Seminars

Enabling Practical Deployments of Privacy-Preserving Technologies

Efficient and Dependable Deep Learning Systems

Democratizing Computer Hardware Design

Acceleration Techniques of Sparse Linear Algebra on Emerging Architectures

Building User-Driven Edge Devices

Optimizing Emerging Graph Applications Using Hardware-Software Co-Design

Efficient, Reconfigurable, and QoS-Aware Systems for Deep Neural Networks

Compiler Support for Robust and High Performance Autonomous Driving Environments

Securing Connected and Automated Vehicle through Proactive Vulnerability Analysis and Security Enhancement

In-SRAM Computing for Neural Network Acceleration

Efficient utilization of heterogeneous compute and memory systems

Towards Free, Open, and Ubiquitous Hardware Design

In-Memory Acceleration for General Data Parallel Applications