Falcon: Accelerating Homomorphically Encrypted Convolutions for Efficient Private Mobile Network Inference
Type
Publication
In ACM/IEEE International Conference on Computer Aided Design (ICCAD)
Meng Li
Assistant Professor
I develop efficient and privacy-preserving AI systems through algorithm–hardware co-design, with applications in large language models, embodied AI, and multimodal intelligence.