project/templates/talk/conf_schedule.html
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     1 {% extends "base.html" %}
       
     2 {% block content %}
       
     3 <h1 class="title">SciPy.in 2010 Conference Schedule</h1>
       
     4 
       
     5 <h3 id="sec-1">A detailed list of talks will be announced after accepting the Call for Papers is complete. The schedule of invited talks given below may change. The final schedule for the conference will be put up after evaluating the submitted talks.</h3>
       
     6 
       
     7 <h2 id="sec-1">Day 1 </h2>
       
     8 
       
     9 <table border="2" cellspacing="0" cellpadding="6" rules="groups" frame="hsides">
       
    10 <caption></caption>
       
    11 <colgroup><col align="right" /><col align="left" /><col align="left" /><col align="left" />
       
    12 </colgroup>
       
    13 <thead>
       
    14 <tr><th scope="col">Time</th><th scope="col">Agenda</th><th scope="col">Speaker</th><th scope="col">Title</th></tr>
       
    15 </thead>
       
    16 <tbody>
       
    17 <tr><td>9:00-9:30</td><td>Inauguration</td><td></td><td></td></tr>
       
    18 <tr><td>9:30-10:30</td><td>Keynote</td><td>Perry Greenfield</td><td><a href="#sec-3">How Python Slithered into Astronomy</a></td></tr>
       
    19 <tr><td>10:30-10:45</td><td>Tea Break</td><td></td><td></td></tr>
       
    20 <tr><td>10:45-11:30</td><td>Special Talk 1</td><td>Fernando Perez</td><td><a href="#sec-4">IPython : Beyond the Simple Shell</a></td></tr>
       
    21 <tr><td>11:30-12:00</td><td>Invited Talk 1</td><td>Asokan Pichai</td><td><a href="#sec-5">Teaching Programming with Python</a></td></tr>
       
    22 <tr><td>12:00-13:15</td><td>Talks</td><td></td><td></td></tr>
       
    23 <tr><td>13:15-14:15</td><td>Lunch</td><td></td><td></td></tr>
       
    24 <tr><td>14:15-14:45</td><td>Lightning Talks</td><td></td><td></td></tr>
       
    25 <tr><td>14:45-15:55</td><td>Talks</td><td></td><td></td></tr>
       
    26 <tr><td>15:55-16:10</td><td>Tea Break</td><td></td><td></td></tr>
       
    27 <tr><td>16:10-17:30</td><td>Talks</td><td></td><td></td></tr>
       
    28 </tbody>
       
    29 </table>
       
    30 
       
    31 <h2 id="sec-2">Day 2 </h2>
       
    32 
       
    33 <table border="2" cellspacing="0" cellpadding="6" rules="groups" frame="hsides">
       
    34 <caption></caption>
       
    35 <colgroup><col align="right" /><col align="left" /><col align="left" /><col align="left" />
       
    36 </colgroup>
       
    37 <thead>
       
    38 <tr><th scope="col">Time</th><th scope="col">Agenda</th><th scope="col">Speaker</th><th scope="col">Title</th></tr>
       
    39 </thead>
       
    40 <tbody>
       
    41 <tr><td>9:00-10:00</td><td>Special Talk 2</td><td>John Hunter</td><td><a href="#sec-6">matplotlib: Beyond the simple plot</a></td></tr>
       
    42 <tr><td>10:00-10:45</td><td>Invited Talk 2</td><td>Prabhu Ramachandran</td><td><a href="#sec-7">Mayavi : Bringing Data to Life</a></td></tr>
       
    43 <tr><td>10:45-11:00</td><td>Tea Break</td><td></td><td></td></tr>
       
    44 <tr><td>11:00-13:15</td><td>Talks</td><td></td><td></td></tr>
       
    45 <tr><td>13:15-14:15</td><td>Lunch</td><td></td><td></td></tr>
       
    46 <tr><td>14:15-14:45</td><td>Lightning Talks</td><td></td><td></td></tr>
       
    47 <tr><td>14:45-15:55</td><td>Talks</td><td></td><td></td></tr>
       
    48 <tr><td>15:55-16:10</td><td>Tea Break</td><td></td><td></td></tr>
       
    49 <tr><td>16:10-17:30</td><td>Talks</td><td></td><td></td></tr>
       
    50 </tbody>
       
    51 </table>
       
    52 
       
    53 <h2 id="sec-3">Keynote by Perry Greenfield </h2>
       
    54 
       
    55 <p>Perry Greenfield
       
    56 </p>
       
    57 
       
    58 <h3 id="sec-3_1">Title </h3>
       
    59 
       
    60 <p>How Python Slithered into Astronomy
       
    61 </p>
       
    62 
       
    63 <h3 id="sec-3_2">Talk/Paper Abstract </h3>
       
    64 
       
    65 <p>
       
    66 I will talk about how Python was used to solve our problems for the
       
    67 Hubble Space Telescope. From humble beginnings as a glue element for
       
    68 our legacy software, it has become a cornerstone of our scientific
       
    69 software for HST and the next large space telescope, the James Webb
       
    70 Space Telescope, as well as many other astronomy projects. The talk
       
    71 will also cover some of the history of essential elements for
       
    72 scientific Python and where future work is needed, and why Python is
       
    73 so well suited for scientific software.
       
