Garrett Aldrich (2013 - date)

Garrett Aldrich (2013 - date)

The University of California - Davis

Garrett is a Computer Science Ph.D. student at The University of California – Davis. His research at LANL has been on big data visualization, feature extraction and analysis. Garrett’s current mentors are Jim Ahrens and Jon Woodring.

Divya Banesh (2015 - date)

Divya Banesh (2015 - date)

The University of California - Davis

Divya Banesh is a Computer Science Ph.D. student at The University of California – Davis with Professors Bernd Hamann and Mike Oskin. She earned her B.S. in Electrical Engineering and Computer Science from The University of California – Berkeley.  Her emphasis was in visualization and computer graphics. Divya’s mentors are Jim Ahrens and David Rogers.

Daniel Ben-naim (2016 - date)

Daniel Ben-naim (2016 - date)

The University of California - Santa Barbara

Daniel Ben-naim is an undergraduate student at the University of California – Santa Barbara. This is his first year with the Data Science at Scale School. He will conduct research into automated pipelines for conducting perceptual tests. Currently we understand well how to conduct perception tests on Amazon Mechanical Turk (AMT), but these tests are work intensive, even though the general concepts and expertise to conduct them can be well-codified for a specific set of comparisons. Daniel will develop code that, with the answers to a few simple questions and a set of artifacts to compare, enables a user to automatically generate all supporting infrastructure content to conduct a specific set of tests on a set of data inputs. For example, by answering a few questions about images to be compared, the user would have a complete perceptual test run on AMT, and results reported back about that test. This will bridge the gap between AMT capabilities and specific perceptual testing knowledge in scientific visualization. Daniel’s mentors is David Rogers.

Soumya Dutta (2015 - date)

Soumya Dutta (2015 - date)

The Ohio State University

Soumya Dutta is a Ph.D. student in the Department of Computer Science and Engineering of The Ohio State University. He is working with Dr. Han-Wei Shen in the Gravity group. Before joining Ohio State, he completed his B. Tech. in Electronics and Communication Engineering from West Bengal University of Technology, Kolkata, India. He has also worked under the supervision of Dr. Bidyut B. Chaidhuri and Dr. Madhurima Chattopadhyay during his undergraduate years. This is Soumya’s second year with the Data Science at Scale School. He is researching concurrent, in transit analysis for a large-scale simulations and providing feedback to the simulations for convergence in the CESAR project. Soumya’s mentors are Jon Woodring and Emily Casleton.

Nils Feige (2016 - date)

Nils Feige (2016 - date)

University of Kaiserslautern

Nils Feige is a Ph.D. student in Computer Science at the University of Kaiserslautern in Germany. Nils works with Professor Hans Hagen. Nils’ mentors are Qiang Guan and John Patchett.

Felipe Horta (2016 - date)

Felipe Horta (2016 - date)

New York University

Felipe Horta is a Ph.D. student in Computer Engineering at New York University’s Tandon School of Engineering. He is working with Professor Claudio Silva. Felipe’s mentors are Jon Woodring and Qiang Guan.

Jonas Lukasczyk (2015 - date)

Jonas Lukasczyk (2015 - date)

University of Kaiserslautern

Jonas Lukasczyk is a Ph.D. student in Computer Science at the University of Kaiserslautern in Germany. Jonas’ mentors are Jim Ahrens and Curt Canada.

Jesus Pulido (2013 - date)

Jesus Pulido (2013 - date)

The University of California – Davis

Jesus is a Ph.D. student at the University of California – Davis with Professor Bernd Hamann. His research at LANL involves the analysis of DNS Turbulence data with collaborator Dr. Daniel Livescu. He is also collaborating with Johns Hopkins University to further develop the Johns Hopkins Turbulence Database to support visualization of massive datasets. His research interest are visualization, wavelets and multi-resolution methods, high-performance computing, and applications to turbulence. Jesus’ mentors are Jim Ahrens and Curt Canada.

Cameron Tauxe (2016 - date)

Cameron Tauxe (2016 - date)

New Mexico State University

Cameron is a Los Alamos local working under David Rogers as UI Programmer and Web Developer for a variety of data-visualization projects. During the school year, he attends New Mexico State University where he is pursuing degrees in Computer Science and Animation & Visual Effects.

