Program
Listed below are confirmed presentations for SciPy2013. More details and schedule information coming soon.
Keynotes
General | Machine Learning | Reproducible Science
Astronomy and Astrophysics | Bioinformatics | GIS - Geospatial Data Analysis | Medical Imaging | Meteorology, Climatology, Atmospheric and Oceanic Science
Posters
General | Machine Learning | Reproducible Science
Astronomy and Astrophysics | Bioinformatics | GIS - Geospatial Data Analysis | Medical Imaging | Meteorology, Climatology, Atmospheric and Oceanic Science
Posters
| Back to top Keynotes |
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|---|---|
| IPython: from the shell to a book with a single tool; the method behind the madness | Fernando Perez, UC Berkeley Henry H. Wheeler Jr. Brain Imaging Center |
| The New Scientific Publishers | William Schroeder, Kitware |
| Trends in Machine Learning and the SciPy community | Olivier Grisel |
| Back to top General |
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| A comprehensive look at representing physical quantities in Python | Bekolay, Trevor, University of Waterloo |
| A Portrait of One Scientist as a Graduate Student | Ivanov, Paul, UC Berkeley |
| Analyzing IBM Watson experiments with IPython Notebook | Bittner, Torsten, IBM |
| Breaking the diffraction limit with python and scipy | Baddeley, David, Nanobiology Institute, Yale University |
| Bringing astronomical tools down to earth | Droettboom, Michael, STScI; Dencheva, Nadia, STScI; Aldcroft, Tom, Harvard-Smithsonian Center for As |
| Data Agnosticism: Feature Engineering Without Domain Expertise | Kridler, Nicholas, Accretive Health |
| DMTCP: Bringing Checkpoint-Restart to Python | Arya, Kapil, Northeastern University; Cooperman, Gene, Northeastern University |
| Dynamics with SymPy Mechanics | Moore, Jason, University of California at Davis |
| High Performance Reproducible Computing | Zhang, Zhang, Intel Corporation; Rosenquist, Todd, Intel Corporation; Moffat, Kent, Intel Corporation |
| Import without a filesystem: scientific Python built-in with static linking and frozen modules | Pat Marion, Kitware; Aron Ahmadia; Bradley M. Froehle, University of California, Berkeley |
| Julia and Python: a dynamic duo for scientific computing | Bezanson, Jeff, MIT; Karpinski, Stefan, MIT |
| Matrix Expressions and BLAS/LAPACK | Rocklin, Matthew, University of Chicago Computer Science |
| Modeling Complexity with Python | Dr. Maksim Tsvetovat, independent; Alex Kouznesov, independent |
| Modeling the Earth with Fatiando a Terra | Uieda, Leonardo, Observatorio Nacional; Oliveira Jr, Vanderlei C., Observatorio Nacional; Barbosa, V |
| Multidimensional Data Exploration with Glue | Beaumont, Christopher, U. Hawaii; Robitaille, Thomas, MPIA; Borkin, Michelle, Harvard; Goodman, Alys |
| open('/dev/real_world') - Raspberry Pi Sensor and Actuator Control | Minardi, Jack, Enthought Inc. |
| Opening Up Astronomy with Python and AstroML | Vanderplas, Jake, University of Washington; Ivezic, Zeljko, University of Washington; Connolly, Andrew, University of Washington |
| Parallel Volume Rendering in yt: User Driven & User Developed | Skillman, Samuel, University of Colorado at Boulder; Turk, Matthew, Columbia University |
| PyOP2: a Framework for Performance-Portable Unstructured Mesh-based Simulations and its Application to Finite-Element Computations | Rathgeber, Florian, Imperial College London, UK; Markall, Graham R., Imperial College London, UK; Mi |
| Pythran: Enabling Static Optimization of Scientific Python Programs | Serge Guelton, ENS; Pierrick Brunet, Télécom Bretagne; Alan Raynaud, Télécom Bretagne; Adrien Merlini, Télécom Bretagne; Mehdi Amini, SILKAN |
| Scientific Computing and the Materials Genome Initiative | Reid, Andrew, National Institute of Standards and Technology |
| Scikit-Fuzzy: A New SciPy Toolkit for Fuzzy Logic | Warner, Joshua, Mayo Clinic Department of Biomedical Engineering; Ottesen, Hal H., Adjunct Professor |
| SymPy Gamma and SymPy Live: Python and Mathematics Online | Li, David, SymPy |
| Synoptic Atmospheric Transport of Wildfire Smoke Plume to Greenland | Lavoue David, DL Modeling and Research, Milton, Ontario, Canada |
