Area of research
Artificial Intelligence · Computer Vision and Pattern Recognition
Research interest
Research interests include Quantum Computing Algorithms and Architecture, Quantum Information and Cryptography, Advanced Neural Network Applications, and Low-power high-performance VLSI design.
Artificial intelligence for quantum computing
Lightening-Transformer: A Dynamically-Operated Optically-Interconnected Photonic Transformer Accelerator
Atomique: A Quantum Compiler for Reconfigurable Neutral Atom Arrays
Hybrid Gate-Pulse Model for Variational Quantum Algorithms
SnCQA: A hardware-efficient equivariant quantum convolutional circuit architecture
A Fully-Integrated Energy-Scalable Transformer Accelerator Supporting Adaptive Model Configuration and Word Elimination for Language Understanding on Edge Devices
QuantumNAS: Noise-Adaptive Search for Robust Quantum Circuits
Enable Deep Learning on Mobile Devices: Methods, Systems, and Applications
TorchQuantum Case Study for Robust Quantum Circuits
SnCQA: A hardware-efficient equivariant quantum convolutional circuit architecture
SpAtten: Efficient Sparse Attention Architecture with Cascade Token and Head Pruning
Searching Efficient 3D Architectures with Sparse Point-Voxel Convolution
GCN-RL Circuit Designer: Transferable Transistor Sizing with Graph Neural Networks and Reinforcement Learning
SpArch: Efficient Architecture for Sparse Matrix Multiplication
HAT: Hardware-Aware Transformers for Efficient Natural Language Processing
APQ: Joint Search for Network Architecture, Pruning and Quantization Policy
AMC: AutoML for Model Compression and Acceleration on Mobile Devices