Past Presentations

Building a Machine Learning Factory: Going from Science Projects to Mission-Critical Execution of Machine Augmented Analytics

Building a Machine Learning Factory: Going from Science Projects to Mission-Critical Execution of Machine Augmented Analytics

Innovation can and does occur in Bill Hewlett’s garage, but ultimately you need a production-strength ISO 9001 factory. This is also true for high performance data analysis projects. R and python are great tools for research and for science projects -- in the best sense of the word. Innovative approaches to get new analytic outcomes are crucial to address the challenge of sense-making in a complex data world.

But, once the lab project is proven to be a valuable analysis method, we must make it performant, manageable, and make it scale to work with data volumes that are meaningful for the mission, not just with experimental sample data sets. In this talk we will learn how SAP, the world’s largest Enterprise Software company, approaches the problem of managing the execution of innovative machine learning and artificial intelligence algorithms to solve hard analytical problems. We will discuss how to empower the data science team at your organization to innovate with tools they are comfortable and familiar with, yet deliver their innovation to the mission in a way that is powerful and secure.

Presentation by Bob Palmer, VP Software Solutions, SAP: NS2, National Security

Using Dark Data and Data Science to Track the Money Trail

Using Dark Data and Data Science to Track the Money Trail

  • Empowering analysts to extract information from ‘dark data’ sources
  • Crafting advanced predictive models, with minimal data science skills, to automatically identify suspicious banking transactions
  • Tracking down dangerous non-state actors before they can fund threatening operations

Presentation by Doug Ellis, VP Global Solution Architects, Altair

The Challenges of Going Dark

The Challenges of Going Dark

Exploring alternative analytical methods that can help to circumvent the limitations posed by encryption of data

Presentation by Frederic Lemieux, Professor of the Practice and Faculty Director of the MPS in Applied Intelligence, Georgetown University

IARPA’s New Developments in Processing Data to Support Infrastructure

IARPA’s New Developments in Processing Data to Support Infrastructure

Dr. Jason Matheny, Director of IARPA for the Office of the Director of National Intelligence, shares R&D approaches to support intelligence agencies efforts and how the implementation of machine learning and automated systems is increasing optimization.