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CLSAC 2019

Benefits and Challenges of Large-Scale Analytics for Society


October 7--10 , 2019
Hotel Annapolis
126 West Street
Annapolis, MD  21401

Theme: 
​As the use of machine learning and artificial intelligence expands to become an integral part of our basic infrastructure, there is an increasing need to understand the impacts and vulnerabilities of these algorithms. The eighth CLSAC conference will explore efforts to address societal impacts of large-scale analytics including, for example, consequences of "fooling" ML algorithms in automated systems, consequences to data privacy and policy, understanding and incorporating uncertainty in analytics models and data, and AI explainability. The conference will engage experts from industry, government, and academia to understand how the various communities are addressing these challenges for large-scale analytics.

Organizing Committee:
John Feo (PNNL)
​Jim Ang (PNNL)

David Haglin (Trovares Inc.)
Richard Murphy (Micron Technology)
Ron Oldfield (SNL)
Steve Pritchard (Independent Consultant)
J.T. Halbert (DoD)
​T.C. Tuan (DoD)
Candace Culhane (LANL)

         2019 Sponsors
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Agenda

2019_agenda.pdf
File Size: 205 kb
File Type: pdf
Download File



Monday, October 7
7:00-8:30 PM
Registration and Welcome Reception (Annapolis Atrium)

Tuesday, October 8

7:00 - 8:30 am
Breakfast and Registration (Atrium)
8:00 - 8:30 am
Welcome
​George Cotter Award for Vision and 
Leadership in the Field of Data Analytics
Jim Ang, Candy Culhane
Keynote
8:30 - 9:15 am
HPC and AI – The Next Horizon -  Advancing Humanity’s Grand Challenges
Debra Goldfarb, Intel
Session 1: Applications 1
TC Tuan, Moderator
9:15 - 10:00 am
DataOps -- a new methodology for transformational analytic outcomes
Harlan Kadish, Tamr Inc.
10:00 - 10:15 am
Break (Atrium)
10:15 - 11:00 am
Machine Learning of Interatomic Potentials
Justin Smith, LANL
11:00 - 11:45 am
Robust AI: How to protect your networks - whether cyber or neural
Steven Forsyth, NVIDIA
Ed Raff, BAH
11:45 - 12:30 pm
Panel Discussion
12:30-1:45 pm
Lunch (Atrium)
Session 2: Applications 2
John Feo, Moderator
1:45 - 2:30 pm
Scalable Predictive Analytics for Optimizing Power Network Operations and Maintenance
Nagi Gabraeel, Georgia Institute of Technology
2:30 - 3:15 pm
Modeling Complex Data with Hypergraphs
Emilie Purvine, PNNL
3:15 - 3:30 pm
Break
3:30 - 4:15 pm
Predicting Behavior in Complex, Interactive Systems
Julie Huff,
Northrup Grumman
4:15 - 5:00 pm
Panel Discussion
6:00 - 7:30 pm
Dinner (Atrium)
The Evolution of Cyberspace and National Security – Challenging Assumptions
Sam Visner, NCCoE/NIST
7:30 - 9:00 pm
Reception (Mainsale/Spinnaker)

Wednesday, October 9

7:30 - 8:30 am
Breakfast
Keynote
8:30-9:15am
Early and Often:  Taking AI Ethics Seriously
Dr. Heather Roff, The Johns Hopkins University Applied Physics Laboratory
Session 3: Software
Ron Oldfield, Moderator
9:15 - 10:00 am
Software Data Analytics Framework for Detecting Malware and Machine Learning Back Doors
Doug Joseph, ARM
10:00-10:15 am
Break
10:15 - 11:00 am
Data Analytics are Powerful – Handle with Care
Jeremy Wendt, SNL
11:00 - 11:45 am
Data Science Needs Interactive Supercomputing
Bill Reus, DoD
11:45 - 12:30 pm
Panel discussion
12:30-6:00 pm
Free Time (lunch and dinner on your own)
6:00-7:30 pm
Random Access Session (Ballroom)
Sign-up sheet will be at the registration table.
​Talks limited to 10 minutes. 

JT Halbert, Moderator
7:30-9:00 pm
Reception and Poster Session (Mainsail/Spinnaker)
Steve Pritchard, Moderator
Poster
Student
Simra Ali
Georgetown University
Robert D’Angelo-Cosme
Georgetown University
Ricky Laishram
Syracuse University
Advancing the Bases: Tensor Methods and the Frontiers of Generality
Matthew Merris
Boise State University
Vidya Nagaraju
University of Massachussets

Thursday, October 10

7:00 - 8:30 am
Breakfast
Keynote
8:30 - 9:15 am
Addressing the Pitfall of AI in Military Operations
Brigadier General Matthew Easley, Director of Army Artificial Intelligence
Session 4: Hardware
Richard Murphy, Moderator
9:15 - 10:00 am
xBGAS: Toward a RISC-V Extension for Scalable System Addressing
Michel Kinsy, Boston University
10:00 - 10:15 am
Break
10:15 - 11:00 am
Accelerating Large Scale Analytics with Cerebras
Andy Hock, Cerebras
11:00 - 11:45 pm
AI and the Memory Innovations That Will Be Created as a Result
Steve Pawlowski, Micron
11:45 - 12:30 pm
Panel Discussion
12:30 - 1:45 pm
Lunch
Session 5: Policy
David Haglin, Moderator
1:45 - 2:30 pm
Smart City Data Collection at Scale Has Major Privacy and Policy Challenges
Isaac Potoczny-Jones, Tozny LLC
2:30 - 3:15 pm
Data as the Driver of Biomedical Research: Why aren't we going faster?
Jack Collins, Frederick National Laboratory for Cancer Research
3:15 - 3:30 pm
Break
3:30 - 4:15 pm
Machine Learning at the Edge: Impact on Analytics, Business, and Privacy
Chris Krieger, DoD
4:15 - 5:00 pm
Panel Discussion
5:00 - 5:15 pm
Closing Remarks and Adjourn
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