| The DyND Library | Wiebe, Mark, Continuum Analytics |
| Why you should write buggy software with as few features as possible | Granger, Brian, Cal Poly San Luis Obispo |
| XDress - Type, But Verify | Scopatz, Anthony, The University of Chicago & NumFOCUS, Inc. |
| Back to top Machine Learning |
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| A Gentle Introduction To Machine Learning | Kastner, Kyle, Southwest Research Institute |
| Hyperopt: A Python library for optimizing the hyperparameters of machine learning algorithms | Bergstra, James, University of Waterloo; Yamins, Dan, Massachusetts Institute of Technology; Cox, David D., Harvard University |
| Implicit Sentiment Mining with SnowWhite | Tsvetovat, Maksim, 2042 Labs; Alex Kouznetsov, |
| Infer.py: Probabilistic Programming and Bayesian Inference from Python | Zinkov, Rob |
| mystic: a framework for predictive science | Michael McKerns @ California Institute of Technology, Houman Owhadi @ California Institute of Techno |
| Processing biggish data on commodity hardware: simple Python patterns | Author: Gael Varoquaux Institution: INRIA, Parietal team |
| Python Tools for Coding and Feature Learning | Johnson, Leif, University of Texas at Austin |
| Roadmap to a Sentience Stack | Eric Neuman |
| Skdata: Data seets and algorithm evaluation protocols in Python | Bergstra, James, University of Waterloo: Pinto, Nicolas, Massachusetts Institute of Technology; Cox, David D., Harvard University |
| Using Python for Structured Prediction | Zinkov, Rob |
| Back to top Reproducible Science |
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| An efficient workflow for reproducible science | Bekolay, Trevor, University of Waterloo |
| Complex Experiment Configuration, Control, Automation, and Analysis using Robot Operating System (ROS) | Stowers, John, TU Wien; Straw, Andrew, Research Institute of Molecular Pathology |
| Emacs + org-mode + python in reproducible research | Kitchin, John Carnegie Mellon University |
| Exploring Collaborative HPC Visualization Workflows using VisIt and Python | Krishnan, Harinarayan, Lawrence Berkeley National Labs; Harrison, Cyrus, Lawrence Livermore National |
| GraphTerm: A notebook-like graphical terminal interface for collaboration and inline data visualization | Ramalingam Saravanan, Texas A&M University |
| IPython-powered Slideshow Reveal-ed | Avila, Damian, OQUANTA; |
| lmonade: a platform for development and distribution of scientific software | Erocal, Burcin, TU Kaiserslautern |
| lpEdit: An editor to facilitate reproducible analysis via literate programming | Richards, Adam, Duke University, CNRS France; Kosinski Andrzej, Duke University; Bonneaud, Camille, |
| matplotlib: past, present and future | Michael Droettboom |
| OS deduplication with SIDUS (single-instance distributing universal system) | Quemener, Emmanuel, Centre Blaise Pascal (Lyon, France); Corvellec, Marianne, McGill University (Mon |
| Reproducible Documents with PythonTeX | Poore, Geoffrey, Union University |
| The advantages of a scientific IDE | Cordoba, Carlos, The Spyder Project |
| The Open Science Framework: Improving, by Opening, Science | Spies, Jeffrey, Center for Open Science; Nosek, Brian, Center for Open Science |
| Using IPython Notebook with IPython Cluster for Reproducibility and Portability of Atomistic Simulations | Trautt, Zachary, Materials Measurement Science Division, National Institute of Standards and Technol |
| Using Sumatra to Manage Numerical Simulations | Davison, Andrew, CNRS (principal developer); Wheeler, Daniel, NIST (speaker) |
| vIPer, a new tool to work with IPython notebooks | Avila, Damian, OQUANTA; |
| Writing Reproducible Papers with Dexy | Nelson, Ana |
| Back to top Astronomy and Astrophysics |
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| Accessing the Virtual Observatory from Python | Plante, Raymond, NCSA/UofIL; Fitzpatrick, Mike, NOAO; Graham, Matthew, Caltech; Tody, Doug, NRAO |
| Astropy, growing a community-based software system for astronomy | Droettboom, Michael, STScI; Robitaille, Thomas, Max Planck Institute; Tollerud, Erik, Yale Universit |
| Combining C++ and Python in the LSST Software Stack | Bosch, Jim, Princeton University |