Karen Tsai (2016 - DATE)

Karen Tsai (2016 - DATE)

The University of Texas – Austin

Karen is a Ph.D. Computational Science, Engineering and Mathematics student at the University of Texas – Austin. While at LANL in 2016 Karen joined data scientists from the LANL Data Science at Scale team, John Patchett and David Rogers, and UT-Austin, Francesca Samsel, Greg Abram and Terece Turton, to work with Galen Gisler of LANL’s Integrated Design & Assessment group to produce visualization and analysis of threats from asteroid ocean impacts. Their work is summarized in a paper and video that have been accepted as finalists in the SC16 Visualization Showcase. Karen’s mentors are John Patchett and Francesca Samsel.

Tzu-Hsuan Wei (2016 - DATE)

Tzu-Hsuan Wei (2016 - DATE)

The Ohio State University

Tzu-Hsuan Wei is a Ph.D. Student in Computer Science at The Ohio State University. He is working with Dr. Han-Wei Shen in the Gravity group.  His mentors are Jon Woodring and Curt Canada.

Wathsala Widanagamaachchi (2015 - date)

Wathsala Widanagamaachchi (2015 - date)

The University of Utah

Wathsala is a Computer Science Ph.D. student in the Scientific Computing and Imaging Institute at University of Utah. Her advisor is Dr. Valerio Pascucci and her primary research interests are in Scientific Visualization, Computer Graphics and Image Processing. Together with her advisor and Dr. Peer-Timo Bremer, she works on a topology based framework which allows interactive exploration of large-scale, time-varying datasets. Apart from that, her research also includes a scalable data-parallel halo-finder operator in PISTON (with Dr. Chris Sewell & Dr. Jim Ahrens of the Data Science at Scale team) and Ray graphs, a flexible framework for space and time exploring panoramas (with Dr. Paul Rosen). Wathsala was at LANL in the summer of 2015 for an onsite internship and is being supported for an offsite internship back in Salt Lake City.

 

Max Zeyen (2014 - date)

Max Zeyen (2014 - date)

The University of Kaiserslautern

Max is making his M.Sc. in Computer Science at the University of Kaiserslautern in Germany. Max is continuing work begun during the summer of 2014 at Los Alamos in applying advanced analysis, compression and visualization techniques to the complexissues that arise in comparing mesoscale material simulations with experimental measurements. This work touches on registration of multiple data sources, querying of large, complex datasets for scientific analysis, comparison of experiment and simulation results, and novel visualization methods for high dimensional data. He refined some initial experimental techniques into tools that can be used to quickly investigate and understand the large data that LANL’s material science experiments produce. Max’s mentors are David Rogers and Chris Sewell.

Past Students

Vignesh Adhinarayanan (2015)

Vignesh Adhinarayanan (2015)

Virginia Tech

Vignesh Adhinarayanan was a Ph.D. student in the Department of Computer Science at Virginia Tech with Professor Wu-chun Feng when he was a summer intern with the Data Science at Scale School in 2015.  His work was as part of the ‘Optimizing the Energy Usage and Cognitive Value of Extreme Scale Data Approaches’ (ECX) Project team. He focused on three areas; 1) establishing end-to-end workflow measurements, 2) measuring the behavior of sampling-modified workflow, and 3) modeling and optimizing a power-constrained workflow. Vignesh continued his work on the ECX project when he returned to Virginia Tech at the end of the summer. Vignesh’s mentors are David Rogers and Scott Pakin.

Zoe Ashton (2015)

Zoe Ashton (2015)

Florida Institute of Technology

Zoe Ashton was an undergraduate student at Florida Institute of Technology when she was a summer intern with the Data Science at Scale School in 2015. She was pursuing a B.A. in Humanities and a B.S. in Applied Mathematics with an emphasis in statistics.  She studied the effectiveness of colormaps, especially those developed by Francesca Samsel. She worked with Los Alamos statisticians Joanne Wendelberger and Lawrence Ticknor to analyze task-based user study data to compare colormaps. She also worked with visiting UT-Austin data analyst Terece Turton to develop user studies that produce more statistically suitable data. Her mentors were Joanne Wendelberger and Lawrence Ticknor.