    74 </p>
       
    75 
       
    76 
       
    77 <h2 id="sec-4">Special Talk 1 </h2>
       
    78 
       
    79 <p>Fernando Perez
       
    80 </p>
       
    81 
       
    82 <h3 id="sec-4_1">Title </h3>
       
    83 
       
    84 <p>IPython : Beyond the Simple Shell
       
    85 </p>
       
    86 
       
    87 <h3 id="sec-4_2">Talk/Paper Abstract: </h3>
       
    88 
       
    89 <p>IPython is a widely used system for interactive computing in Python
       
    90 that extends the capabilities of the Python shell with operating
       
    91 system access, powerful object introspection, customizable "magic"
       
    92 commands and many more features.  It also contains a set of tools to
       
    93 control parallel computations via high-level interfaces that can be
       
    94 used either interactively or in long-running batch mode.
       
    95 
       
    96 In this talk I will outline some of the main features of IPython as it
       
    97 has been widely adopted by the scientific Python user base, and will
       
    98 then focus on recent developments.  Using the high performance ZeroMQ
       
    99 networking library, we have recently restructured IPython to decouple
       
   100 the kernel executing user code from the control interface.  This
       
   101 allows us to expose multiple clients with different capabilities,
       
   102 including a terminal-based one, a rich Qt client and a web-based one
       
   103 with full matplotlib support. In conjunction with the new HTML5
       
   104 matplotlib backend, this architecture opens the door for a rich
       
   105 web-based environment for interactive, collaborative and parallel
       
   106 computing.  
       
   107 
       
   108 There is much interesting development to be done on this front, and I
       
   109 hope to encourage participants at the sprints during the conference to
       
   110 join this effort.
       
   111 
       
   112 </p>
       
   113 
       
   114 <h2 id="sec-5">Invited Talk 1 </h2>
       
   115 
       
   116 <p>Asokan Pichai
       
   117 </p>
       
   118 
       
   119 <h3 id="sec-5_1">Title </h3>
       
   120 
       
   121 <p>Teaching Programming with Python
       
   122 </p>
       
   123 
       
   124 <h3 id="sec-5_2">Talk/Paper Abstract: </h3>
       
   125 
       
   126 <p>As a trainer I have been engaged a lot for teaching fresh Software
       
   127 Engineers and software job aspirants. Before starting on the language,
       
   128 platform specific areas I teach a part I refer to as Problem Solving
       
   129 and Programming Logic. I have used Python for this portion of training
       
   130 in the last 12+years. In this talk I wish to share my experiences and
       
   131 approaches.
       
   132 
       
   133 This talk is intended at Teachers, Trainers, Python Evangelists, and
       
   134 HR Managers [if they lose their way and miraculously find themselves in SciPy :-)]
       
   135 
       
   136 </p>
       
   137 
       
   138 
       
   139 <h2 id="sec-6">Special Talk 2 </h2>
       
   140 
       
   141 <p>John Hunter
       
   142 </p>
       
   143 
       
   144 <h3 id="sec-6_1">Title </h3>
       
   145 
       
   146 <p>matplotlib: Beyond the simple plot
       
   147 </p>
       
   148 
       
   149 <h3 id="sec-6_2">Talk/Paper Abstract: </h3>
       
   150 
       
   151 <p>matplotlib, a python package for making sophisticated publication
       
   152 quality 2D graphics, and some 3D, has long supported a wide variety
       
   153 of basic plotting types such line graphs, bar charts, images,
       
   154 spectral plots, and more.  In this talk, we will look at some of the
       
   155 new features and performance enhancements in matplotlib as well as
       
   156 some of the comparatively undiscovered features such as interacting
       
   157 with your data and graphics, and animating plot elements with the
       
   158 new animations API.  We will explore the performance with large
       
   159 datasets utilizing the new path simplification algorithm, and
       
   160 discuss areas where performance improvements are still needed.
       
   161 Finally, we will demonstrate the new HTML5 backend, which in
       
   162 combination with the new HTML5 IPython front-end under development,
       
   163 will enable an interactive Python shell with interactive graphics in
       
   164 a web browser.
       
   165 </p>
       
   166 
       
   167 
       
   168 <h2 id="sec-7">Invited Talk 2 </h2>
       
   169 
       
   170 <p>Prabhu Ramachandran
       
   171 </p>
       
   172 
       
   173 <h3 id="sec-7_1">Title </h3>
       
   174 
       
   175 <p>Mayavi : Bringing Data to Life
       
   176 </p>
       
   177 
       
   178 <h3 id="sec-7_2">Talk/Paper Abstract: </h3>
       
   179 
       
   180 <p>Mayavi is a powerful 3D plotting package implemented in Python.  It
       
   181 includes both a standalone user interface along with a powerful yet
       
   182 simple scripting interface.  The key feature of Mayavi though is that it
       
   183 allows a Python user to rapidly visualize data in the form of NumPy
       
   184 arrays.  Apart from these basic features, Mayavi has some advanced
       
   185 features.  These include, automatic script recording, embedding into a
       
   186 custom user dialog and application.  Mayavi can also be run in an
       
   187 offscreen mode and be embedded in a sage notebook
       
   188 (http://www.sagemath.org).
       
   189 
       
   190 We will first rapidly demonstrate these key features of Mayavi.  We will
       
   191 then discuss some of the underlying technologies like enthought.traits,
       
   192 traitsUI and TVTK that form the basis of Mayavi.  The objective of this
       
   193 is to demonstrate the wide range of capabilities that both Mayavi and
       
   194 its underlying technologies provide the Python programmer.
       
   195 
       
   196 </p>
       
   197 
       
   198 
       
   199 {% endblock content %}