Data Science and Artificial Intelligence

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== ICube Data Science and Artificial Intelligence ==
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__NOTOC__
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=== When ===
 
=== When ===
 
<p>Thursday November 7th, 2019</p>
 
<p>Thursday November 7th, 2019</p>
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<p>9:00am - 15:30pm</p>
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<p>9:00am - 16:00pm</p>
  
 
===Where ===
 
===Where ===
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<p>ICube Laboratory, 300 Bd Sébastien Brant, 67400 Illkirch-Graffenstaden<br>(<i>Room A207</i>).</p>
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<p>ICube Laboratory, 300 Bd Sébastien Brant, 67400 Illkirch-Graffenstaden - <b>Room A207</b></p>
 
<p>[https://goo.gl/maps/XVoh1KzCHzGMekSm6 Google map direction]</p>
 
<p>[https://goo.gl/maps/XVoh1KzCHzGMekSm6 Google map direction]</p>
  
 
=== Registration ===
 
=== Registration ===
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<p>If you want to attend the workshop, please register here: [link]</p>
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<p>If you want to attend the workshop, please register [https://evento.renater.fr/survey/dsai-workshop-novemb...-bw7us7tv here] by '''November 5'''</p>
  
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=== Temporary program ===
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=== Program ===
  
 
{| class="wikitable"
 
{| class="wikitable"
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!colspan="3"|09:00 -  Introduction
 +
|-
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| <i>Long presentation</i> || Romain Orhand     ||  CSTB || Towards autonomy and explainability in Artificial Intelligence
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|-
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| <i>Long presentation</i> || Vinkle Srivastav  || AVR || Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images
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|-
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|      <i>Short presentation</i> || Pascal Guehl     || IGG || Creative AI for Texture Synthesis
 +
|-
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| <i>Short presentation</i> || Hugo Gangloff    || IMAGeS || Automatic Segmentation of Atherosclerotic Cross-Sections of Arteries with Deep Learning
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|-
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| <i>Meet&Match</i> || Yves-Andre Chapuis || MaCEPV || Accelerated Development of Materials and Devices via Data Analytics and Artificial Intelligence
 
|-
 
|-
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| 09:00 Introduction
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| <i>Meet&Match</i> || Pei Zhang || CSIP || Inventive design in AI context
 
|-
 
|-
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| Romain Orhand     ||   CSTB || Towards autonomy and explainability in Artificial Intelligence
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| <i>Meet&Match</i> || Enagnon Aguénounon || IPP || Fast spatial frequency imaging parameters extraction using generative network
 
|-
 
|-
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| Vinkle Srivastav  || AVR || Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images
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| <i>Meet&Match</i> || Morgan Madec || SMH || Optical recognition of bacteria
 
|-
 
|-
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|       Pascal Guehl     || IGG || Creative AI for Texture Synthesis
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!colspan="3"| 10:30 - Coffee break  -  11:00
 
|-
 
|-
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| Hugo Gangloff    || IMAGeS || Automatic Segmentation of Atherosclerotic Cross-Sections of Arteries with Deep Learning
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| <i>Long presentation</i> ||Emmanuelle Claeys || SDC || Reinforcement learning with time series
 
|-
 
|-
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| Yves-Andre Chapuis || MaCEPV || Accelerated Development of Materials and Devices via Data Analytics and Artificial Intelligence
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| <i>Long presentation</i> ||Anne Jeannin-Girardon || CSTB || Transfer Learning: review and recent advances
 
|-
 
|-
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| Pei Zhang || CSIP || Inventive design in AI context
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| <i>Short presentation</i> ||Bertrand Goldman || ISU || Stellar streams in the Gaia mission area
 
|-
 
|-
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| Enagnon Aguénounon || IPP || Fast spatial frequency imaging parameters extraction using generative network
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| <i>Short presentation</i> ||Chinedu Nwoye || AVR || Weakly-supervised convolutional LSTM approach for surgical tool tracking in laparoscopic videos.
 
|-
 
|-
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| Morgan Madec || SMH || Optical recognition of bacteria
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| <i>Short presentation</i> ||Xin Ni || CSIP || An approach merging the IDM-related knowledge
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| 10:30 Break
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|-
 +
| <i>Short presentation</i> ||Michal Parusinski || SERTIT || AI at SERTIT for remote sensing
 +
|-
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!colspan="3"| 12:20 - Lunch - 14:00
 +
|-
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| <i>Long presentation</i> ||Argheesh Bhanot || IMAGeS || Online dictionary learning for single-subject fMRI data unmixing
 +
|-
 +
| <i>Long presentation</i> ||Birgitta Dresp-Langley || IGG || The quantization error in the Self-Organizing Map (SOM) output as a diagnostic tool for single-pixel change in complex patterns
 +
|-
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| <i>Short presentation</i> ||Hyewon Seo || || Generating 3D Facial Expressions with RNN
 +
|-
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| <i>Short presentation</i> ||Simon Chatelin || AVR || Machine learning for elasticity imaging in biological soft tissue
 +
|-
 +
| <i>Short presentation</i> ||Stella Marc-Zwecker || SDC || Spatio-temporal data modeling using graphs
 +
|-
 +
| <i>Short presentation</i> ||Thomas Weber || CSTB || RADMEL: An ensemble predictor to reveal disease-relevant missense variants with low degree of uncertainty
 +
|-
 +
| <i>Short presentation</i> ||Baptiste Lafabregue || SDC || A comparison of unsupervised representation learning  methods for time series
 +
|-
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| <i>Short presentation</i> ||Claudine Mayer || CSTB || Deep learning for protein fold recognition
 +
|-
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!colspan="3"| 15:30 - Closing and coffee break -  16:00
 
