Knowledge Graphs for AI in the EnterpriseColumbia University presents the first major knowledge graph technology conference. Knowledge graphs are a defining technology that will transform data management in the next decades & 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 & 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 & 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 & 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 & 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 & the Executive Education program of Columbia University School of Professional Studies.
List of speakers, & 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 & 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
Applications inFinancial Services...
Pierre Haren, CEO & 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 & 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 & Challenges to Implement Graphs in Financial Services: Combating Financial Crime
David Newman, SVP, Innovation R&D Group, Wells Fargo -Knowledge Graphs & AI: The Future of Financial Data
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, & How to Bridge it?
Lambert Hogenhout, Chief Analytics, Partnerships & 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 & Digital Libraries, German National Library of Science & Technology- Creating a knowledge graph based Enterprise Innovation Architecture
Applications in Forensics...
Friedrich Lindenberg,Data Team Lead, OCCRP-Using Graphs & Data Integration to Track Organised Crime
Thomas Moran,Senior Data ScientistandAnalytics Team Lead, Enigma.io-Impact & Insights from Public Data: Fighting Money Laundering by Linking & Resolving Entities
Tim Baker,Global Head of Applied Innovation, Refinitiv Financial-Practical Use Cases & Challenges to Implement Graphs in Financial Services: Combating Financial Crime
Michael Tung, Founder & 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 & Building Enterprise Knowledge Graphs from Relational Databases in the Real World
Denny Vrandecic,Ontologist, Google AI-Wikidata, Knowledge Graphs, & Beyond
Alfio Gliozzio, Research Manager, Knowledge Induction, IBM Research -Extending Knowledge Graphs using Distantly Supervised Deep Nets
Benjamin Han, Principal ML & Data Scientist, NLP Researcher, Microsoft -Building a Large-scale, Accurate & Fresh Knowledge Graph
Amy Hodler, Analytics Program Manager, Neo4J -A Real-World Guide to Building Your Knowledge Graphs
Vicky Froyen,Researcher, Collibra- Collibra's Context Graph
Group enrollment & student benefits:Organizations enrolling two or more participants are eligible for a tuition benefit. Limited student ticket rates also available. Please email email@example.com 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