Tutorial Sessions

Tutorial Sessions
June 13, 2022(Monday)

[Tutorial #1] 09:00-10:30
Low-Power Computer Vision: Algorithms and Practice

Prof. Zhangyang “Atlas” Wang
The University of Texas at Austin, USA

Biography Abstract

[Tutorial #2] 09:00-10:30
Accelerator System Design Challenges from Real-time and Multi-DNN Workloads

Dr. Hyoukjun Kwon
Facebook Meta, USA

Biography Abstract

[Tutorial #3] 09:00-10:30
Training Spiking Neural Networks Using Lessons from Deep Learning

Dr. Jason K. Eshraghian
University of Michigan, USA

Biography Abstract

[Tutorial #4] 10:45-12:15
Machine Learning Reproducibility: Guidance for Practitioners

George K. Thiruvathukal
Loyola University Chicago, USA

Biography Abstract

[Tutorial #5] 10:45-12:15
Realizing a 5X Computer Vision Inference Speedup with PyTorch

Abhinav Goel
Purdue University, USA

Biography Abstract

[Tutorial #6] 10:45-12:15
Deep Neural Network Training Processor Design

Prof. Dongsuk Jeon
Seoul National University, Korea

Biography Abstract

[Tutorial #7] 13:15-14:45
Ultra-Low Power Biomedical AI Processor Design for Wearable Intelligent Health Monitoring Devices

Prof. Jun Zhou
University of Electronic Science and Technology of China, China

Biography Abstract

Prof. Liang Chang
University of Electronic Science and Technology of China, China

Biography

[Tutorial #8] 13:15-14:45
Compute-in-Memory Processors: A Cross-layer Approach

Prof. Yongpan Liu
Tsinghua University, China

Biography Abstract

[Tutorial #9] 15:00-16:30
Event-driven bio-inspired audio sensor front end for edgeTinyML

Prof. Shih-Chii Liu
University of Zurich and ETH Zurich, Switzerland

Biography Abstract

Dr. Kwantae Kim
University of Zurich and ETH Zurich, Switzerland

Biography

[Tutorial #10] 15:00-16:30
In-memory Computing Circuit Design for Neural Network Acceleration

Prof. Shyh-Shyuan Sheu
ITRI, Taiwan

Biography Abstract