David C. Barnes (2015)

David C. Barnes (2015)

Massachusetts Institute of Technology

David C. Barnes was an undergraduate student majoring in Applied Mathematics at the Massachusetts Institute of Technology when he was a summer intern with the Data Science at Scale School in 2015. He worked on applying machine learning algorithms in scientific datasets. He begun by acquiring fundamental knowledge and skills on cloud computing infrastructure (e.g. OpenStack, AWS), Big Data software stacks (e.g. Hadoop/Spark), databases (SQL/NoSQL) and machine learning libraries (Mahut/MLib). He then explored using those skills in identifying/extracting significant features in our scientific datasets. David’s mentors were Chris Sewell and Ollie Lo.

Anne Berres (2015)

Anne Berres (2015)

University of Kaiserslautern

Anne Berres held B.Sc. and M.Sc. Degrees in Computer Science from the Technical University of Kaiserslautern and was a Ph.D. student in Computer Science at the Technical University of Kaiserslautern when she was a summer intern with the Data Science at Scale School in 2015. Her research interests include topology, differential manifolds, differential geometry, medical visualization, neural diseases and probablistic tractogrphy. Her work focused on analysis and reduction of extreme scale data. Anne’s mentors were Jim Ahrens and John Patchett. She joined the Data Science at Scale team as a PostDoc in November 2015.

Ayan Biswas (2013 - 2015)

Ayan Biswas (2013 - 2015)

The Ohio State University

Ayan Biswas was a Computer Graphics and Visualization Ph.D. student at The Ohio State University with Professor Han-Wei Shen when he was a summer intern in 2013, 2014 and 2015. He has worked with flow field data and particle tracing using streamlines and stream surfaces and is now looking at the time-varying multivariate data exploration and using information theory to provide some insights into the data. He is also working with turbulent flow structures and vortex visualization for the unstable time-varying complex flows. In 2015 Ayan worked on developing a new parallel algorithm for visualization of streamlines. This was implemented in MPAS and tested in parallel. Ayan’s mentors were Jon Woodring and Richard Strelitz.

Wendy Caldwell (2016)

Wendy Caldwell (2016)

Arizona State University

Wendy Caldwell is an Applied Mathematics graduaate student at Arizona State University. 2016 was Wendy’s first year with the Data Science at Scale School. She had previously taken part in the 2015 Computational Physics Student Summer Workshop at Los Alamos. Wendy’s mentors are Sara Del Valle and Qiang Guan.

Sebastian Klaassen (2015 - 2016)

Sebastian Klaassen (2015 - 2016)

University of Vienna

Sebastian Klaassen is a graduate student in Computer Science at the University of Vienna with Professor Torsten Moeller. Sebastian came to Los Alamos in May 2015 and extended his stay into 2016. Sebastian researched the question ‘a local-to-global strategy is currently used for a Cinema Database, but can a quicker exploration and understanding of the data be found by starting with an overview of all sampled items?’ Sebastian’s mentors were Jim Ahrens and David Rogers.

Shaomeng (Samuel) Li (2016)

Shaomeng (Samuel) Li (2016)

University of Oregon and NCAR

Shaomeng (Samuel) Li is a Ph.D. student in the Computer Science Department at the University of Oregon. He also holds a concurrent role as a staff computer scientist at the National Center for Atmospheric Research. Samuel’s research focuses on novel ways to represent and compress scientific data for visualization purposes, especially in relation to exascale computing. Currently, Samuel is investigating the usage of wavelet compression and state-of-the-art encoders from the image processing community. While at LANL in 2016 Samuel worked with Chris Sewell, Ollie Lo, and Jon Woodring.

Nina McCurdy (2016)

Nina McCurdy (2016)

The University of Utah

Nina McCurdy is a Ph.D. student in Computer Science at the University of Utah with a focus on computer graphics and visualization. She is primarily interested in developing visualization tools to help scientists and scholars answer their big research questions and better understand their data. She is currently collaborating with poets/poetry scholars to develop a visualization tool in support of close reading, specifically in the context of poetry. Her Ph.D. advisor is Dr. Miriah Meyer. Nina visited the the Data Science at Scale School for a few weeks in the summer of 2016. Nina’s mentors are Francesca Samsel.