45 <tbody> |
45 <tbody> |
46 <tr><td class="right">09:00-09:45</td><td class="left">Gael</td><td class="left"><a href="#sec2.23">Invited Speaker: <b>Machine learning as a tool for Neuroscience</b></td></tr> |
46 <tr><td class="right">09:00-09:45</td><td class="left">Gael</td><td class="left"><a href="#sec2.23">Invited Speaker: <b>Machine learning as a tool for Neuroscience</b></td></tr> |
47 <tr><td class="right">09:45-10:15</td><td class="left">Kannan Moudgalya</td><td class="left"><b>Invited</b></td></tr> |
47 <tr><td class="right">09:45-10:15</td><td class="left">Kannan Moudgalya</td><td class="left"><b>Invited</b></td></tr> |
48 <tr><td class="right">10:15-10:45</td><td class="left"></td><td class="left"><b>Tea</b></td></tr> |
48 <tr><td class="right">10:15-10:45</td><td class="left"></td><td class="left"><b>Tea</b></td></tr> |
49 <tr><td class="right">10:45-11:05</td><td class="left">Hrishikesh Deshpande</td><td class="left"><a href="#sec2.14">Higher Order Statistics in Python</a></td></tr> |
49 <tr><td class="right">10:45-11:05</td><td class="left">Hrishikesh Deshpande</td><td class="left"><a href="#sec2.14">Higher Order Statistics in Python</a></td></tr> |
50 <tr><td class="right">11:05-11:25</td><td class="left">Shubham Chakraborty</td><td class="left"><a href="#sec2.15">Combination of Python and Phoenix-M as a low cost substitute for PLC</a></td></tr> |
50 <tr><td class="right">11:05-11:25</td><td class="left">Jaidev Deshpande</td><td class="left"><a href="#sec2.18">A Python Toolbox for the Hilbert-Huang Transform</a></td></tr> |
51 <tr><td class="right">11:25-12:10</td><td class="left">Emmanuelle</td><td class="left"><b>Invited</b></td></tr> |
51 <tr><td class="right">11:25-12:10</td><td class="left">Emmanuelle</td><td class="left"><b>Invited</b></td></tr> |
52 <tr><td class="right">12:10-13:10</td><td class="left"></td><td class="left"><b>Lunch</b></td></tr> |
52 <tr><td class="right">12:10-13:10</td><td class="left"></td><td class="left"><b>Lunch</b></td></tr> |
53 <tr><td class="right">13:10-13:30</td><td class="left">Mahendra Naik</td><td class="left"><a href="#sec2.13">Large amounts of data downloading and processing in python with facebook data as reference</a></td></tr> |
53 <tr><td class="right">13:10-13:50</td><td class="left">Ole Nielsen</td><td class="left"><a href="#sec2.25">Invited Speaker: <b>7 Steps to Python Software That Works</b></a></td></tr> |
54 <tr><td class="right">13:30-14:10</td><td class="left">Ole Nielsen</td><td class="left"><a href="#sec2.25">Invited Speaker: <b>7 Steps to Python Software That Works</b></a></td></tr> |
54 <tr><td class="right">13:50-14:20</td><td class="left">Kunal Puri</td><td class="left"><a href="#sec2.21">GPU Accelerated Computational Fluid Dynamics with Python</a></td></tr> |
55 <tr><td class="right">14:10-14:30</td><td class="left">Jaidev Deshpande</td><td class="left"><a href="#sec2.18">A Python Toolbox for the Hilbert-Huang Transform</a></td></tr> |
55 <tr><td class="right">14:20-14:50</td><td class="left">Chetan Giridhar</td><td class="left"><a href="#sec2.19">Diving in to Byte-code optimization in Python</a></td></tr> |
56 <tr><td class="right">14:30-15:00</td><td class="left">Chetan Giridhar</td><td class="left"><a href="#sec2.19">Diving in to Byte-code optimization in Python</a></td></tr> |
56 <tr><td class="right">14:50-15:10</td><td class="left">Mahendra Naik</td><td class="left"><a href="#sec2.13">Large amounts of data downloading and processing in python with facebook data as reference</a></td></tr> |
57 <tr><td class="right">15:00-15:30</td><td class="left"></td><td class="left"><b>Tea</b></td></tr> |
57 <tr><td class="right">15:10-15:40</td><td class="left"></td><td class="left"><b>Tea</b></td></tr> |
58 <tr><td class="right">15:30-16:00</td><td class="left">Kunal Puri</td><td class="left"><a href="#sec2.21">GPU Accelerated Computational Fluid Dynamics with Python</a></td></tr> |
58 <tr><td class="right">15:40-15:50</td><td class="left">Sachin Shinde</td><td class="left"><a href="#sec2.22">Reverse Engineering and python</a></td></tr> |
59 <tr><td class="right">16:00-16:10</td><td class="left">Sachin Shinde</td><td class="left"><a href="#sec2.22">Reverse Engineering and python</a></td></tr> |
59 <tr><td class="right">15:50-16:20</td><td class="left">Vishal Kanaujia</td><td class="left"><a href="#sec2.7">Exploiting the power of multicore for scientific computing in Python</a></td></tr> |
60 <tr><td class="right">16:10-16:40</td><td class="left">Vishal Kanaujia</td><td class="left"><a href="#sec2.7">Exploiting the power of multicore for scientific computing in Python</a></td></tr> |
60 <tr><td class="right">16:20-17:00</td><td class="left"></td><td class="left"><b>Lightning Talks</b></td></tr> |
61 <tr><td class="right">16:40-17:00</td><td class="left"></td><td class="left"><b>Lightning Talks</b></td></tr> |
|
62 </tbody> |
61 </tbody> |
63 </table> |
62 </table> |
64 <br/><br/> |
63 <br/><br/> |
65 |
64 |
66 <h2> Coverage</h2> |
65 <h2> Coverage</h2> |
74 a cluster of machine. Multiprocessing and Gearman ( a distributed job queue with Python bindings ) allows |
73 a cluster of machine. Multiprocessing and Gearman ( a distributed job queue with Python bindings ) allows |
75 any simple python script to go distributed with minimal refactoring.</p> |
74 any simple python script to go distributed with minimal refactoring.</p> |
76 <h4>Slides</h4> |
75 <h4>Slides</h4> |
77 <p>To be uploaded</p> |
76 <p>To be uploaded</p> |
78 |
77 |
79 <h3 id="sec2.3">Robson Benjamin : Automated Measurement of Magnetic properties of Ferro-Magnetic materials using Python</h3> |
78 <h3 id="sec2.3">William Natharaj P.S: Automated Measurement of Magnetic properties of Ferro-Magnetic materials using Python</h3> |
80 <h4>Abstract</h4> |
79 <h4>Abstract</h4> |
81 <p>Hysterisis is basically a phenomenon where the behaviour of a system depends on the way the system moves. |
80 <p>Hysterisis is basically a phenomenon where the behaviour of a system depends on the way the system moves. |
82 On increasing the magnetizing field H applied to a magnetic material , |
81 On increasing the magnetizing field H applied to a magnetic material , |
83 the corresponding induction B traces a different path when it increases from that when the field |
82 the corresponding induction B traces a different path when it increases from that when the field |
84 decreases tracing a loop. It is often referred to as the B-H loop.</p> |
83 decreases tracing a loop. It is often referred to as the B-H loop.</p> |