| Ginga: an open-source astronomical image viewer and toolkit | Jeschke, Eric, Subaru Telescope, National Astronomical Observatory of Japan |
| Python and the SKA | Simon Ratcliffe SKA South Africa, Ludwig Schwardt SKA South Africa |
| SunPy - Python for Solar Physicists | Mumford, Stuart, University of Sheffield / SunPy |
| Back to top Bioinformatics |
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| All-by-all learning of protein complexes from mass spectrometry data | Blake Borgeson, Center for Systems and Synthetic Biology, University of Texas at Austin; Cuihong Wa |
| Best-practice variant calling pipeline for fully automated high throughput sequencing analysis | Chapman, Brad; Kirchner, Rory; Hofmann, Oliver; Hide, Winston |
| Detection and characterization of interactions of genetic risk factors in disease | Francis-Lyon, Patricia, University of San Francisco; Belvadi, Shashank, University of San Francisco; Wang, Lin, University of San Francisco |
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| EMAN2 and EMEN2: Flexible Python-based platforms for electron microscopy | Rees, Ian, Baylor College of Medicine; Ludtke, Steven, Baylor College of Medicine |
| Exploring disease genetics from thousands of individual genomes with Gemini | Quinlan, Aaron, University of Virginia; Paila, Uma, University of Virginia; Chapman, Brad, Harvard School of Public Health; Kirchner, Rory, |
| Massive Online Collaborative Research and Modeling using Synapse and Python | Omberg, Larsson, Sage Bionetworks |
| metaseq: a Python framework for integrating high-throughput sequencing analyses | Dale, Ryan, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of |
| MIST: Micro-Simulation Tool to Support Disease Modeling | Jacob Barhak |
| Stuff to do with your genomic intervals | Pedersen, Brent; University of Colorado |
| Back to top GIS - Geospatial Data Analysis |
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| GIS Panel | Panel participants: Sergio Ray (Arizona State U), Shaun Walbridge (ESRI), Andrew Wilson (TWDB) |
| LarvaMap - A python powered larval transport modeling system | Wilcox, Kyle, Applied Science Associates (ASA); Crosby, Alex, Applied Science Associates (ASA) |
| Optimizing Geographic Processing and Analysis for Big Data | Carissa, GeoDecisions; Gleason, Jason, GeoDecisions |
| SCI-WMS: A Python Based Web Map Service For Met-Ocean Data Accessible Over OpenDAP Or As NetCDF | Crosby, Alexander |
| Streamed Clustering of Lightning Mapping Data in Python Using sklearn | Bruning, Eric C., Texas Tech University |
| The Production of a Multi-Resolution Global Index for Geographic Information Systems | MacManus, Kytt, Columbia University CIESIN |
| Back to top Medical Imaging |
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| A Rapidly-Adaptable Analytical Imaging & Measurement Standardization Platform for Cancer Diagnostics Research | Garsha, Karl, Ventana Medical Systems Inc.; Ventura, Franklin, Ventana Medical Systems Inc.; |
| An Open Source System for De-identification and Use of Medical Images for Research | Miller, Jeffrey, Center for Biomedical Informatics, The Children's Hospital of Philadelphia |
| Automating Quantitative Confocal Microscopy Analysis | Fenner, Mark; Fenner, Barbara, King's College, Wilkes-Barre, PA |
| Estimating and Visualizing the Inertia of the Human Body with Python | Moore, Jason, University of California at Davis; Dembia, Christopher, Stanford |
| Experiences in Python for Medical Image Analysis | Warner, Joshua, Mayo Clinic Department of Biomedical Engineering |
| NeuroTrends: Large-scale automated analysis of the neuroimaging literature | Carp, Joshua, University of Michigan |
| Back to top Meteorology, Climatology, Atmospheric and Oceanic Science |
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| Advances in delivery and access tools for coastal ocean model data | Signell, Richard, US Geological Survey |
| Climate Observations from ACIS in pandas | Noon, William: Northeast Regional Climate Center |
| Iris & Cartopy: Open source Python packages for Atmospheric and Oceanographic science | Elson, Philip, UK Met Office; |
