Value Pack

Machine Learning & Artificial Intelligence Stage

Machine Learning and Artificial Intelligence Stage is one of the 5 stages you can attend during the third annual Data Innovation Summit 2018 in Stockholm. In this presentation you can explore the Machine Learning and Artificial Intelligence stage in detail, and learn why you and your team should attend the event and this stage. Once you have registered for the summit you can attend any of the five stages on the summit. Here we go!

Why attend

Machine Learning & Artificial Intelligence Stage

Technical and Automation focus

Artificial intelligence (AI) is no longer the future. For businesses, it is the here and now. And it is not used only in companies like Apple, Amazon, Tesla, Netflix, Nest and so on. Implementation can be found in almost every industry. Recent real-time examples are in the finance and legal sector.

Artificial Intelligence by it self is disruptive. It refers to set of computer science techniques that enable systems to perform tasks normally requiring human intelligence and interaction. Boosted with Machine Learning, Deep learning adaptation and learning algorithms., companies now can automise defined and undefined process and design new products and services.

On the Machine Learning and Artificial Intelligence Stage this year we will not focus on the futuristic aspect of Machine Learning and Artificial Intelligence, but more on practical implementation functionalities, like Artificial Narrow Intelligence (ANI), Robotic Process Automation (RPA), chatbots, neural networks and deep learning.

All presentations last 18 minutes + 2 min for quick Q&A.

What you will learn

  • Recognizing opportunities for Machine Intelligence and Machine Learning - Shani Offen, Spotify
  • Leveraging Machine Learning for gaining Competitive Advantage - Jim Aldon D´Souza, TomTom
  • More AI steel, less dashboards - Markus Virtanen, Valio
  • The Paradigm Shift of the Enterprise R&D - Jesse Chao, Ericsson AB
  • Democratization of AI – making state-of-the-art techniques available for all - Luka Crnkovic-Friis, Peltarion
  • Tinder for Robots – Process meets automation - Bjoern Ebeling, Merck KGaA
  • Adaptive Infrastructure (AI): Making Infrastructure Intelligent - Ritesh Agrawal, Uber
  • Implementing Machine learning and Artificial Intelligence in your Analytics efforts
  • Developing Algorithms and leveraging AI to drive Profit, CX and Growth
  • How to leverage Analytics and AI applications to Improve Efficiency and Standardisation
  • Machine Learning Innovation to power intelligent business decisions
  • How AI and Chatbots are transforming the Customer Experience
Speakers are the ones who make events unforgettable, exciting and insightful.

Here are some of the awesome speakers on the ML / AI Stage

Shani Offen

Machine Learning Lead


Shani got her PhD in neuroscience from NYU in 2008, with a focus on computational vision. At Spotify, she leads a machine learning team in the quest to make audio ads interactive, relevant, and measurably effective. This effort spans many areas of ML and AI, from algorithms to infrastructure. Her favorite algorithm is division, she is amused by superstitious pigeons, and she recommends fiction as a good way to expand your priors.

Jim Aldon D´Souza

Autonomous Driving Engineer


Jim is a research engineer working with autonomous driving systems at TomTom. His primary interests lie in the perception, localization, and mapping aspects of self-driving technology.

Jim has a master's in electrical engineering from the Technical University of Denmark, and a bachelor's from National Institute of Technology Karnataka, India. His master's thesis addresses the localization issues faced by a planetary rover when navigating in a symmetrical and featureless environment such as the one on the surface of Mars. It was concluded in 2016 at the German Research Center for Artificial Intelligence in Bremen, Germany.

Markus Virtanen

Chief Data Scientist


M.Sc (Tech, Computer Science) with research focus in statistical modeling and machine learning for time series data. Markus is teaching open source computational algorithms using Python, R and Hadoop ecosystem.

Luka Crnkovic-Friis



Bjoern Ebeling

Innovation Manager

Merck KGaA

The Digital Platform Team for Merck Business Services combines competencies in user experience, future analytics, cloud integration and digital efficiency. Bjoern´s role is to coordinate the team and to relate business needs with technology.

Ritesh Agrawal

Senior Data Scientist


A leading data scientist for optimizing infrastructure, Ritesh Agrawal at Uber leads the Infrastructure Analytics and Science (IAS) team. The team focuses on scaling data infrastructure for Uber’s growing business needs now and foreseeable in the future. Before Uber, Ritesh specialized in predictive and ranking models at Netflix, AT&T Labs and Yellow Pages where he built scalable machine learning infrastructure with technologies such as Docker, Hadoop, Spark, and more. A Ph.D. scholar from Pennsylvania State University (State College) in Environmental Earth Science, Ritesh’s thesis focused on computational tools and technologies such as concept map ontologies.

Register Today

Prices from 2390 SEK

About the event

The Data Innovation Summit is an annual one day event in Stockholm bringing together the most innovative minds, enterprise practitioners, technology providers, start-ups and academics, working with Data Science, Big Data, Analytics, AI, IOT and Data Management. With over 60 Nordic and international speakers on five stages and plenty of learning and networking activities in the exhibition area, the 2018 summit is the place to be for all professionals and organisations working with utilisation of data for increasing profit, reinventing business models, develop data-driven products, and increasing customer satisfaction.

Created By
Hyperight AB

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