European Big Data Value Forum Agenda by Whova

Natalie Cernecka

IMT

Natalie CERNECKA is the Head of Business Development at TeraLab, which is a trusted, secure, and sovereign data sharing platform to boost innovation and technology transfer. TeraLab is pwned by IMT, one of the leading French engineering schools. Natalie holds a PhD from the University of Cambridge, and has worked in academic positions in the UK, France, and Japan. She subsequently moved to tech, working in business development and partnership roles with focus on data science and AI. Natalie is a coorganiser of the meetup WiMLDS Paris, which promotes women working in data science and machine learning and counts over 3500 members.

Natalie is speaking at

Parallel session on Federating efforts to foster European Data-Driven Innovation (EUHubs4Data project sponsored session)

Focus Track 3 - Market uptake: Bringing AI and Data Sciences to Practice

November 4, 2020

2:00 pm - 3:30 pm

Speakers

Daniel Alonso Roman (Speaker) ITI - Artificial Intelligence & Big Data Partnerships Driver, BDVA i-Spaces group chair / EUHubs4Data coordinator
Ana García Robles (Parallel session chair) Secretary General, Big Data Value Association
Stefanie Lindstaedt (Speaker) CEO, Know-Center
Ernst Stoeckl-Pukall (Speaker) Head of the Digitization and Industry 4.0, BMWi
Dominik Rohrmus (Speaker) CTO, Labs Network Industrie 4.0
David Bisset (Speaker) Executive Director, euRobotics
Natalie Cernecka (Speaker) IMT
Holger Hoos (Speaker) Professor of Machine Learning, Leiden University
Maria Hajdu (Speaker) Programme Officer, European Commission

Description

Concept:

During this session, we will explore potential and existing models of collaboration/federation in cross-border initiatives that can be applied in a practical / realistic way to foster data driven innovation at European level, and make this innovation available and accessible to all actors in the European data landscape, in particular SMEs and Start-ups, as it is aimed in the project EUHubs4Data. Starting from a general view on needs, benefits and models of a federation, we will focus on specific and concrete aspects such as governance and structure, a federated catalogue / offer (including data sources, data governance, delivery of joint services and a common training programme), potential legal or organisational barriers, etc. We will also count with the experience of actors involved in existing and different types of federation and networks.

Objectives:

The expected outcome from this workshop aims to be a set of recommendations about the best options for each of the aspects considered, that could contribute, in the scope of EUHubs4Data project, to the establishment of federated network of data-driven experimentation facilities in Europe (with special focus on AI and Data service innovation development and experimentation), find synergies, share knowledge and assets, and let small and medium size actors on each region to benefit from latest European advances on those fields.

For more information on the EUHubs4Data project visit: https://euhubs4data.eu/

Parallel Session Towards an European AI skills ecosystem: Building the next generation of innovative, open and interoperable AI learning opportunities

Focus Track 4 - New challenges ahead: Data, AI and the new Society

November 4, 2020

4:30 pm - 5:30 pm

Speakers

Stefan Göllner (Parallel session chair) Innovation manager, Stifterverband / AI Campus
Jan Smith (Speaker) Professor, Chalmers University of Technology, Gothenburg Sweden
Amy Loutfi (Speaker) Professor, Pro-Vice Chancellor for Artificial Intelligence, Department of Science and Technology, Örebro University
Florian Rampelt (Speaker) Managing Director , AI Campus / KI-Campus
Natalie Cernecka (Speaker) IMT
Ville Valtonen (Speaker) Reaktor Education

Description

In order to realize the tremendous potentials that Artificial Intelligence and BIG DATA technologies are expected to have as a main driver for economical, technological and societal innovation, joint efforts are needed across Europe to improve AI skill across all fields of education and to make the best educational resources accessible for a broad community of learners.

In this session we ask for appropriate approaches to implement innovative, state-of-the-art learning opportunities and platforms. We focus on the topic of AI skills and open educational approaches (OER). We reflect such approaches from the perspective of higher education, research, non-formal education as well as further education and lifelong learning.

We also address the question, how national initiatives to facilitate online learning in the field of AI and Data Literacy can become better coordinated on a European level. The session wants to encourage joining forces to make high quality educational resources openly and widely accessible to students and lifelong learners across all member states.

Questions that are related to this challenge include:

Which learning opportunities and platforms, I. e. examples of good practice, do currently exist across Europe?
Which approaches have proved especially successful?
Which skills and competences should especially be focused on? Which professional fields could be a priority on European level
Which standards and guidelines for a European AI skills ecosystem could be developed?
Which approaches could ensure joint open standards and interoperability of platforms from different EU member states?

We bring together in this session practitioners on online learning, teaching experts, as well as political strategists that all have a profund interest in a conclusive implementation of a future oriented AI educational strategy.