Artificial Intelligence


Artificial Intelligence meets Intelligence Artificielle

Be part of the first French-German conference on the application of artificial intelligence!
Enjoy concret use cases and panel discussion about the application areas of artificial intelligence from Germany, France and the world!

Conference Day | October 1st
Location: ZKM – Zentrum für Kunst und Medien Karlsruhe | Karlsruhe, Germany

Workshop Day | October 2nd
Location: CyberForum e.V. | Karlsruhe, Germany

Join us and explore how to tackle the application of AI for your business!


Jean-Louis Queguiner

CTO Data & IA at OVH

Graduated in computer science at University of Québec in Canada and in Mechanical engineering at Arts et Metiers ParisTech, Jean-Louis held several positions in various industrial environments and worked as CTO for Auchan retail international.

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Prof. Dr. Michael Feindt

Founder and Chief Scientist of Blue Yonder

Keynote II: AI as Chance for Sustainability and Fairness

Prof. Feindt’s main experience and most successful research work is data driven software development, understanding and learning effects through data analysis, usage, further development and discovery of new multivariate statistical algorithms and respective software (today labelled “predictive analytics” or “machine learning’’) in big data environments.

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Antoine Blondeau

Alpha Intelligence Capital

Keynote III: Artificial Intelligence – Hype or Reality?

Antoine Blondeau is co-founder and Managing Partner of Alpha Intelligence Capital, a venture capital firm investing in deep algorithmic science-based Artificial Intelligence companies, globally. A seasoned entrepreneur and investor, Antoine has 25 years of experience in the technology industry, having held senior leadership positions at Good Technology,, and Sybase.

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Check out our various Panel sessions on the application of AI – how does artificial intelligence influence our daily (working) life? Concrete Use Cases from practitioners will open up this “black box” of potential.

AI & Technologies

AI technology has led to major improvements in human-like perception of machines. Natural language processing and image recognition are reliably used in commercial applications today and only the beginning of possibilities and methods businesses can apply.

AI & Business

AI can provide a competitive advantage in most industries. The possible applications penetrate any business areas.  From “intelligent” chatbots to predictive analytics, AI is on the advance. Hence, the impact of AI on Businesses will be transformative.  What will future professions look like and how can we leverage the most of humans and AI working together?

AI & Ethics

With great power comes great responsibility. AI technology has challenged the status quo of humans as decision maker. What is the best (European) way to tackle those future-oriented decisions that need to be made for a “humane” symbiosis of AI and Humans?

AI industry solutions: Production

Digitalization of production systems has enabled the massive gathering of data. AI can make meaningful use of this data. From predicting malfunctions of machines and finding root causes to new methods in quality assurance, there is great potential. Close human-robot collaboration is on the advance. AI can reinforce the collaboration by “humanizing” the robot behaviour. To what extent is this already reality in production?

AI industry solutions: Mobility

What modes of transport will we use in the future?  AI has the prospect to play a major role and help solve current mobility problems. Check out the latest developments presented in this session.

AI industry solutions: Retail/E-Commerce

Possible applications of AI encompass the entire product and service cycle in Retail. From supply chain planning (85%) and demand forecasting (85%), to customer intelligence (79%), AI will revolutionize retail. — IBM, 2019

  • Sessions

    3rd December

  • Michael Klingel: Network state estimation for the renewable energy transition

    The energy transition is taking place - through the expansion of renewable energies and the market ramp-up of electromobility - in the distribution grid. As a result, power generation is increasingly migrating to medium and low voltage. This dynamic is accompanied by new challenges for distribution network operators: they have to deal with bidirectional power flows and enormous peak loads - and all this with huge network areas. This is only possible with innovative approaches and the inclusion of artificial intelligence!

    Dr. Cyrille Waguet: AI for resilient infrastructures

    Timely maintenance of railway tracks is crucial for resilience, comfort and safety in rail traffic. It increases the acceptance of rail transport and its sustainability. developed a smart monitor for rails which identifies and categorises anomalies on railway tracks by analysing sensor data based on daily train operations. Connected to the operator’s business processes, the resulting digital twin of the tracks keeps the maintenance teams up to date about the rail conditions and their expected evolution.

  • Francois Werner

    Grand Est Region: an ambition to lead in terms of innovation, competitiveness, job creation and attractivity. The 2019 adopted regional plan for Artificial Intelligence is built around 5 strategic axes: Boosting business competitiveness through AI Supporting scientific excellence, ensuring its outreach and valorization Energizing AI start-ups. Training AI competences and skills Securing an ethical, transparent and inclusive IA It focuses on 3 sectors : health, industrie and bioeconomy.

  • Stéphane Canu: French Strategy on artificial intelligence

    French-German cooperation and its implementation modalities, in particular via calls for projects already implemented or to be implemented in the future will be presented.

