AAIEA 2019
Accelerating AI for Embedded Autonomy

The Workshop on Accelerating Artificial Intelligence for Embedded Autonomy aims at gathering researchers and practitioners in the fields of autonomy, automated reasoning, planning algorithms, and embedded systems to discuss the development of novel hardware and software architectures that can accelerate the wide variety of AI algorithms demanded by advanced autonomous and intelligent systems.

Preliminary Program

9:00 - 9:15
Introduction to the workshop
Workshop organizers
9:15 - 10:00
Edge Intelligence: Bringing Autonomy to IoT Devices
Ali Keshavarzi
Adjunct Professor, Electrical Engineering, Stanford University
10:00 - 10:30
Coffee break
10:30 - 11:00
The system implications of neural recommendation at scale
Brandon Reagen, Facebook
11:00 - 11:30
Unique Challenges of VTOL Autonomy
Igor Cherepinsky
Director, Autonomy Programs, Sikorsky Aircraft
11:30 - 12:00
Geoff Shapiro
Associate Director, Collins Aerospace Program Office, UTRC
12:00 - 13:30
13:30 - 14:00
Analog Memory Hardware Accelerators for Deep Learning
Charles Mackin
IBM Research, Almaden
14:00 - 14:30
Accelerating for Multi-Robot SLAM on FPGA platforms: Visual Odometry and Place Recognition
Lincheng Yu
Tsinghua University, Beijing, China
14:30 - 15:00
Neuromorphic Computing: A Step Towards Energy-Efficient Machine Learning
Anup Das
Drexel University
15:00 - 15:30
Coffee Break
15:30 - 17:00
Panel Discussion
Enabling the Future of Embedded AI