| Oil spill modeling and uncertainty forecasts with Python | Hou,Xianlong, University of Texas at Austin; Hodges,Ben, University of Texas at Austin |
| Using Python to drive the General NOAA Operational Modeling Environment | Barker, Christopher H. NOAA Emergency Response Division. |
| Back to top Posters |
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| 3D Perception: Point cloud data processing and visualization | Marion, Pat, Kitware; |
| A Python way to an undergraduate CFD course | Jaime Kardontchik |
| Basic Interactive Unix for Data Processing | Hale, Walker, Baylor College of Medicine |
| Basin-hopping and beyond: Global optimization and energy landscape exploration in molecular systems | Jacob Stevenson and Victor Rühle |
| Code as text: Open source in academia | Rey, Sergio, Arizona State University |
| Data Wrangling with the SheafSystem™ | Butler, David M., Limit Point Systems, Inc. |
| Dedalus: A Python-Based Spectral PDE Solver | Keaton J. Burns, University of California Berkeley; Jeffrey S. Oishi, American Museum of Natural History; Geoffrey M. Vasil, University of California Berkeley; Daniel Lecoanet, University of California Berkeley; Eliot Quataert, University of California Berkeley |
| Experimental Mathematics with Python: Calculating Lyapunov exponents of non-elastic billiard models | Alonso Espinosa & David P. Sanders* (presenter) Institution: Department of Physics, Faculty of Sciences, Universidad Nacional Autónoma de México (UNAM) |
| G-mode Clustering Method applied to Asteroid Taxonomy | Hasselmann, P. H., Carvano, J. M., Lazzaro, D. |
| Hearing Assessment: Lessons learned developing a modular solution for audiometric testing | Chambers, Robert D., Creare Inc.; Finger, William H., Creare Inc.; Norris, Jesse A., Creare Inc.; Cl |
| HTSQL - A Navigational Query Language For Relational Databases | Charles Tirrell and Clark Evans |
| IRLB, a fast partial SVD | Baglama, Jim, University of Rhode Island; Kane, Michael, Yale |
| Managing Ensembles of Multi-Processor Jobs with Tex-MECS and PyLauncher | Tobis, Michael, Planet 3.0; Eijkhout, Victor, Texas Advanced Computing Center |
| Mica: data-mining the Chandra archive for satellite operations | Jean M. Connelly, Smithsonian Astrophysical Observatory (SAO); Thomas L. Aldcroft, SAO |
| Modeling elastic wave propagation using PyOpenCL | Ursula Iturraran-Viveros and Miguel Molero |
| Navigating the Scientific Python Communities - the missing guide | Ivanov, Paul, UC Berkeley |
| Peatland data analysis and simulation with Python | Reeve, Andrew (University of Maine); Westervelt, Claire (University of Maine) |
| Powering Recommendations with Distributed Computing using Python and MapReduce | Caraciolo, Marcel; Atapassar |
| PyDocX: Parsing Word documents in order to increase greater collaboration in collaborative writing | Portnow, Samuel, University of Virginia; Ward, Jason, PolicyStat LLC; Spies, Jeff, R, Center for Open Science |
| Scholarly: An open, freely accessible dataset of the academic citation network | Rybacki, Harry, UNCG; Carp, Joshua, University of Michigan; Spies, Jeffery, Center for Open Science |
| Self-documenting runtime: becoming omniscient with Contexture | Alexander Kouznetsov |
| Technical and social challenges in creating the Python ARM Radar Toolkit (Py-ART) | Helmus, Jonathan, Argonne National Laboratory; Collis, Scott, Argonne National Laboratory |
| The UQ Foundation: Supporting the Right Scientific Tools for Reproducibility | Drew Marsden1, Michael McKerns2, Houman Owhadi2, Clint Scovel2, Tim Sullivan3 |
| The Use of Python in the Prompt Assessment of Global Earthquake Response (PAGER) System | Hearne, Michael, US Geological Survey |
| Ureka: a distribution of Python & IRAF software for astronomy | Turner, James, Gemini Observatory; Slocum, Christine, Space Telescope Science Institute; Sienkiewicz |
| Using Git to improve reproducibility & transparency | Gemayel, Toni, Banyan |
| Using Python to Study Rotational Velocity Distributions of Hot Stars | Bragança, Gustavo, Observatório Nacional; Daflon, Simone, Observatório Nacional |
| UV-CDAT Re-sharable Analyses and Diagnostics (U-ReAD): a framework to create and share UV-CDAT plugins | Doutriaux, Charles, LLNL |