efficient deep learning architectures

Liangyu Wang

Ph.D. Student, Computer Science

LLM efficient deep learning architectures Reinforcement Learning Efficient AI privacy-preserving AI

Liangyu Wang's research focuses on efficient systems and optimization for large language models, including distributed training and inference, GPU systems, zeroth-order optimization, privacy-preserving training, and matrix-based optimizers.

KAUST-CEMSE-ECE-PhD-Dissertation-Defense-Design-of-Neuromorphic-Object-Detection-Systems

Design of Neuromorphic Object Detection Systems

Diego Augusto Silva, Ph.D. Student, Electrical and Computer Engineering

Jul 16, 16:00 - 17:00

B3 L5 R5209

event-based object detection neuromorphic vision systems efficient deep learning architectures

This dissertation advances event-based object detection by developing efficient deep learning frameworks such as ReYOLOv8 and Chimera, introducing novel encoding and augmentation techniques, releasing a new neuromorphic dataset, and demonstrating a real-time, low-power traffic monitoring system that highlights the practical potential of bio-inspired vision systems.