Join more than 30 leading AI researchers and practitioners to discuss the shifting paradigm from model centric AI to data centric AI.

During more than 16 keynotes and panel sessions we will discuss the latest AI discoveries that have a true impact on the development of future technologies.
What
Virtual
Conference
When
Nov 9th, 2021
9 AM - 9 PM
Where
Online

Learn about

While AI has been pretty focused on models, the real-world experience of those who put models into production is that most of the time the data matters more.

The DCAID brings together academics and practitioners to share their vision and ideas about the future of AI.

Some of the topics covered:
Data quality monitoring and improvement
Data augmentation
Data selection
Model training with noisy data
MLOps at scale
Declarative ML systems
Data-centric AI case studies
And much more.

Conference schedule

9:00
AM
Overview of France's strategy on data sovereignty
Renaud Vedel, Coordinator of France’s national strategy on Artificial Intelligence
9:30
AM
Introduction to Data Centric AI
Francois-Xavier Leduc, CEO and Cofonder of Kili Technology
09:40
AM
Changing the world by changing the data
Anna Rogers, Postdoctoral Researcher at the University of Copenhagen
10:00
AM
Better models through better training data
Edouard d’Archimbaud, Co-Founder & CTO at Kili Technology
10:30
AM
Resources for multilingual NLP in the neural era: the examples of OSCAR and CamemBERT
Benoît Sagot, Research Director at Inria
11:00
AM
Panel 1: Data in practice.
How data quality can be monitored and improved?
  • Thomas Michel, Senior Data Scientist at Jellysmack
  • Aymen Shabou, Head of AI at Groupe Crédit Agricole
  • Roland Acra, Senior VP & CTO at Cisco
11:30
PM
From cleaning before ML to cleaning for ML
Félix Neutatz, Research Associate at Technische Universität Berlin
12:00
AM
Limitations of Autoregressive Models and Their Alternatives
Chu-Cheng Lin, Research Assistant at Carnegie Mellon University
12:20
AM
Group fairness: recent developments and challenges.
Evgenii Chzhen, Research scientist at CNRS/Université Paris-Saclay
12:35
AM
The role of data in end to end learned autonomy
Fergal Cotter, Head of the Perception team at Wayve
13:00
AM
Break
13:30
PM
Continual learning and interactive data collection
Antoine Bordes, AI Researcher at Facebook
14:00
PM
The role of data-centric AI in visual control
Karim Sayadi, Delivery Manager at OCTO Technology
14:30
PM
Panel 2: Model in practice. How can we train models with imperfect labels? How DevOps for data centric AI can help scale AI in the company?
  • Léo Dreyfus-Schmidt, VP of Research at Dataiku
  • Anne Wu, PhD Student at Cornell University
  • Jean-Louis Quéguiner, Research & Innovation at OVHcloud
  • Victor Storchan, AI/ML Lead at JPMorgan Chase & Co
15:30
PM
Declarative ML systems
Piero Molino, Co-Founder at Stealth Startup
16:00
PM
Human in the loop: Lessons learned from AI projects in enterprise
Khemon Beh, Managing Data Scientist
16:30
PM
Why and how to care about ML ethics
Clement Delangue, Hugging Face CEO and co-founder
17:00
PM
Augmenting bladder cancer diagnostic utilizing unstructured data
Thibaut Troude, CTO at VitaDX
17:30
PM
Closing remarks and physical event
Opening of the cocktail

Ready to learn about the future of AI ?

Join the event