Knowledge Graphs for AI in the Enterprise

Columbia University presents the first major knowledge graph technology conference. Knowledge graphs are a defining technology that will transform data management in the next decades and we want to be leaders of the transformation. Knowledge graphs:

• provide an elegant solution to the complex problem of data management in the enterprise
• are a mature technology and adoption is growing fast
• have a very strong potential backed by decades of research

As an educational institution, we also realize there is a need to educate and enable a community to facilitate technology adoption. The goals of this conference are thus:

• to showcase major knowledge graphs implementations
• to educate on how knowledge graphs are built, maintained and used
• to build a community around technology leaders

We have gathered world experts representing leading organizations working with knowledge graphs. See below the list of speakers and presentations. We are building this conference as a yearly forum gathering the community around this topic. This year's theme: knowledge graphs for AI in the enterprise, will be strongly represented in the program.

The conference is organized by Francois Scharffe, the Applied Analytics Club of Columbia University and the Executive Education program of Columbia University School of Professional Studies.

Check out the conference Program

List of speakers, and presentations by topic

Applications in Digital Commerce...

Xiaoya Wei, Knowledge Graph Lead, Airbnb - Knowledge Graph at Airbnb

Subhabrata Mukherjee, Machine Learning Scientist, Amazon - Deep Learning for Knowledge Extraction and Integration to build the Amazon Product Graph

Joshua Shinavier, Research Scientist, Uber - Building an Enterprise Knowledge Graph at Uber: Lessons from Reality

Andrew Chumney, Managing Director, Single View Solutions, Pitney Bowes - Intelligent Customer Service Using Knowledge Graphs

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Applications in Financial Services...

Pierre Haren, CEO and Co-Founder, Causality Link - A Perspective on the Reasoning Power of Knowledge Graphs

Patricia Branum, Enterprise Data Governance, Capital One - Knowledge Graph Pilot Provides Value

Christos Boutsidis, Scientist and Software Engineer, Goldman Sachs - Pythia: the Goldman Sachs Social Graph

Arthur Keen, Senior Solutions Architect, TigerGraph - Analyzing Time-varying Transitive Risk in Swap Networks using Graphs

Tim Baker, Global Head of Applied Innovation, Refinitiv Financial - Practical Use Cases and Challenges to Implement Graphs in Financial Services: Combating Financial Crime

David Newman, SVP, Innovation R&D Group, Wells Fargo - Knowledge Graphs and AI: The Future of Financial Data

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Applications in Health Care, Government, Supply Chain, Libraries...

Tom Plasterer, Director, US Cross-Science, AstraZeneca - Fair Data Knowledge Graphs (From Theory to Practice)

Parsa Mirhaj, Director, Clinical Research Informatics, Montefiore Hospital - The Chasm of a Million Analytics, and How to Bridge it?

Lambert Hogenhout, Chief Analytics, Partnerships and Innovation, United Nations - A Graph as a Means to Store Unpredictable Knowledge – A Practical Implementation

Ron Snyder, Director of Research, JSTOR Labs - Why Wikibase? Why not?

Chris Brockman, CEO, Eccenca - Knowledge Graph for Digital Transformation in the Supply-Chain

Professor Soren Auer, Director, Head of Research Group, Data Science and Digital Libraries, German National Library of Science and Technology - Creating a knowledge graph based Enterprise Innovation Architecture

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Applications in Forensics...

Friedrich Lindenberg, Data Team Lead, OCCRP - Using Graphs and Data Integration to Track Organised Crime

Thomas Moran, Senior Data Scientist and Analytics Team Lead, Enigma.io - Impact and Insights from Public Data: Fighting Money Laundering by Linking and Resolving Entities

Tim Baker, Global Head of Applied Innovation, Refinitiv Financial - Practical Use Cases and Challenges to Implement Graphs in Financial Services: Combating Financial Crime

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How To...

Michael Tung, Founder and CEO Diffbot - Knowledge Graphs for AI

Teresa Tung, Manager Director, Accenture Labs - Using a Domain Knowledge Graph to Manage AI at Scale

Juan Sequeda, Co-Founder, Capsenta - Designing and Building Enterprise Knowledge Graphs from Relational Databases in the Real World

Denny Vrandecic, Ontologist, Google AI - Wikidata, Knowledge Graphs, and Beyond

Alfio Gliozzio, Research Manager, Knowledge Induction, IBM Research - Extending Knowledge Graphs using Distantly Supervised Deep Nets

Amy Hodler, Analytics Program Manager, Neo4J - A Real-World Guide to Building Your Knowledge Graphs

Vicky Froyen, Researcher, Collibra - Collibra's Context Graph

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Registration Fee: $450

Group enrollment and student benefits: Organizations enrolling two or more participants are eligible for a tuition benefit. Limited student ticket rates also available. Please email spsexeced@columbia.edu for details.

Cancellation Policy:
Full refunds of the program fee may be obtained through March 4, 2019; no refunds will be provided after this date. All notification of withdrawals must be sent in writing to Columbia School of Professional Studies. Columbia School of Professional Studies is not responsible for travel or related costs under any circumstances.

We recommend participants consider purchasing trip cancellation insurance in the unlikely event the program is cancelled or they cannot attend for personal or professional reason

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