    Lisa Kratochwill: Artificial Intelligence – from Hype to Reality for the Energy Industry

    Looking at artificial intelligence as hyped technology no longer seems to be appropriate - it has already penetrated most sectors as a key technology. Especially in the energy sector the high efficiency potential of AI has been very well received - much faster than expected. In dena’s new AI-analysis the most promising fields of application for AI in the energy industry are classified and an initial assessment is carried out to examine the opportunities and challenges.

  • Prof. Dr.-Ing. Gisela Lanza: Artificial Intelligence - The new production manager

    The possible industrial applications of artificial intelligence (AI) are manifold. There are AI systems that perform quality inspection more reliably than humans as well as systems that support engineers in the design phase. Thus, will entire factories soon be managed by AI? Practical examples demonstrate what AI systems can already do, where they are already applied and what limits prevail. Altogether, the new role of production managers will be projected.

    Korbinian Weiß: Sorting Guide – AI development at TRUMPF

    To tackle the complexity of sheet metal production AI solutions can help make this manageable. The overall efficiency of laser cutting of sheet metal can be greatly improved by new tools to minimize waste an increase speed in production. Learn how a AI solution utilizes computer vision to support the worker on the shop floor.

    Dr. Hannes Sieling: AI-Enabled Price Markdowns for Groceries in Real-Time

    AI allows retailers to translate business decisions at scale with a high degree of automation. As grocery retailers experience intensifying competition, they need to manage pricing processes for expiring products to balance profitability and waste. Learn how AI enables the full utilization of intraday POS data and real-time decision making to manage markdowns. Markdown pricing contributes to sustainability goals by minimising and controlling waste based on the retailer’s business strategy.

    Guillaume Cazenave: Computer Vision for gains in efficiency and cost saving

    There are a growing number of Computer Vision (CV) use cases for increasing efficiency and cost savings of organisations. Prior the Edge AI CV revolution, cameras were used by agents for limited visual monitoring actions. Most of the time, agents could at best see an incident at it was occurring or investigate after it happened. With the implementation of Edge AI CV, a single agent can monitor multiple sites remotely and leverage camera infrastructure and AI to prevent incidents and take proactive decisions. This result in significant improvement in business process and reduction in product loss for an increase in ROI of organisations.

    Sébastien Picardat: The challenges of AI and data in agriculture

    Decision tools used in precision agriculture and integrating AI are designed using useful digital agricultural data. These data come from the many connected objects in place in farms: weather sensors, drones, electronic loops, etc. By relying on reliable data, exchanged with the consent of farmers, AI can make a major contribution to the sustainability of the agricultural sector.

  • Dr.-Ing. Robin Hirt:

    AI will open up remarkable opportunities by learning from our data. However, we need to ensure that this exact data is kept safe during the process.

    Thomas Mann:

    AI is the driver of progress of this century - the automation of processes, enabling opportunities for more sustainable prosperity.

    Katia Hilal:

    The industry desperately lacks historical failure data to train Machine Learning algorithms. Blind failure prediction means we predict equipment failures without historical failure data. Magical? No, we invented scientific methods to generate highly discriminant health indicators from industrial time series.




Main Host

Katrin-Cécile Ziegler

Katrin-Cécile is a digital economist, speaker and journalist. She has been involved with the digital transformation for 15 years, has served as a leader in various sectors for many years, and is a multiple media award winner.
From 2009-2017 Katrin-Cécile worked as Editor-in-chief and Newsanchor of a southern German TV station.
As a freelance host, she is specialized in topics all around digitalization and is especially fascinated by the limitless possibilities of artificial intelligence and IoT.


Moderation Session I & II

Dr.-Ing. Matthias Richter

After his studies of computer science with specialization in computer vision, Dr.-Ing. Matthias Richter received his doctorate in computer graphics and media art at the KIT on the Application of Mechanical Learning Methods in the Industrial Checking. Since 2019 Matthias Richter is working as Machine Learning Engineer at inovex, where he helped customers with the conception, implementation and scaling of learning systems for productive use.

Matthias Richter is co-founder and organizer of organizes regular lectures on the subject of machine learning and Artificial Intelligence in the Karlsruhe area and has meanwhile developed more than 1400 members.


Moderation Session I & II

Dr.-Ing. Julius Pfrommer

Dr.-Ing. Julius Pfrommer has worked as an industrial engineer in Karlsruhe and Grenoble and received his doctorate in computer science at the KIT. Since 2018, Julius Pfrommer has been in charge of a research group at the Fraunhofer IOSB in Karlsruhe. His field of interest is the Application of machine learning to optimize physical processes with Applications ranging from manufacturing processes to the control of Combustion engines.

Julius Pfrommer is co-initiator and organizer of


Would you like to support AIxIA as a sponsor or partner and promote Artifcial Intelligence this way?
Then contact our project managers and help us create a conference of superlatives with us!

Christin Eckerle
Innovation & Digital Ecosystems

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