Prof. Dr. Erik Graf

Steckbrief

Prof. Dr. Erik Graf Dozent

  • Adresse Berner Fachhochschule
    Technik und Informatik
    Abt Informatik
    Höheweg 80
    2502 Biel

Tätigkeiten

  • Head of Data Engineering Specialisation

Lehre

  • BsC Computer Science

  • Database Systems

  • Data Engineering Life Cycle

  • Deep Learning

Forschung

  • Natural Language Processing

  • Fin-Tech, Legal-Tech Applications

  • Applied Machine Learning Applications

  • Interactive Machine Learning

  • Intelligent Automation

  • Intelligent Search

Lebenslauf

  • Professor Graf has over 12 years’ industrial R&D experience in the fields of natural language processing and information retrieval in multinational companies and startups. His passion lies in the development of scalable artificial-intelligence and machine-learning solutions for real-world problems. He obtained his PhD at the University of Glasgow, exploring information retrieval based on human information processing. His general research interest lies at the intersection of cognitive science, IR, and NLP. He has worked or collaborated with several academic and industry research groups, including the HP Information Dynamics Lab, IBM Labs, the Glasgow IR Group, and the Sheffield NLP Research Group. As Chief Scientific Officer at Cortical.io, he has been responsible for the development of successful commercial NLP solutions for large enterprises. These include the Cortical.io Retina, which enables semantic searching of big text data, and the Cortical.io Contract Intelligence Engine, which automates extraction of key information from large volumes of legal documents. His current role as Professor for Data Engineering centres around the successful application of "AI" technologies in the context of applied research, teaching and entrepreneurship.
  • 2013-2017 Chief Scientific Officer (CSO) Cortical.io
  • PhD University of Glasgow

Projekte

Mitgliedschaften

  • Data Science and Engineering Research Group

  • ACM

  • Member of the Swiss Profile Commission "Master of Engineering Data Science"

Auszeichnungen

Sprachen- und Länderkenntnisse

  • Deutsch - Muttersprache oder zweisprachig
  • Englisch - Muttersprache oder zweisprachig
  • Französisch - Konversationssicher
  • Japanisch - Konversationssicher