Researcher Kurt Keutzer

Researcher Biography
http://www.eecs.berkeley.edu/Faculty/Homepages/keutzer.html

Current Projects

Data Efficiency for Point Cloud Perception Model
Efficient Deep Learning for ADAS/AV Through Systematic Pruning and Quantization
Embedded In-Car AI Assistant: Efficient End-to-End Speech Recognition and Natural Language Understanding for Command Recognition at the Edge
Using High-Level Structure and Context for Object Recognition
Training Data Augmentation for Autonomous Driving
An Innovative Approach to the Dual Problems of High-Resolution Input and Video Object Detection
Automated Search for Neural Net Architectures

Past Projects

Unified Neural Architecture Search Framework for Computer Vision
Efficient Model for Large-Scale Point Cloud Perception
Systematic Study of Neural Network Robustness Against Adversarial Attacks
Enabling Valuable Training Data through Domain Adaptation
Embedded natural language processing for in-car speech commands
Efficient Neural Networks through Systematic Quantization
Real-time, Energy Efficient Video Object Detection and Tracking
Domain Adaptation for Realistic LiDAR Data Synthesis
Efficient Neural Nets for Real-Time object-recognition on High-Resolution Images
Safe and Effective Learning through Formal Simulation
Energy-Efficient Deep Neural Nets for Occupancy-Grid Mapping
Design Space Exploration for Deep Neural Nets for Advanced Driver Assistance Systems