principal computational and data science specialist. Her primary areas of research focus are in the fields of distributed computing/ Cyberinfrastructure (CI), scientific data management and reproducible science. She leads the Open Science Chain (OSC) project which uses blockchain to ensure integrity of scientific data. Since 2005, she has been working on various projects related to reducing the complexity of using CI resources such as developing metascheduling tools, creating science gateways, providing scientific computing support, and leading training effort.

Mahidhar Tatineni, Ph.D.

SDSC | Director, User Services

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 and Comet.

Mary Thomas, Ph.D.

SDSC | Computational Data Scientist, HPC Trainer

Mary Thomas is a member of the Data Enabled Scientific Computing (DESC) division. Mary holds a Ph.D. in computational science, and M.S. degrees in computer science and physics. Her research interests include: HPC computing and training; coastal ocean modeling; cyberinfrastructure and emerging technologies, including Jupyter notebooks, interactive and cloud computing. For more information, see .

Nicole Wolter

SDSC | Computational and Data Science Research Specialist

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.

Ilya Zaslavsky, PH.D.

SDSC | Director of Spatial Information Systems Lab

Dr. Ilya Zaslavsky is director of Spatial Information Systems Lab at the San Diego Supercomputer Center, University of California San Diego. His research focuses on distributed information management systems, spatial and temporal data discovery and integration, and visual analytics for surveys and image collections. Zaslavsky received his Ph.D. from the University of Washington (1995), and earlier a Ph.D. equivalent from the Russian Academy of Sciences (1990). He has been leading design and technical development in several large cyberinfrastructure projects supported by the U.S. National Science Foundation, mostly in the geosciences.

Andrea Zonca, Ph.D.

SDSC | Senior Computational Scientist

Andrea Zonca has a background in Cosmology, he has been working on analyzing Cosmic Microwave Background data from the Planck Satellite. In order to manage and analyze large datasets, he developed expertise in parallel programming in Python and C++. At SDSC he helps research groups in any field of science to port their data analysis pipelines to XSEDE supercomputers. Andrea is also a certified Software Carpentry instructor.