Conference Digital Economy 23-26 July 2017 with over 100 sessions - San Fancisco, CA
Dr. Daniel Dahlmeier

Dr. Daniel Dahlmeier

Development manager SAP
Mir Nawab Hussain

Mir Nawab Hussain

IT Consultant , msg systems
Mariya Savinova

Mariya Savinova

Senior Business Development Manager, SIRFULL
Christophe Bourguignat

Christophe Bourguignat

CO-Founder and CEO Zelros
Bernard Debauche

Bernard Debauche

Chief Product Officer Systancia

Robin Hirt

Robin Hirt

AI enthusiast and scientist
Ingmar Wolff

Ingmar Wolff

Ai-Startup-founder and computer scientist
Dr. Oliver Mauss

Dr. Oliver Mauss

Chief Executive Officer at PlusServer Group
Prof. Dr. Michael Feindt

Prof. Dr. Michael Feindt

Founder and Chief Scientist of Blue Yonder
Dr. -Ing. Julia Hoxha

Dr. -Ing. Julia Hoxha

Co-founder and CEO Zana Technologies GmbH

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Admired By The A-List

Grand Conference Hall - 881 7th Ave New York, NY

Even if you’re not a high roller, you can arrive like one. If you’re planning on hitting the tables, Luxor Limo can get you there with sophistication and style. Let the action begin at your front door. With a limo, you can get the excitement started, and the champagne flowing, long before the first roll of the dice.

Conference Schedule

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  • 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. incontext.technology 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.

  • 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.

    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.

  • 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.


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