|}
 
|}
  
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=== Format ===
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- The workshop will be held in English
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11:00
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- Long presentation are 20mn (15mn talk + 5mn questions)
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1 Emmanuelle Claeys SDC Reinforcement learning with time series
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- Short presentation are 10mn (5-7mn talk + 5-3mn questions)
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2 Anne Jeannin-Girardon CSTB Transfer Learning: review and recent advances
+
- Meet & Match are 5mn (5mn talk before the coffee break to allow for discussions with potential collaborators)
−
3 Bertrand Goldman Other Stellar streams in the Gaia mission area
 
−
4 Chinedu Nwoye AVR Weakly-supervised convolutional LSTM approach for surgical tool tracking in laparoscopic videos.
 
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5 Xin Ni CSIP An approach merging the IDM-related knowledge
 
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6 Michal Parusinski Other AI at SERTIT for remote sensing
 
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12:20 Lunch
 
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14:00
 
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1 Argheesh Bhanot IMAGeS Online dictionary learning for single-subject fMRI data unmixing
 
−
2 Birgitta Dresp-Langley IGG The quantization error in the Self-Organizing Map (SOM) output as a diagnostic tool for single-pixel change in complex patterns
 
−
3 Hyewon Seo Other Generating 3D Facial Expressions with RNN
 
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4 Simon Chatelin AVR Machine learning for elasticity imaging in biological soft tissue
 
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5 Stella MARC-ZWECKER SDC Spatio-temporal data modeling using graphs
 
−
6 Thomas Weber CSTB RADMEL: An ensemble predictor to reveal disease-relevant missense variants with low degree of uncertainty
 
−
7 Baptiste Lafabregue SDC A comparison of unsupervised representation learning  methods for time series
 

Version actuelle datée du 4 novembre 2019 à 20:15

When

Thursday November 7th, 2019

9:00am - 16:00pm

Where

ICube Laboratory, 300 Bd Sébastien Brant, 67400 Illkirch-Graffenstaden - Room A207

Google map direction

Registration

If you want to attend the workshop, please register here by November 5

Program

09:00 - Introduction
Long presentation Romain Orhand CSTB Towards autonomy and explainability in Artificial Intelligence
Long presentation Vinkle Srivastav AVR Human Pose Estimation on Privacy-Preserving Low-Resolution Depth Images
Short presentation Pascal Guehl IGG Creative AI for Texture Synthesis
Short presentation Hugo Gangloff IMAGeS Automatic Segmentation of Atherosclerotic Cross-Sections of Arteries with Deep Learning
Meet&Match Yves-Andre Chapuis MaCEPV Accelerated Development of Materials and Devices via Data Analytics and Artificial Intelligence
Meet&Match Pei Zhang CSIP Inventive design in AI context
Meet&Match Enagnon Aguénounon IPP Fast spatial frequency imaging parameters extraction using generative network
Meet&Match Morgan Madec SMH Optical recognition of bacteria
10:30 - Coffee break - 11:00
Long presentation Emmanuelle Claeys SDC Reinforcement learning with time series
Long presentation Anne Jeannin-Girardon CSTB Transfer Learning: review and recent advances
Short presentation Bertrand Goldman ISU Stellar streams in the Gaia mission area
Short presentation Chinedu Nwoye AVR Weakly-supervised convolutional LSTM approach for surgical tool tracking in laparoscopic videos.
Short presentation Xin Ni CSIP An approach merging the IDM-related knowledge
Short presentation Michal Parusinski SERTIT AI at SERTIT for remote sensing
12:20 - Lunch - 14:00
Long presentation Argheesh Bhanot IMAGeS Online dictionary learning for single-subject fMRI data unmixing
Long presentation Birgitta Dresp-Langley IGG The quantization error in the Self-Organizing Map (SOM) output as a diagnostic tool for single-pixel change in complex patterns
Short presentation Hyewon Seo Generating 3D Facial Expressions with RNN
Short presentation Simon Chatelin AVR Machine learning for elasticity imaging in biological soft tissue
Short presentation Stella Marc-Zwecker SDC Spatio-temporal data modeling using graphs
Short presentation Thomas Weber CSTB RADMEL: An ensemble predictor to reveal disease-relevant missense variants with low degree of uncertainty
Short presentation Baptiste Lafabregue SDC A comparison of unsupervised representation learning methods for time series
Short presentation Claudine Mayer CSTB Deep learning for protein fold recognition
15:30 - Closing and coffee break - 16:00

Format

- The workshop will be held in English
- Long presentation are 20mn (15mn talk + 5mn questions)
- Short presentation are 10mn (5-7mn talk + 5-3mn questions)
- Meet & Match are 5mn (5mn talk before the coffee break to allow for discussions with potential collaborators)
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