September 14, 2018: Keynote Talk “Navigating the rapidly changing data landscape with AI/ML: the pragmatic economic opportunity of big data”

2018 Data Science Day

  • Date: Friday. Sep 14, 2018
  • Location: Union ballroom

Sponsored By

School of Computing

Agenda

9:00 AM – 1:00 PM   PIPELINE Career Expo
1:00 PM – 2:00 PM   Posters and Demos
2:00 PM – 2:30 PM   Welcome address: Dan Reed, Senior Vice President for Academic Affairs
2:30 PM – 3:30 PM   Panel: Data Science in Industry
3:30 PM – 4:50 PM   Data Science + X Talks
5:00 PM – 6:00 PM   Keynote Talk
6:00 PM – 6:15 PM   Poster Awards !!

Keynote Talk

Usama M. Fayyad

SpeakerUsama M. Fayyad, PhD. Co-Founder & CTO, OODA Health (Twitter @usamaf)

Talk TitleNavigating the rapidly changing data landscape with AI/ML: the pragmatic economic opportunity of big data

Abstract: Unstructured data and big data platforms have forced a disruptive change that has left most enterprises in data chaos. The combination of new economic drivers in enterprise computing, the need to leverage semi-structured and unstructured data, and the emergence of the Internet of Things (IOT), is driving a dramatic shift in the enterprise data landscape. Hadoop and the open source stack have accelerated the changes to a point of confusion. This has led business data analysts to face a bewildering environment of technologies and challenges involving semi-structured and unstructured data with access methodologies that have almost no relation to the past. IT and business users face equal confusion. Yet, the ability to drive significant business value from “data assets” has never been greater.

In this talk, Dr. Fayyad will cover:

  1. A historical summary of AI and machine learning, including what has worked, what didn’t, and why
  2. Why big data is different
  3. Economic drivers for change in storage technology
  4. Why the requirement for real-time data streaming and analysis is stronger than ever
  5. Why data science and related fields have become critical to almost all future analytical tasks
  6. How every company is becoming a big data company, even the smallest organizations
  7. How to fit the benefits of advanced analytics within the modern healthcare technology stack, and their accompanying issues and challenges
  8. Case studies showing the challenges and opportunities for big data, data science, and AI/ML

Data Science + X Talks


Panel on Data Science in Industry

  • McKay Hyde, Goldman Sachs
  • Melanie Crandall, L3
  • Berton Earnshaw, Recursion Pharma
  • Joshua Coon, Sandia National Laboratory

Previously: Data Science Day 2017

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