Deep Learning, Machine Learning, and Artificial Intelligence Symposium 2018

Statement of Purpose

This will be a multi-day symposium focusing on deep learning, machine learning and artificial intelligence, technologies that are transforming a diverse set of scientific, engineering and business domains.The symposium has two components. An educational component will feature workshops led by Nvidia instructors on topics including deep learning for health care and image analysis, genomics, image segmentation and classification, neural networks and more. The second component will focus on how researchers are using these technologies in the Triangle and beyond, in particular at local institutions such as UNC-Chapel Hill, Duke and NC State, and at businesses such as SAS. We hope that this gathering and sharing of ideas and knowledge will generate new avenues of inquiry and new possibilities for collaboration.

This symposium was organized and sponsored by the Research Computing group at the University of North Carolina at Chapel Hill along with our partners at Nvidia and the SAS Institute. We would also like to thank our colleagues at Duke University and North Carolina State University for their contributions to making this event a reality.

Link to  Deep Learning Symposium Program.pdf

The agenda below contains links to the presentations where they are available.

Agenda

Thursday, September 27, 2018

9:00 — 9:15 Opening Remarks
Randy Guard
Executive Vice President and Chief Marketing Officer, SAS

9:15 — 9:30 Welcome
Mike Barker
Associate Vice Chancellor and CTO, Research Computing, ITS, UNC-Chapel Hill

9:30 — 10:30 Deep Learning Demystified
David Williams, Jeff Layton
Senior Solution Architect, Nvidia

10:30 — 10:50 Break

10:50 — 11:40 On Adversarial Training of Deep Networks
Lawrence Carin
James L. Meriam Professor of Electrical and Computer Engineering, Duke University

11:40 — 12:30 SAS Deep Learning: From Toolkit to Fast Model Prototyping
Wayne Thompson
Manager Data Science Technologies, SAS
Andre Violante
Staff Scientist, SAS

12:30 — 1:30 Lunch

1:30 — 2:00 Developing a Recommender System for Shark Presence along East Coast Beaches
Pamela Thompson
Faculty, Business/IS/CS Catawba College, Adjunct Computer Science UNC Charlotte

2:00 — 2:30 Simulation-Based Learning for Decision Making in Football
James Gilman
Graduate Student, Statistics, NC State University

2:30 — 3:00 Leveraging Deep Learning and Rapid Response Team Nurses to Improve Sepsis Management
Mark Sendak
Population Health and Data Science Lead, Duke Institute for Health Innovation

3:00 — 3:15 Break

3:15 — 4:00 Object Detection and Keypoint Detection in SAS Deep Learning
Xindian Long
Senior Computer Vision Scientist, Machine Learning Developer, SAS

4:00 — 4:45 How AI Might Design Your Next Prescription Medicine?
Olexandr Isayev
Assistant Professor at Eshelman School of Pharmacy, UNC-Chapel Hill

5:00 — 6:30 Reception

Thursday Nvidia Lab Schedules

1:30 — 3:00 Applied Deep Learning Lab
3:30 — 5:00 Deep Learning: Getting Started (Image Classification)

Friday, September 28, 2018

9:00 — 9:50 Using AI to Extract Deeper Meaning From the Face
Karl Ricanek Jr.
Associate Professor of Computer Science, UNC-Wilmington

9:50 — 10:30 Multimodal, Knowledgeable, and Stylistic Language Generation Models
Mohit Bansal
Assistant Professor of Computer Science, UNC-Chapel Hill

10:30 — 10:50 Break

10:50 — 11:20 Implementing AI systems with Interpretability
Ilknur Kaynar Kabul
Senior Manager, AI and ML R&D, SAS

11:20 — 11:50 Applying Machine-learning Techniques to Build Self-Reported Depression Prediction Models
Jeeyae Choi
Associate Professor, School of Nursing, UNC-Wilmington

11:50 — 12:20 Computer-Assisted Design: How AI/ML Can Help Engineers Make Better Design Decisions
Scott Ferguson
Associate Professor, Mechanical and Aerospace Engineering, NC State
University

12:20 — 1:20 Lunch

1:20 — 2:10 Complex Geospatial Object Based Image Analysis: Algorithms and Applications
Raju Vatsavai
Chancellor’s Faculty Excellence Program Associate Professor, Computer Science Department, NC State University

2:10 — 2:40 Brain MRI Extraction and Prediction Using Deep Neural Networks
Yi Hong
Assistant Professor, Computer Science, University of Georgia

2:40 — 3:10 Multimodal Feature Fusion and Synthetic Data Generation for Medical Image Analysis
Faisal Mahmood
Postdoctoral Fellow, Biomedical Engineering, Johns Hopkins University

3:10 — 3:30 Break

3:30 — 4:20 A New Paradigm for Privacy and Private Data Representation
Guillermo Sapiro
James B. Duke Professor of Electrical and Computer Engineering, Duke University

4:20 — 4:50 Deep Learning Quantum Matter
Joaquin Drut
Associate Professor and Melchor Fellow, Physics and Astronomy, UNC-Chapel Hill
Andrew Loheac
Graduate Student, Physics and Astronomy, UNC-Chapel Hill

4:50 — 5:00 Wrap Up, Thank You and Good-bye
Mike Barker
Associate Vice Chancellor and CTO, Research Computing, ITS, UNC-Chapel Hill

Friday Nvidia Lab Schedules

10:30 — 12:00 Deep Learning: Object Detection with DIGITS
1:30 — 3:00 Deep Learning: Neural Network Deployment with DIGITS and TensorRT
3:30 — 5:00 Image Segmentation (Intermediate)

Sights from the Symposium